warehouse automation case study

Warehouse Automation Explained: Types, Benefits & Best Practices

This article explains how to automate your warehouse, why it’s worth it and the challenges you may encounter. Learn about various automation technologies and our advice on when and how to implement them.

This article will cover:

• When to automate your warehouse
• How to automate your warehouse
• Warehouse automation best practices
• Warehouse automation trends

What Is Warehouse Automation?

Warehouse automation is the process of automating the movement of inventory into, within, and out of warehouses to customers with minimal human assistance. As part of an automation project, a business can eliminate labor-intensive duties that involve repetitive physical work and manual data entry and analysis.

For example, a warehouse worker may load an autonomous mobile robot with heavy packages. The robot moves the inventory from one end of the warehouse to the shipping zone and software records the movement of that inventory, keeping all records current. These robots improve the efficiency, speed, reliability and accuracy of this task.

But warehouse automation does not require physical or robotic automation, and in many cases simply refers to the use of software to replace manual tasks. However, this scenario illustrates how robots and humans work together to accomplish repetitive tasks while minimizing fatigue and injury.

Warehouse Automation

Key Takeaways:

• Automation can start with a warehouse management system (WMS), data collection and inventory control.
• While warehouse automation has significant upfront costs, there are many benefits, ranging from improving operations to minimizing human error.
• The future of automating the warehouse lies in robotics and integrating artificial intelligence (AI) onto the warehouse floor.

What Is Digital Automation?

Digital automation uses data and software to reduce manual workflows. Automatic identification and data capture (AIDC) technology, like mobile barcoding, is an example of digital automation in the warehouse.

The benefits of digital process automation include the ability to integrate with enterprise resource planning (ERP) systems , enhanced security, greater data management efficiency, reduced operational and legal risks, and improved safety—but from the warehouse perspective, it reduces manual processes and eliminates human errors. AIDC technology like radio frequency identification (RFID) and mobile barcode scanning can enhance the worker experience, improve customer service and reduce operational costs associated with human error.

Implementing digital automation technology requires a significant upfront investment. These costs include hardware, software and support contracts and the time and resources required to implement the systems and train employees. In addition, digital automation can increase the risk of lost or corrupted data and cybersecurity threats.

What Is Physical Automation in the Warehouse?

Physical automation is a way to use technology to minimize employee movement and build more efficient workflows. Robots are one example of how it works in the warehouse.

The advantages of physical automation include increased warehouse capacity and efficiency, enhanced reliability and scalability of services and improved performance. The downsides are the significant upfront expenses, the scarcity of a skilled workforce to manage and maintain the system, high maintenance costs and equipment that is meant for highly-specific functions.

To take advantage of automated warehouse systems , businesses need advanced planning and organization. These systems are more suited for large-volume warehouses and distribution centers with space to accommodate specialized equipment.

How Does Warehouse Automation Work?

Warehouse automation works by using software and technology like robotics and sensors to automate tasks. These products work in concert with existing tools like inventory management software .

Warehouse automation helps ensure that business-critical operations in your facilities meet customer demand. It starts with a warehouse management system (WMS) that automates manual processes and data capture, inventory control and supports data analysis. These systems integrate with other solutions to efficiently manage and automate tasks across different business and supply chain functions .

Video: What Is Warehouse Automation?

Categories of Warehouse Automation Explained

Warehouse automation varies from relatively simple to quite complex. Basic automation uses planning, machinery and vehicles to reduce repetitive tasks. Advanced systems take advantage of artificial intelligence and robotics.

Warehouse automation categories include:

• Basic Warehouse Automation: This type of automation refers to simple technology that assists people with tasks that would otherwise require more manual labor. For example, a conveyor or carousel moves inventory from point A to point B.
• Warehouse System Automation: This type of system uses software, machine learning, robotics and data analytics to automate tasks and procedures. For example, a warehouse management system reviews all the orders that need to be filled in a day and has users pick like items to fulfill all those orders at once so they don’t traverse the warehouse back and forth multiple times.
• Mechanized Warehouse Automation: This kind of warehouse automation uses robotic equipment and systems to assist humans with warehouse tasks and procedures. Autonomous mobile shelf loader robots that lift racks of products and deliver them to human pickers to retrieve and sort is one example.
• Advanced Warehouse Automation: Advanced warehouse automation combines mechanized warehouse robotics and automation systems that can replace labor-intensive human workflows. For example, a robotic forklift fleet that uses advanced AI, cameras and sensors to navigate a warehouse and communicate each forklift’s location to an online tracking portal.

Types of Warehouse Automation Technology

There are many types of warehouse automation because there is a wide range of warehouse technology and systems available. Warehouse automation aims to minimize manual tasks and speed up processes, from receiving to shipping.

Warehouse automation technology includes:

• Goods-to-Person (GTP): Goods-to-person fulfillment is one of the most popular methods for increasing efficiency and reducing congestion. This category includes conveyors, carousels and vertical lift systems. When properly applied, GTP systems can double or triple the speed of warehouse picking.
• Automated Storage and Retrieval Systems (AS/RS): AS/RS are a form of GTP fulfillment technology that includes automated systems and equipment like material-carrying vehicles, tote shuttles and mini-loaders to store and retrieve materials or products. High-volume warehouse applications with space constraints tend to utilize AS/RS systems.
• Automatic Guided Vehicles (AGVs): This class of mechanized automation has minimal onboard computing power. These vehicles use magnetic strips, wires or sensors to navigate a fixed path through the warehouse. AGVs are limited to large, simple warehouse environments designed with this navigation layout. Complex warehouses with lots of human traffic and space constraints are not good candidates for AGVs.
• Autonomous Mobile Robots (AMRs): More flexible than AGVs, AMRs use GPS systems to create effective routes through a specific warehouse. They use advanced laser guidance systems to detect obstacles, so AMRs can safely navigate dynamic environments with lots of human traffic. They are easy to program with routes and easy to implement quickly.
• Pick-to-Light and Put-to-Light Systems: These systems use mobile barcode scanning devices synced to digital light displays to direct warehouse pickers where to place or pick up selected items. They can dramatically reduce walking and searching time and human error in high-volume situations.
• Voice Picking and Tasking: The use of voice-directed warehouse procedures, also known as pick-by-voice, uses speech recognition software and mobile headsets. The system creates optimized pick paths to direct warehouse workers where to pick or put away a product. This method eliminates the need for handheld devices like RF scanners, so pickers can concentrate on their task with improved safety and efficiency.
• Automated Sortation Systems: Sortation is the process of identifying items on a conveyor system and diverting them to a warehouse location using RFID, barcode scanners and sensors. Companies use automated sortation systems in order fulfillment for receiving, picking, packing and shipping.

When to Automate Your Warehouse

Deciding when to automate your warehouse depends on a host of factors. You’ll need to evaluate your processes and procedures, examine your supply chain, recruit in-house expertise and identify gaps in current technology and future business goals.

8 Questions to Decide If It’s Time to Automate Your Warehouse

Answer these questions before committing to warehouse automation projects:

• Are your customer orders delayed due to a limited workforce?
• Are your existing warehouse processes and procedures labor-intensive?
• Is your order fulfillment capacity declining?
• Are your inventory counts inaccurate?
• Are you still using legacy warehouse management software or manual inventory management tools like spreadsheets?
• Is customer satisfaction data indicating problems in the supply chain?
• Do you have to increase/decrease your workforce to meet fluctuating demand?
• Do you have buy-in from key stakeholders?

How to Automate Your Warehouse

Automating a warehouse requires a project plan. You’ll need to involve stakeholders, create a project schedule, complete a risk assessment and designate goals and deliverables.

First, form a support team and designate project manager(s). They will determine a project schedule and build a timeline and deliverables calendar. Next, make implementation support plans with feedback from all levels of management (including corporate leadership and warehouse managers from all locations). Finally, choose the warehouse automation that best supports your business goals, customer demand, and incorporates feedback from your team, time and available resources. When reviewing automation options, you’ll need to research these options and request demonstrations. Implementing mobile barcode scanning has different requirements than installing an AS/RS inventory management system, for instance.

5 Steps to Automate Your Warehouse

Use this sample five-step plan to get started with warehouse automation.

• Create an implementation committee. Form a committee of internal stakeholders who have expertise on current warehouse performance, capabilities and challenges, and understand existing technology gaps. Consider adding third-party experts who know about supply chain automation and have experience relative to your industry and warehouse operations.
• Collect critical data. Successful warehouse automation relies on data about your existing supply chain and business-critical warehouse operations . Before implementing new automation technology, evaluate your current data collection process and infrastructure. You’ll want to assign ownership of data migration to skilled IT stakeholders.
• Evaluate your inventory controls. Inventory control is at the core of warehouse operations. Before implementing a warehouse automation solution, determine or refine your standard operating procedures (SOPs) for inventory control. Include SOPs for purchasing, shipping, receiving, customer satisfaction and inventory loss. Define the key performance indicators (KPIs) to measure the success of automated inventory control processes and procedures. Evaluate the inventory accounting method currently in place (for example, periodic or perpetual systems) and determine how automation will impact it. Read the guide about inventory control to learn more.
• Implement a warehouse management system (WMS). WMS platforms feature software modules that help control and track inventory, manage warehouse operations, reduce labor costs associated with manual tasks, and improve customer service. A modern WMS supports mobile devices and should be able to work with your existing enterprise software.
• Determine what kind of warehouse automation you want. Is your goal to use automation to streamline manual data entry and reduce labor costs associated with back-office warehouse operations and accounting? Or, are you expanding your warehouse footprint or adding locations and think it’s time to use advanced physical process automation like robots and GTP systems? Determining the type of warehouse automation that aligns with goals and customer demand is essential.

Why Should You Automate Your Warehouse?

An inefficient warehouse negatively impacts the customer experience. Automated warehouses do more with less and thrive under increased customer demand.

Benefits of Warehouse Automation

Using automation to improve warehouse operations brings a wide range of advantages, from running more efficiently to minimizing human error. Here’s a list of the most commonly cited benefits:

• Increased warehouse throughput
• Better resource utilization
• Reduced labor and operational costs
• Improved customer service
• Reduced handling and storage costs
• Reduced human error
• Minimized manual labor
• Increased productivity and efficiency
• Improved employee satisfaction
• Enhanced data accuracy and analysis
• Reduced stockout events
• Optimized warehouse space
• Greater inventory control
• Improved workplace safety
• Fewer shipping errors
• Reduced inventory loss
• Enhanced material handling coordination
• Improved order fulfillment accuracy

Challenges of Warehouse Automation

Despite the benefits related to warehouse automation, it also has some challenges. For example, it requires significant capital to get up and running and expertise to establish and maintain the system, which many companies don’t have in-house and can be difficult to find. Additionally, equipment can break down, often at the worst of times, leading to downtime and repair/maintenance costs.

To minimize maintenance issues, you’ll want to set up maintenance schedules. Consider contracting with a third-party vendor that provides skilled maintenance and repair experts to ensure the new systems and equipment stay operational. The high upfront costs for equipment and setup typically pay for themselves over time through efficiencies and increased sales, but businesses need to carefully anticipate and mitigate some challenges with proper risk assessment and planning. The planning phase should include regular inventory audits to verify the accuracy of new data from automated processing against existing records. See below for more details on how much it costs to automate your warehouse.

Warehouse Automation Best Practices

The warehouse’s role in the supply chain has evolved significantly. Modern warehouses provide business-critical, cost-saving functions and add value to customer experiences.

Here’s a list of six warehouse automation best practices to consider:

• Integrate with a WMS : Make sure the warehouse automation systems you choose integrate with a WMS platform. Look for a solution that can manage inventory controls, track inventory, monitor and report on labor costs, integrate dashboards and automates these capabilities. Learn more about WMS features and the difference between inventory management and warehouse management .
• Invest in Scalable Solutions: Your technology should scale with your business. The system should account for adding future warehouses, employees, equipment and new supply chain partnerships, like 3PLs or drop shippers.
• Automate Data Collection: Regardless of the type and level of warehouse automation, you're considering long term, start with a solution that automates data collection, transfer and storage. Cloud-based solutions paired with mobile barcode scanners create a low-cost, low-risk path to automation. This ecosystem will help you eliminate human error, capture critical warehouse performance and inventory data, and store it in a centralized cloud database for further analysis.
• Perform Continuous Cycle Counts: Cycle counts monitor inventory levels against the inventory data record and are a key feature of WMS. Once you have automated data collection systems in places, you can automate continuous cycle counts with mobile barcode scanning or RFID sensors. Then you can use dashboards to check for inventory discrepancies.
• Optimize Receiving: Warehouse data collection starts with receiving, so you want a system that can collect as much data as possible upfront to help direct warehouse workflows. Identify the incoming product (dimensions, classifications, packaging), then set rules in your WMS that determine how to handle it, where to store it and how to direct available resources to put it away.
• Evaluate Warehouse Design: Many physical automation solutions, including GTP and AS/RS systems, AGVs and sortation systems, require specific warehouse layouts and ample space to be successful. Consider reworking the design of existing warehouses and distribution centers to optimize them for automation technology. Work with solutions vendors, architects and contractors that understand your unique requirements. You’ll want to include this evaluation in your implementation budget.

What Warehouse Processes Can Be Automated

Many warehouse processes can be automated, such as bin tracking, cycle counting and order picking. Warehouse process automation leads to more cost-effective operations and reduces product handling costs.

Warehouse Processes that Benefit from Automation

The right warehouse automation technology can automate tasks that touch every aspect of order fulfillment and inventory control, including:

• Receiving: You can use mobile devices to quickly capture data in your warehouse’s receiving area. Integrated software captures, processes and stores data that impacts downstream and upstream automated workflows.
• Returns: Automated sorting systems and equipment like conveyors can automate return processing procedures. Use them to sort products to return-to-stock shelves or put away in designated storage locations.
• Putaway: Putaway refers to the act of moving products from receiving to storage. Physical and digital warehouse process automation can make putaway more efficient and accurate. Automating this process can also help facilitate cross-docking, where goods are rapidly sorted, processed and placed onto trucks bound for different destinations instead of being stored in the warehouse.
• Picking: Manual order picking is the costliest warehouse activity—warehouse travel time can consume as much as 50% percent of working hours. Using GTP systems and autonomous mobile robots can rapidly increase the speed and efficiency of moving inventory from stock locations to fill customer orders.
• Sorting: Sorting and consolidating warehouse inventory is a time-consuming, often confusing task. Automated sortation and AS/RS systems improve inventory accuracy and quality control by recognizing and handling small or fragile inventory separately.
• Replenishment: Automated inventory tracking and cycle counting empower automated reorders. When an inventory item reaches a designated par level, the system automatically triggers an order request and flags it for approval. Automated replenishment can help prevent overstocking costs and inventory loss due to spoilage and theft.
• Packaging: The packaging stage of order fulfillment is critical due to the high cost and environmental impact of packaging materials. Automated packaging and cartonization systems use algorithms to determine the best type of shipping packaging based on product attributes (like durability), dimensions and material costs.
• Shipping: Automated shipping systems uses conveyors, scales, dimension sensors, printers and software applications to determine available carriers, estimate shipping rates and apply labels to packages for shipment.

Real World Examples of Warehouse Automation

The popularity and growth of ecommerce has increased the demand for warehouse automation. Here are some examples of how it works across various industries:

• Barcode Scanning: Amazon uses automated barcode scanning and labels to dominate online retail and optimize warehouse operations. This automation is responsible for Amazon’s famously innovative storage system. Unique barcodes are placed on incoming products and on the shelves where they reside. When it’s time to ship a product, employees use the updated picking list to find the product location based on automated routes optimized for efficiency and flow.
• Picking Automation with GTP Systems: Nike implemented a GTP picking system in its new distribution center in Japan. The automated GTP picking system uses autonomous robots to carry products and packages loaded on shelves or pallets directly to warehouse workers for order fulfillment. The new warehouse automation helped transform logistics and enable Nike to provide same-day delivery to customers in Japan.
• Inventory Automation with AS/RS Systems: IKEA operates highly automated warehouse facilities worldwide. Its distribution centers feature AS/RS inventory automation systems and equipment, including 100-foot-tall trilateral stacker cranes and conveyor rack systems capable of automatically transferring 600 pallets an hour to dispatch areas.
• Back-Office Automation: WMS platforms with digital process automation features can optimize back-office operations. iAutomation , a distributor of machine control solutions and services to OEM machine builders, had siloed applications that slowed productivity, as staff had to manually import and export data across multiple systems to support sales and customer service teams. The company implemented NetSuite's Inventory Management , CRM and Manufacturing Execution System to enhance back-office sales and customer support functions with automated barcoding, case management and issue tracking solutions.

Warehouse Automation Trends & Statistics

Warehouse automation will help address insufficient warehouse space, inefficient inventory operations and labor shortages. Online retail sales of physical goods are expected to approach $500 billion dollars (opens in new tab) , increasing warehouse services demand.

More than 90% of warehouse operators report that cost-cutting measures are critical (opens in new tab) to successfully balance the need for more space and services and the difficulty of hiring and retaining a qualified workforce to meet demand. Failing to plan for these trends may cost more than the expenses associated with warehouse automation.

What is the State of Robotics and Automation in Warehousing Now?

Modern warehouses focus less on traditional storage roles and more on value-added services, order customization and rapid flow-through processes that stage products according to just-in-time inventory principles.

Here's a list of the digital and physical warehouse automation and robotics trends empowering the modern warehouse:

• Robotics: The investment in warehouse robotics startups increased (opens in new tab) by 57% in the first quarter of 2020 to more than $380 million. The trend will continue to see momentum in a post-pandemic economy and areas with workforce shortages, like Japan.
• Cobotics: Cobotics refers to a collaboration between person and robot (cooperation and robotics forms cobotics). Cobots, designed to work with people, do not replace human tasks. Cobots in warehouse automation include AMRs that can scan their environment. This cobot AMR can avoid collisions with humans and human-operated machinery by recognizing changes in its 360-degree field of vision and can safely drive backward when necessary.
• Supply Chain as a Service: Warehouse service-based markets are growing to fill the demand for flexible warehouse operations and automated technology like autonomous robots. Companies offering subscription-based, full-service automated warehouse solutions seek to replace manufacturers and service providers that offer automated equipment and system sales.
• Blockchain Technology: Although still in its infancy, blockchain technology is a secure automated network that uses cryptography to create data transfers in blocks on a shared digital ledger. Blockchain technology has implications for warehouse operations and inventory management because of its advanced data authentication, validation and transparency. Blockchain databases could allow every stakeholder in complex supply chains to connect and share permanent, automated records for every transaction made, with shared data storage accessible to everyone within the secure network.
• Warehouse Drones: Intelligent drone fleets powered by advanced algorithms and connected to cloud-based WMS can help manage inventory inside warehouses. Some warehouse drones are equipped with visual sensors or barcode scanners to track inventory and automate procedures like cycle counting.
• Fast Shipping: The “Amazon effect” of one- or two-day shipping has created intense demand for rapid online shipments regardless of who sells the product. Same-day shipping will continue to drive warehouse automation that speeds up order fulfillment tasks like picking and improves the accuracy and cost-effectiveness of automated packaging and shipping procedures.
• Warehouse Cleaning: There is already a market for automated industrial-sized robotic floor cleaners that navigate complex warehouse layouts. Now, a new class of automated mobile cleaning robots is emerging to safely sanitize and disinfect high-touch indoor workplaces like warehouses and distribution centers with UV lights and sanitization chemicals.
• Mobile Shelving: Amazon is the most famous example of companies using GTP systems powered by AGVs and AGRs. The autonomous robot fleets can load and transport mobile shelving units with stored inventory to designated locations. This enables workers to pick orders with minimal movement and walking time.
• Autonomous Vehicles: Autonomous robotic forklifts are already in use at automated warehouse and distribution centers. Autonomous vehicles are expected to move further up the supply chain to include automated delivery trucks that transport inventory between warehouses, manufacturers and retail locations.
• ERP Integrations: API technology and machine learning (ML) are empowering automation systems that integrate with ERP suites to create an end-to-end automated business platform. Further improvements in automation and ERP applications will free up back-office workforces to perform more value-added, creative and customer-focused tasks.
• Big Data: The move toward cloud-based applications and databases capable of collecting, processing and storing large datasets that are easily accessible will drive data analytics around warehouse operations further.
• IoT: Although not strictly an emerging technology, RFID sensors continue to be a driver for new IoT applications that streamline supply chains and warehouse operations. IoT expands warehouse visibility by providing location data on equipment and inventory in real time. The mobility, affordability and real-time inventory tracking capability of RFID sensors provide enhanced data collection capabilities across systems.
• Wireless Fleet Management: Innovations in IoT applications, cloud databases and sensor technology has created the ability to manage automated fleet vehicles wirelessly. Onboard computers communicate telemetry to your system with detailed information about equipment location, maintenance schedules and accident alerts.

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How Much Does It Cost to Automate Your Warehouse?

The cost of warehouse automation varies depending on the level and type of automation. However, a full overhaul of your existing infrastructure can cost millions of dollars.

To determine if warehouse automation is right for your business, start by calculating your estimated ROI. Estimate the budget for current warehouse labor and existing equipment and include any expected annual increases. Next, calculate your average turnover rate for warehouse employees and factor in the cost of hiring and training new employees. Now, determine the purchase cost of the new automated systems and equipment, and factor in estimated labor and cost savings, training and implementation costs and ongoing maintenance expenses. Finally, compare these figures to determine the estimated minimum ROI for warehouse automation.

In addition to cost and ROI calculations, consider how warehouse automation might impact other operations. For example, if you're upgrading to digital process automation software or a feature-rich WMS solution, how will the new system create value for other warehouse functions? Will you save time and resources with warehouse documentation procedures for purchase orders and invoicing? How will an automated platform improve your cash flow tied to supply chain operations? What about customer service metrics? How will automated warehouse processes and procedures improve your omnichannel and delivery capabilities or product offerings?

Implement Warehouse Automation with Software

Warehouse automation using inventory tracking and warehouse management systems has tremendous potential and will be crucial to the evolution of modern warehouse management. Moving products from one place to another with as little human contact as possible helps create supply chains capable of rapid, seamless order fulfillment. Investing in these machines and advanced devices will help companies continue to meet customer expectations that seem to grow by the day.

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The Ultimate Guide to Warehouse Automation

30 min read

60-Second Summary

Are you considering implementing automation in your warehouse but aren’t sure where to start? This ultimate guide will introduce the different types of warehouse automation and technologies to assist you in choosing the right solution to help your operation successfully meet its goals.

An Overview of Warehouse Automation

Warehouse automation is the process of automating repetitive tasks involved with the movement of inventory in and out of a warehouse, distribution center, micro-fulfillment center, or retail space using equipment, robotics, or software. Warehouse automation is used to streamline inventory handling to reduce overhead costs and speed-up order fulfillment, distribution, or replenishment while driving efficiency and output. Utilizing a form of automation can even minimize worker injury, fatigue, and error when implemented correctly.

Automation can be simple or fairly complex, ranging from using barcode scanners to autonomous robots that aid workers with moving inventory or preparing items for shipping. iHerb, an online health product retailer , uses automation in its fulfillment facilities, relying on the OPEX® Perfect Pick® automated storage and retrieval system, allowing them to process over 40,000 orders per day with same-day shipping.

Rapid Industry Adoption

With the need for supply chain technology and automation growing to meet rapidly fluctuating consumer and market demand, many companies are implementing automation to some degree in their warehouses and fulfillment centers. According to Research and Markets, the global warehouse automation market is expected to reach USD $33.34 billion from 2022-2026 at a CAGR of 13.60% .

Types of Warehouse Automation

Warehouse automation comes in many different forms, all ranging from simple to complex, but the two main types are digital and physical warehouse automation, each of which can be broken down into different categories.

Digital Warehouse Automation

While you may be familiar with the robots and large  equipment used in  warehouses, digital warehouse automation is comprised of the software and data used to reduce the need for human intervention and manual, labor-intensive processes. Digital automation can be used for reading barcodes, automatic identification and data capture (AIDC), radio frequency identification (RFID), and similar applications.

Digital warehouse automation provides many advantages – faster and more accurate inventory handling, improved security, better data management, reduced operational and legal risks, and improved safety. It can also result in higher profitability and reduced expenses. However, digital automation may require significant planning and capital upfront or during the use of software.

Physical Warehouse Automation

Physical warehouse automation can consist of robotics, equipment, conveyors, and similar technology to streamline material handling workflows and reduce manual, labor-intensive processes. Physical warehouse automation has a variety of advantages, including better warehouse space utilization, improved worker safety, more accurate order fulfillment, improved inventory security, and increased inventory storage.

Implementing physical automation in your warehouse can provide a fast ROI, helping to increase profitability, reduce overhead and labor expenses, and improve customer service and satisfaction. However, to implement this type of equipment in your warehouses or distribution centers, you’ll need significant capital upfront and comprehensive planning beforehand. Physical automation systems will also need maintenance and service to keep downtime at a minimum.

Classifications of Warehouse Automation

Warehouse automation can be broken down into smaller categories, ranging from simple pieces of equipment to complex systems that can use both physical and digital automation technologies.

The four main categories are:

1. Basic Warehouse Automation

Basic warehouse automation assists with manual and repetitive tasks to help move inventory throughout points in the distribution or manufacturing process. Basic automation can include conveyors or carousels.

2. Warehouse System Automation

Warehouse system automation typically combines software with warehouse automation equipment, but can include other elements such as robotics, machine learning, and data analytics to automate tasks and workflows involving order fulfillment, inventory management, shipping, returns processing, or similar applications.

This type of automation can include inventory software, warehouse management software (WMS), conveyors, automated storage and retrieval systems (AS/RS), automated sorting systems, or robots.

3. Mechanized Warehouse Automation

Mechanized warehouse automation consists of robotics equipment and systems that assist warehouse employees with tasks and workflows to minimize human intervention in repetitive tasks or reduce labor-intensive procedures.

An example of mechanized warehouse automation is the OPEX® Infinity® AS/RS, a system with a grid racking structure where wireless robots retrieve totes containing inventory, which are then delivered to a presentation port where an operator can fulfill an order.

4. Advanced Warehouse Automation

Similar to mechanized warehouse automation, advanced warehouse automation combines robotics and equipment with machine learning or artificial intelligence (AI) to replace manual and labor-intensive workflows entirely.

Advanced warehouse automation includes autonomous mobile robots (AMRs) that can navigate freely to move goods or perform tasks using AI, sensors, and cameras in addition to other automation.

Types of Warehouse Automation Technologies

Automated storage and retrieval systems (as/rs), goods-to-person systems (g2p or gtp), other types of as/rs systems.

• Unit-Load Systems Unit-load systems handle heavy loads (usually between 1000-5500 lbs.) of full or partial pallets and cases.
• Mini Load Systems Similar to unit-load systems, mini-load systems handle smaller loads of totes, trays, or cartons.
• Crane-Based Crane-based systems are designed to retrieve pallets or totes using a fixed or moveable crane located in an aisle.
• Shuttle Based Commonly a feature of G2P systems, shuttle-based systems deliver inventory using a shuttle, bot, or automated guided vehicle (AGV) that runs on a track within an AS/RS or G2P racking structure. These vehicles deliver totes or trays to a workstation that can be integrated with the system.
• High Density AS/RS Systems A high-density AS/RS system has a dense storage racking structure that relies on AMRs or AGVs to navigate the racking system to find and retrieve totes or trays. Inventory is then delivered and presented to an operator at an integrated workstation to perform warehouse activities.
• Carousel Systems Carousel systems are similar to conveyor systems, but retrieve and store inventory by spinning until an item is placed or removed.
• Vertical Lift Module (VLM) Systems A vertical lift module system (VLM) is a fully automated and enclosed structure where an inserter/extractor is surrounded by totes or trays to retrieve and deliver inventory.

Automated/Automatic Guided Vehicles (AGVs)

Autonomous mobile robots (amrs), pick-to-light or pack-to-light systems, voice-picking, voice-tasking, or pick-by-voice, automated sortation systems, automation software.

• Warehouse Management System (WMS): A warehouse management system (WMS) is a comprehensive software solution typically used to manage logistics, supply chain, and warehouse operations. It can provide visibility into inventory movement, stock levels, and item location while also facilitating communication between automation solutions.
• Inventory Management Software: Inventory management software primarily tracks inventory throughout an organization’s entire supply chain, providing an overview of inventory and stock levels and sometimes stock availability from suppliers. This type of software is commonly used along with a WMS.
• Order Fulfillment Software: Similar to inventory management software, order fulfillment software handles inventory management activities that are focused on order fulfillment – receiving orders, creating item picking lists, guiding order picking and packing, shipping, and tracking.

Processes Suitable for Automation

Timing of automating your operations, five questions to determine if it’s time to automate your warehouse operations:.

• Are your existing tasks, procedures, and workflows manual and labor-intensive?
• Does your workforce increase or decrease based on demand during peak seasons?
• Is inventory data inaccurate or incomplete?
• Are customer orders delayed due to a long or complex order fulfillment process?
• Are inventory levels imbalanced from supply chain disruptions?

Considerations Before Implementing Automation

Warehouse automation challenges, benefits from automating your warehouse.

• Increased throughput and order fulfillment
• Improved order fulfillment accuracy
• Optimized and better utilized warehouse space
• Improved supply chain resilience
• Enhanced data analysis and information accuracy
• Reduced workplace injuries and improved employee safety
• Minimized labor-intensive, time consuming, and repetitive tasks
• Enhanced customer satisfaction
• Higher profitability
• Reduced overhead expenses
• Stronger inventory security and visibility
• Increased sustainability practices and less resources use

Warehouse Automation Best Practices

• Choose a Scalable Automation Solution: With consumer and market demand constantly fluctuating, it’s best to choose a solution that can grow with your business or scale back to accommodate lower demand without impacting existing labor.
• Ensure WMS Integration: The automation solution you choose should be able to integrate with a WMS system to ensure interconnectivity and communication with all warehouse operations, providing accurate inventory and performance data.
• Keep Warehouse Design and Space in Mind: It’s important that the automation solution you choose can accommodate your existing warehouse space (brownfield) or fit the needs of a new fulfillment center or warehouse (greenfield).

Prerequisites for Automating Your Warehouse

• Create a Team of Stakeholders: Who will be involved in the planning and decision-making process? It’s important to put together an expert team involved with your warehouse and logistics operations who have knowledge of current performance, needs, and challenges. This team will also need to work with your automation supplier and/or integrator.
• Establish Your Goals: Before implementing automation, you’ll need to establish your goals and know what you’re setting out to accomplish with automation. It’s important to establish operational objectives, competitive strategy, and long-term goals with room for adjustments
• Minimize labor dependence
• Reduce overhead costs
• Attract investors
• Boost efficiency
• Meet fluctuating demand
• Collect and Analyze Data: To implement the right solution for your operation, you’ll need to understand how inventory and goods are moving throughout your warehouse and supply chain. This will include a baseline of products ordered, inventory path, and knowledge of how automation is expected to change inventory flow.
• Assess the Physical Space: You’ll need to assess the physical space you’ll be automating before introducing new equipment. Consider the building floor space, obstructions, existing and new equipment, seismic zones, and any temperature requirements.
• Consider the Future: Will the automation solution you choose for your current needs benefit future ones? Consider if your solution is scalable to accommodate your growing operations or changes in workflow.

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Inside the Amazon Warehouse Where Humans and Machines Become One

They call me the Master of Robots—or at least they should. I grab a flat package, hold its barcode under a red laser dot, and place it on a small orange robot. I hit a button to my left and off zips the robot to do my bidding, bound for one of more than 300 rectangular holes in the floor corresponding to zip codes. When it gets there, the bot engages its own little conveyor belt, sliding the package off its back and down a chute to the floor below, where it can be loaded onto a truck for delivery.

This is not an experimental system in a robotics lab. These are real packages going to real people with the help of real robots in Amazon’s sorting facility of tomorrow, not far from the Denver airport. With any luck, my robot friend and I just successfully shipped a parcel to someone in Colorado. If not—well, blame the technology, not the user.

Seen from above, the scale of the system is dizzying. My robot, a stubby mobile slab known as a drive (or more formally and mythically, Pegasus), is just one of hundreds of its kind swarming a 125,000-square-foot “field” pockmarked with chutes. It’s a symphony of electric whirring, with robots pausing for one another at intersections and delivering their packages to the slides. After each “mission,” they form a neat queue at stations along the periphery, waiting for humans to scan a new package, load the robots once again, and dispatch them on another mission.

You don’t have to look far to see what a massive shake-up this is for the unseen logistics behind your Amazon deliveries. On the other side of the building are four humans doing things the old way, standing at the base of a slide flowing with packages. Frenetically they pick up the parcels, eyeball the label on each, and walk them over to the appropriate chutes. At the bottom of the chutes, yet more humans grab the packages and stack them on pallets for delivery. It’s all extremely labor-intensive and, in a word, chaotic.

Amazon needs this robotic system to supercharge its order fulfillment process and make same-day delivery a widespread reality. But the implications strike at the very nature of modern labor: Humans and robots are fusing into a cohesive workforce, one that promises to harness the unique skills of both parties. With that comes a familiar anxiety—an existential conundrum, even—that as robots grow ever more advanced, they’re bound to push more and more people out of work. But in reality, it’s not nearly as simple as all that.

If only the Luddites could see us fulfilling online orders now.

This Colorado warehouse is, in a way, a monument to robots. It’s not one of the Amazon fulfillment centers you’ve probably heard of by now, in which humans grab all the items in your order and pack them into a box. This is a sorting facility, which receives all those boxes and puts them on trucks to your neighborhood. The distinction is important: These squat, wheeled drives aren’t tasked with finely manipulating your shampoos and books and T-shirts. They’re mules.

By Tess Owen

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By Kim Zetter

Very, very finely tuned mules. A system in the cloud, sort of like air traffic control, coordinates the route of every robot across the floor, with an eye to potential interference from other drives on other routes. That coordination system also decides when a robot should peel off to the side and dock in a charger, and when it should return to work. Sometimes the route selection can get even more complicated, because particularly populous zip codes have more than one chute, so the system needs to factor in traffic patterns in deciding which portal a robot should visit.

“It's basically a very large sudoku puzzle,” says Ryan Clarke, senior manager of Special Amazon Robotics Technology Applications. “You want every column and every row to have an equal amount of drops. How do we make sure that every row and every column looks exactly equal to each other?” The end goal is to minimize congestion through an even distribution of traffic across the field. So on top of tweaking the robots’ routes, the system can actually switch the chute assignments around to match demand, so that neither the robots nor the human sorters they work with hit any bottlenecks.

To map out all this madness, Amazon runs simulations. Those in turn inform how the drives themselves should be performing. What’s the optimal speed? What’s the optimal acceleration and deceleration, given you want the deliveries to be as efficient as possible while keeping the robots from smashing into one another? After all, a bump might toss a package to the ground, which other robots would spot with their vision sensors and route around, adding yet another layer of complexity to the field. (The robots have sensors on either end of their conveyor belt, by the way, so if a package starts to slip off the side, the belt automatically engages to pull the package back on.)

Amazon runs complex simulations to coordinate the robots on the field.

The temptation might be to get these machines moving as quick as possible. “But it would be like having a Ferrari in downtown San Francisco—all you're doing is stop and go,” says Clarke. “We looked at tuning it to many different parameters and found that more speed and more acceleration actually had a reverse effect. They were just bumping into each other and causing more pileups.”

Ready for more complexity? Amazon had to tweak the built space itself to keep the machines happy. Humans doing things the old way on the other side of the building, for instance, enjoy basking in the photons that pour through skylights. Above the robots’ field, though, the skylights are covered, because the glare might throw off the machines’ sensors. To navigate, they’re using a camera on their bellies that reads QR codes on the ground. Even the air-conditioning units hanging from the roof are modified. On the human side, they blow air straight downward, but above the robots they blow out to the side, because gusts of air could blow light packages off the machines’ conveyor belts.

Worse yet, precarious packages like liquids could send the system into chaos. So although the system is automated, humans still monitor the robots on flatscreens below the field, where the packages come down the chutes, and respond to crises. “Think about if I had a package and it had a gallon of paint in it, and that gallon of paint was damaged and it leaked down one of these chutes,” says Steve McDonnell, general manager of the sorting center. “Within minutes I'm able to shut that chute off, redirect drives to another chute, and I'm done.”

The key here is flexibility—not a word that first comes to mind when you think of robots. Flexibility in the robots’ pathways, in their destinations, in the number of robots on the field at once. You might, for example, think the more machines out there, the better. Amazon could deploy up to 800 drives simultaneously, but that could jam up the floor like traffic in a city. Instead, they’re typically operating 400 or 500, with others parked off to the side and waiting to be circulated in.

Beyond coordinating the robots themselves, there’s the question of how to make them good coworkers for the human employees. The humans’ job is to place packages in 6-foot-tall boxes below the field, taking care not to toss in heavy packages first. To make that work manageable, the robots have to distribute packages between the multiple chutes for a particular zip code, so a given chute doesn’t overflow. At the same time, the system considers how to best group packages downstairs by their departure time, so workers don’t have to run around hunting for them.

“The interaction between the associate and the drives is almost like a 3D chess set,” says McDonnell, “because you can optimize the drive field, but then you can make the associate's job harder below the field.”

Across the field from the human workers distributing packages to the drives, a prototype robotic arm, named Robin, sits at the end of a conveyor belt. Its “hand” is a vacuum manipulator, designed to snag boxes and flat packages.

This robotic arm is a test of what it might look like to further automate the work of shuffling packages around. The idea is that the conveyor will deliver packages to the arm, which would then load the drives. “We're going to feed it a little bit differently than we do with humans,” says Rob Whitten, senior technical program manager. “We're not going to just give it a pile coming down a chute—we're going to kind of toss it softballs. We're going to give it a little more structure so it can handle it.” For parcels it can't manipulate, like if they're too heavy or weirdly shaped, humans would step in to help.

As I walk down the line of human robot-loaders, I come across a worker who has set aside a broken box, which has spilled out bottles and other entrails. That uniquely capable human could do two things here: use his problem-solving skills to say, "Something is wrong, I need to set these aside," and then manipulate those objects with exceedingly fine motor skills.

This robot arm has neither problem-solving prowess nor fine motor skills. Imagine if clear laundry liquid had broken inside a package and soaked the bottom of the box. A human might smell the detergent or feel its stickiness before they see it. A robot arm relying on sight alone would miss the problem, loading the package on a drive robot that then snail-slimes the floor of the field.

Even if they had some semblance of judgment, robots are still awful at manipulating complex objects like bottles. That’s why Amazon is keeping it simple here, with a suction arm meant to stick to flat surfaces, as opposed to an analog of the human hand . For quite some time, humans will need to (nearly) literally hold these robots’ hands.

The bottom line is this: We humans have to adapt to the machines as much as the machines have to adapt to us. Our careers depend on it.

Amazon runs simulations to figure out how to keep their human workers comfortable when loading robots with packages. This includes their range of movement from an ergonomics standpoint and their safety. Or such questions as how best for a human to grab a parcel, scan it, place it, and reach over to hit the button that sends the robot on its way. “There's an art to making it feel seamless between what the robot is doing and what the humans are doing,” says Brad Porter, VP of robotics at Amazon.

It’s the kind of dynamic environment that’s perfect for the development of Amazon’s next iteration of its system. The company is working on a new modular robot called Xanthus with different attachments, say to hold containers instead of using a conveyor belt. This machine will in a sense bridge the divide between fulfillment centers, where humans are loading products into boxes by hand, and sorting centers, where they’re mostly working with those assembled boxes.

Amazon's new modular Xanthus robot can be outfitted with attachments that allow it to carry different kinds of cargo.

“You can see how combined with maybe the addition of a sensor platform, you could have an autonomous drive that's driving totes around,” says Porter. But you can also take that same thin sled and replace the tote-carrying unit with a conveyor top and deploy it in the sorting center.

Herein lies Amazon’s huge advantage: It’s got the funds and the talent to develop robots in-house, tailoring each to solve problems specific to Amazon. Other warehouses are starting to go robotic, but they’re working with other companies’ machines. For instance, Boston Dynamics—maker of the hypnotically impressive SpotMini and Atlas —will soon offer a box-lifting robot called Handle . But it’s a generalist machine, not developed exclusively for one client.

Amazon, on the other hand, can iterate on a robot until it's perfectly adapted for a specific task. “They're building it for themselves, and they're building it for their environment and circumstances,” says John Santagate, research director of service robotics at IDC, which does market research. “It's hard to build any one product that suits all of it.”

And every worker they hire into a machine-facing role is doing something no other human has ever done before—lower-level workers in this facility have been promoted to help oversee the massive system whirring around them, as well as the humans intimately integrated with it. “The fully automated or highly automated fulfillment center isn't a North Star we're trying to hit,” says Porter. “Do we see additional levels of automation, at higher and higher levels? Yeah, I think that will increase as the capabilities of our systems increase.”

Here’s the big question, though. Is this kind of automation bound to replace human jobs entirely, or replace parts of those jobs? “Most of the research seems to suggest that the direction that automation is moving in is the displacement of skills, not jobs,” says R. David Edelman, formerly President Obama's special assistant on the digital economy, and now the director of MIT’s Project on Technology, Economy, and National Security. “That suggests those individuals can, by Amazon, be reskilled or leverage other skills they already have in the same job.”

These days, industries that are short human labor need automation to survive. Consumers still want fresh produce, but California’s farms are facing a labor shortage of 20 percent and are increasingly turning to agricultural robotics . Amazon’s business is booming, yet America is enjoying historically low unemployment, so laborers have lots of options for work. “The demand on that company is increasing, but the availability of resources to fill that demand isn't necessarily increasing,” says Santagate. “In fact it's probably contracting.” Robots are filling the void.

Here in this sorting center of tomorrow, I walk along the edge of the field and hear the morning break for humans, called out on loudspeakers. The drive robots continue to shuffle around for a few minutes, with their incessant electric white noise, until suddenly the place falls almost silent. Having delivered their packages to chutes, the robots have run out of work. They park off to the side of the field, some of them in charging stations. Only when the loudspeakers call the end of break do the machines start up again, ready for their humans to feed them more packages.

If only the Luddites could see our codependency now.

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Warehouse Automation: Types, Benefits, & More

What is warehouse automation.

Warehouse automation integrates advanced technologies and systems designed to optimize and streamline operations within logistic centers. This broad field includes various automated equipment and software solutions, such as automated storage and retrieval systems (ASRS), autonomous mobile robots (AMR), and robotic arms that manage the flow of goods while minimizing reliance on manual labor.

As businesses globally face increasing pressure to expedite delivery times, reduce costs, and improve accuracy, the relevance of warehouse automation has surged. It is now a critical component in modern logistics, enabling companies to meet rising consumer expectations and thrive in competitive markets. This introduction sets the stage for exploring the types, benefits, and practical insights on effectively implementing warehouse automation solutions.

The Evolution of Automation Technologies in Warehousing

Automation technologies in warehousing have dramatically transformed from basic mechanical tools to advanced robotic systems. This evolution reflects a trajectory towards increased efficiency, adaptability, and precision in logistics operations. Here, we explore three major phases of automation evolution:

Basic Mechanization

At the outset, warehouse automation was synonymous with basic mechanization, employing tools such as pallets, forklifts, and conveyor systems. Conveyor systems, for example, were revolutionary in the early days, simplifying the movement of goods and reducing manual labor. While once hailed as a groundbreaking automation solution, these systems, reliant on fixed mechanization, falter in delivering the flexibility essential for meeting modern demands. Consequently, their malfunctions can trigger significant operational disruptions. Although conveyors remain commonplace in warehouses, a growing number of businesses are actively working to reduce their dependence on them.

Traditional Automated Storage and Retrieval Systems (ASRS)

The next leap in warehouse automation came with traditional ASRS, including mini loads and shuttle systems. For several decades, these technologies have significantly improved warehouse operations. By utilizing cranes and automated vehicles on fixed tracks, along with conveyance systems, these systems enable the transport of goods between storage racks and picking stations without the need for human intervention. This integration enhances the speed, storage density, and accuracy of storing and retrieving items, optimizing overall efficiency in warehouse management.

However, despite their improvements in throughput, traditional ASRS faced limitations. They are often rigid in their infrastructure, making expansion costly and complex. Moreover, with numerous points of failure and a heavy reliance on conveyance, these systems gradually became less viable, especially as warehouses sought more scalable and flexible solutions.

Robotic Goods-to-Person Systems

The future of warehouse automation is embodied in robotic goods-to-person systems, which offer the flexibility lacking in traditional ASRS. These systems are a subset of Automated Storage and Retrieval Systems (ASRS). However, unlike their predecessors, robotic goods-to-person systems use individual robots operating independently instead of fixed tracks and lifts, thereby eliminating the single point of failure problem. These systems are designed for quick installation and seamless scalability as they operate storage and throughput independently. This results in reduced incremental costs and complexities associated with expansion. They leverage advanced algorithms to provide warehouse operations with unparalleled efficiency, responsiveness, and resiliency, aligning with modern demands for speed and flexibility.

Types of Robotic Goods-to-Person Systems

Floor robots.

Autonomous Guided Vehicles (AGV): AGVs transport goods across a warehouse by following marked paths or wires on the floor, using navigation aids such as magnet strips, wires, or cables. They can move pallets, storage shelves, or individual items efficiently.

Autonomous Mobile Robots (AMR): AMRs operate similarly to AGVs but navigate the environment without pre-defined paths, using sensors and cameras.

Pros & Cons: Both AGVs and AMRs offer quick implementation timelines and significantly improve warehouse operational throughput and accuracy. However, they generally provide lower throughput and storage density compared to ASRS. While AGVs are restricted to fixed paths, AMRs offer more flexibility by navigating freely, making them more adaptable to dynamic warehouse environments.

Robotic ASRS

Cube Storage: These systems organize goods into bins stacked within a cube-shaped storage structure. Robots operate on top of the cube and manage bin shuffling, sorting, and retrieval, delivering them to picking stations.

Mobile ASRS: Mobile ASRS systems utilize autonomous mobile robots that travel between storage racks and picking stations to store and retrieve goods. This category includes Exotec’s S kypod system , which is designed for agility and scalability.

Pros & Cons: Robotic ASRS solutions excel in flexibility, enabling rapid throughput increases by adding more robots or expanding storage racks with minimal disruption to ongoing operations. Despite being relatively new, these systems are becoming the preferred choice for warehouses needing agility and scalability to meet unpredictable future demands.

Implementing End-to-End Warehouse Automation

Warehouse automation extends beyond ASRS and goods-to-person systems to include a comprehensive suite of technologies that can automate the entire process from inbound to outbound. Here we detail some key forms of warehouse automation that complement these systems to streamline processes and increase efficiency:

Pick-to-Light and Put-to-Light Systems

Pick-to-light and put-to-light systems guide warehouse personnel during the picking and placing processes using visual cues. These systems utilize LED displays at storage locations to indicate the number of items to be picked or placed, significantly reducing errors and enhancing picking accuracy and speed. These systems ensure that workers interact with the inventory in the most efficient manner possible, further optimizing fulfillment times and reducing labor costs.

Weight Scales for Accuracy

Accuracy in warehouse operations is paramount, and weight scales play a crucial role in ensuring this accuracy. Integrated within the workflow, these scales verify the weight of items during both the inbound and outbound processes to detect discrepancies and prevent shipping errors. This verification step is helps maintaining quality control, reducing returns due to incorrect shipments, and enhancing customer satisfaction.

Document Machines

Automation extends to the realm of documentation through machines such as package labeling machines and document inserters. These devices automate critical aspects of packaging by generating and applying labels and inserting necessary documents, such as packing lists and receipts, directly into packages. Automating these tasks reduces manual errors, speeds up the packaging process, and ensures that all outgoing shipments are accompanied by the correct documents, thereby complying with shipping regulations and customer expectations.

Automated Packing Systems

Automated packing systems automatically select the appropriate packaging for each item based on its dimensions and fragility, fill the package with the right amount of dunnage, and seal it for shipment. By optimizing the packing process, these systems not only save material and reduce waste but also ensure that products are securely packaged for transit, minimizing damage and returns.

Robotic Picking Arms

Robotic picking arms enhance warehouse automation by boosting both speed and reliability in the picking process. Equipped with advanced sensors and technology, these arms identify, pick, and place items, making them ideal for environments requiring high volume and variety. When integrated with ASRS, robotic picking arms increase throughput, reduce human error, and lessen physical strain on workers, leading to a safer and more productive workplace.

Robotic Palletizers & Depalletizers

Palletizers are used in warehouses to automatically stack items onto pallets. They receive items on a conveyor belt, orient them as needed, form layers on pallets according to a preset pattern, and secure the load for transport. De-palletizers, on the other hand, do the reverse process, removing items from pallets for further processing or distribution. They typically use suction cups, grippers, or other mechanisms to lift items off the pallets, place them onto a conveyor, and transport them to the next stage of production or packaging.

Together, these automation technologies create an integrated and comprehensive system that significantly boosts the efficiency and accuracy of warehouse operations. This ensures a seamless flow of goods from the moment they enter the warehouse until they are shipped out, optimizing every stage of the process.

Here is a view of the inbound stations at Lane Automotive, each showcasing 24 buffer put-to-light cells.

Case Study Highlight: Lane Automotive

At Lane Automotive, the implementation of Exotec’s Skypod System as the centerpiece of their end-to-end warehouse automation exemplifies the significant benefits of mobile ASRS. This integration, combined with a range of inbound and outbound solutions, has revolutionized their operations. Key features include multiple inbound stations, each with 24 buffer put-to-light cells, an empty carton delivery system directing formed shipping cartons to designated picking stations, multiple inline weight scales for enhanced order accuracy and validation, inline packing list insertion, automated packing systems, and inline label applicators.

These advancements have resulted in a more than 600% increase in throughput and a reduction in order processing time from 109 minutes to less than 15 minutes, highlighting the dramatic efficiency gains achievable with advanced automation technologies. Additionally, the system’s scalability enabled Lane Automotive to double its volume handling capacity with minimal additional investment, demonstrating the necessary adaptability for modern business growth.

For an in-depth look at how Lane Automotive transformed its fulfillment operations with Exotec’s solutions, read the full case study here . 

Three Key Benefits of Warehouse Automation

Warehouse automation brings several key advantages to logistics operations:

• Enhanced Efficiency and Productivity: Automation streamlines processes, reducing the time it takes to execute tasks like picking, packing, and shipping. This efficiency boost speeds up operations and increases the overall output without additional labor.
• Improved Accuracy and Reduced Operational Costs:  Automated systems enhance accuracy and efficiency by eliminating guesswork for operators and systematically verifying their operations. This ensures precise inventory management and accurate order fulfillment on the first attempt. Such precision minimizes expensive errors and returns while also reducing labor costs through the automation of repetitive tasks.
• Reduced Dependence on Manual Labor: As business needs evolve, warehouse automation systems provide scalability and adaptability without significantly increasing the need for additional personnel. Whether expanding storage capacity or integrating new technologies, these systems are designed to grow with your business, ensuring long-term sustainability and flexibility in operations.

These benefits combine to make warehouse automation a powerful tool for companies looking to optimize their warehousing and distribution strategies, ultimately improving service quality and customer satisfaction.

How to Automate Your Business or Warehouse

Implementing warehouse automation involves careful planning and strategic decisions. Here’s a step-by-step guide to help you automate your warehouse effectively:

• Assess Your Needs: Evaluate your current operations to identify areas where automation can benefit most. Consider factors like volume, throughput requirements, and specific challenges in handling materials.
• Research Technologies: Discover the latest in warehouse automation by attending industry trade shows. These events let you see AS/RS, conveyor systems, robotic systems, and integrated software in action. Gain insights from expert-led conferences and connect directly with solution providers. Visit our upcoming events page to learn more.
• Select the Right Technologies: Prioritize flexibility when choosing warehouse automation technologies. Opt for solutions that seamlessly grow with your business and adapt to changing operational needs. This focus ensures that the technologies you implement today will continue to serve your evolving requirements, enhancing both scalability and compatibility with your existing infrastructure.
• Change Management Plan: Focus on a change management plan that energizes stakeholders about adopting new automation technologies. Ensure open communication across departments and provide targeted training to facilitate smooth integration and foster support for the transition.
• Provide Accurate Data: Ensure your solution provider receives precise and comprehensive data concerning your current operations, such as your business’ order volume throughout the year and product dimensions, to tailor automation solutions that best fit your specific operational needs and maximize efficiency.
• Roll Out: Work closely with your solution provider to set appropriate milestones throughout the implementation process. This structured approach ensures that each phase of automation is carefully monitored and adjustments are made as needed, facilitating a smooth transition and successful integration.
• Continuous Improvement: After implementation, continually assess the performance of your automated systems and work with your provider to make improvements to optimize efficiency and productivity.

By following these steps and carefully selecting the right technologies, you can effectively automate your warehouse and reap the benefits of increased efficiency, reduced costs, and improved accuracy.

Challenges Faced & Answered by Warehouse Automation

Adopting warehouse automation solutions comes with its set of challenges:

• High Initial Investment: The upfront cost of implementing automated systems can be significant. However, the long-term savings in manual labor costs and increased efficiencies such as optimized space utilization, reduced inventory holding costs, and lower picking error rates resulting in fewer returns and increased customer loyalty often justify the investment.
• Integration with Existing Systems: Integrating new automation technologies with warehouse management systems can be complex. Prioritize automation solutions that offer flexible software that has proven to be compatible with a wide range of warehouse management systems, ensuring a smoother transition.
• Workforce Adaptation: Open communication across various departments, training programs, and the gradual integration of automated systems can help ease the transition, setting your automation projects up for success.  
• Maintenance Requirements: Automated systems require regular maintenance to function optimally. Choosing reliable automation partners like Exotec, who ensure ongoing support and maintenance without hidden fees. This ensures peace of mind with the smooth operation of your automation, keeping your solutions from turning into problems. 
• Data Security and Privacy: As automation often involves handling significant amounts of data, securing this information becomes crucial. Prioritize automation solutions featuring robust cybersecurity measures that will safeguard against potential data breaches.

By addressing these challenges with strategic planning and the right technology partners, businesses can effectively leverage warehouse automation to enhance operational efficiency and competitiveness.

Warehouse Automation Trends

As warehouse automation becomes increasingly essential in the logistics industry, several key trends are shaping its future:

• Advanced Robotics: The shift towards robotics, exemplified by Exotec’s Skypod® System , represents a significant trend. Unlike traditional ASRS that rely on heavy machinery, these agile robots offer rapid installation, adaptability for an unpredictable future, and high reliability without multiple points of failure.
• Scalable Solutions: Flexibility and adaptability in warehouse operations are crucial as market demands fluctuate. More and more businesses are prioritizing scalable systems that allow them to adjust their infrastructure efficiently, enhancing growth and operational agility without excessive downtime.
• Digital Twin Technology: This technology is crucial in planning and optimizing warehouse operations by creating virtual replicas of physical systems. It allows for detailed scenario testing and operational adjustments before implementation, ensuring smoother integration and system efficiency.
• Sustainable Practices: There is a growing emphasis on minimizing environmental impacts within warehouse operations. Systems that use energy-efficient technologies, like the lightweight, battery-powered robots in the Skypod System, are becoming more prevalent, aligning operational efficiency with sustainability goals.
• Enhanced Connectivity with 5G: The integration of 5G technology is poised to revolutionize warehouse automation by enabling faster data processing and enhancing real-time decision-making capabilities.
• Robust Security Measures: As technological advancements continue, ensuring the security of automated systems against physical and cyber threats has become paramount. Implementing comprehensive security measures is essential for protecting assets and maintaining continuous operations.

For a deeper exploration of these trends and how they can transform your warehousing operations, read the full article, “ Top Warehouse Trends for 2024: Future of Automation .”

Automate Your Warehouse with Exotec

Exotec’s solutions, including the Skypod system, are specifically designed to meet the varied needs of modern warehouses. The Skypod System allows for rapid and precise access to goods, boasting a capability where any items in the system can be retrieved within two minutes. This efficiency is paramount for businesses aiming for high throughput, as the system also supports a 5x increase in operational speed compared to traditional manual operations. Additionally, the Skypod system offers remarkable flexibility in scaling both throughput and storage independently, meeting system expansion requirements without unnecessary capital expenditure. This ensures that businesses can adapt their warehouse operations fluidly as market demands or their business model evolves, all while ensuring minimal disruption to ongoing operations.

We recommend taking a Virtual Warehouse Tour of Exotec’s advanced automation solutions. This interactive experience provides valuable insights into optimizing your warehouse operations effectively.

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Improving warehouse operations—digitally

Warehouse operations are increasing in complexity with time. The growth of e-commerce has led to a proliferation of SKUs, and there’s an ever-growing need to delight customers by offering super-fast fulfillment. Technology is a factor as well: as new automation systems come onto the market, operations leaders must face the challenge of keeping pace and understanding which technologies apply and what kind of impact they can generate.

Worldwide, companies spend an estimated $350 billion a year on warehousing, and that number grows each year as pick sizes shrink and costs balloon, raising pressure not just on margins but also on service levels.

The need to improve both sides of the equation may be obvious, but the question is how. Trial-and-error is not an option: companies cannot simply shut down a warehouse so they can tinker with new layouts and workflows to see what works best.

But the better news is that they don’t have to. A few companies are already able to design and visualize their warehouse operations virtually via “digital twin” simulations. The simulations allow companies to create virtual models of their existing facilities, and then test different scenarios—no shutdowns required.

This digital warehouse-design approach lets companies experiment with different floor plans, workflows, and other variables to assess the overall impact virtually. Operations leaders can see the impact of changes in a wide range of factors, including the SKU mix, order and shipment profiles, seasonal demand spikes, productivity initiatives, automation options, and a host of other issues that impact warehouse performance. This level of detail allows warehouse designs to be optimized in advance, before anyone starts moving physical assets.

The process typically takes six to ten weeks. The revamped warehouse designs that result can help companies improve efficiency by 20 to 25 percent, before spending the money to test or pilot the changes (exhibit).

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The power of digital simulations.

Digital warehouse design has a wide range of applications, from productivity initiatives at existing facilities to mergers, warehouse consolidations, and new warehouse construction. Across all applications, however, the benefits are reasonably consistent: sizable savings in operating expenses from productivity improvement, as well as in capital expenses from optimizing the deployment of material-handling equipment, storage assets, and targeted, right-sized automation systems.

The approach removes bottlenecks to improve efficiency and effectiveness, and enables optimal slotting and product flows to meet service requirements at the lowest possible cost. Most important, digital warehouse design identifies the full potential of a given facility, rather than forcing companies to settle for incremental improvements to the as-is layout.

Critically, the process also enables companies to gauge the potential impact of mechanization and automation options across the entire spectrum of vendors and products on the market. These technologies can be powerful tools to reduce space and increase efficiency. But in some cases, incorrect or inappropriate automation can actually create more problems than it solves. Digital modeling lets companies see what is possible from a range of technologies and applications, before they make any investment decisions.

Transcending traditional improvements

Of course, most companies know they need to improve their warehouse operations. But they struggle to identify and make the needed upgrades, due to limited data and internal expertise. Quite simply, many companies lack the full set of capabilities needed to assess various warehouse improvement options and create a business case that incorporates capex investments and running costs.

Some rely on third-party logistics providers, but even those vendors often lack the breadth of expertise to see what is truly possible with alternative warehouse designs and operations. A related problem is that most traditional methods to design or revamp warehouses use computer-aided design software (CAD)—which is resource-heavy and time-consuming, and doesn’t allow companies to calculate the impact of new changes or anticipate second-order effects. Digital warehouse design, by contrast, offers a low-risk way to visualize and optimize layouts, allowing companies to rapidly identify real, feasible solutions that deliver quick impact.

For example, a North American manufacturer decided to consolidate several regional manufacturing and warehouse locations into a single campus, with separate buildings dedicated to manufacturing and warehousing. However, it faced several challenges, including capital constraints, insufficient warehouse space, and a need to move fast.

Instead of relying on traditional tools, the company used a digital warehouse-design approach to simulate various options across warehousing, kitting (assembly of related items into a single “kit” for shipment), and value-added operations. The digital tools allowed the company to develop detailed OPEX and CAPEX estimates for both manual and automated solutions, making it far easier to evaluate various business cases. In all, the company reduced planned capex by approximately 10 percent and operating expenses by more than 30 percent.

Digital warehouse design can also help companies rethink existing facilities. For example, another company deployed digital warehouse-design and simulation tools to optimize and revamp its operations in a warehouse currently in operation. It built models to test various layouts, material-handling-flow scenarios, picking methods, and targeted automation solutions.

Starting from an optimized slotting design, the digital twin analyzed historical orders to estimate the exact labor and equipment requirements by day of the week and by hour of the day. With accurate labor-staffing models, the company was able to choose the most optimal, modular design to implement during the transition. In addition, the company could define precise, engineered standards for each operation of the warehouse, and it could monitor daily labor and equipment performance once the new system was in place. This enabled the company to reduce annual operating expenses by 18 percent.

Similarly, one business had a central regional warehouse in Eastern Europe, with annual costs of several million dollars. By constructing a digital twin, the company analyzed the potential improvements from a proposed layout change (specifically, a picking zone that enabled one-step picking). Looking at both high-season and low-season volume, the company determined that it could reduce input costs by more than 25 percent.

Supply chain risk management is back

Foundational capabilities.

As with most technology, digital warehouse design is not a turnkey solution. To capture its full potential, companies must understand their strategy not only for today and tomorrow, but also well into the future—in terms of product portfolio, customer-order profiles, and other factors. Leadership teams must assess the implications of design changes on the supply-chain network as well. And success requires new capabilities in warehouse design—typically engineers who understand the range of variations and permutations for a space. Most organizations do not yet have internal people ready for these roles, and thus need to source that expertise externally.

As a practical matter, the simulation process must involve operations and warehouse managers—those with the deep day-to-day knowledge and real-world insights that can only come from direct experience. Because these experts will be tasked with implementing any changes to the warehouse after the simulation ends, their buy-in will be essential. The more they contribute during the early stages of the process, the more willing they are likely to be to forego old habits and work in new ways.

Last, companies need to plan for repeated changes over time. Optimizing warehouse performance is a process without a finish line—it must happen again and again, as market forces, technology, and consumer preferences continue to evolve. In fact, digital warehouse-simulation tools could become a new way of setting performance expectations, with the tools embedded as part of the day-to-day management of each distribution center. Estimating daily performance targets based on daily volume, mix, and staffing can help warehouse managers manage the shift’s performance more precisely than any other traditional, static approach to setting goals.

Companies face a growing need to improve their warehouse operations. Digital warehouse design is one clear means to help them do so. The process may be virtual, but the results generate a real impact on performance, providing an edge in an ever-more-complex warehousing landscape.

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Felipe Bustamante is a consultant in McKinsey’s Miami office, Ashutosh Dekhne is a partner in the Dallas office, Jörn Herrmann is a senior expert in the Zürich office, and Vedang Singh is a consultant in the New Jersey office.

The authors wish to thank Aditi Brodie for her contribution to this article.

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Evaluating Introduction of Warehouse Automation Systems

Symbotic is a warehouse automation solutions provider. Its systems are based on mobile robots that can travel freely throughout a dense storage structure, accessing products in all locations and handling them at a very high throughput rate. The main advantages of the Symbotic System are its ability to operate in three dimensions, and their sequencing and palletizing algorithms that build stable, store-friendly pallets at maximum throughput.

The company needed a tool to help their customers learn the impact of warehouse reorganization and compare capital investments against expected operational savings before the actual introduction of automation systems. This tool had to be easily adjusted to the case of each specific client.

Symbotic specialists decided to use AnyLogic simulation software for this purpose because it could precisely estimate costs and visualize processes inside warehouses in 3D, as well as create models that could be easily reconfigured for multiple projects.

The models that Symbotic engineers created for the company’s clients simulated the environment and operations in their warehouses with a high level of detail. More specifically, this included:

• Scheduling and assignment of dock doors, product flow between the dock doors and several different warehouse locations on both inbound and outbound.
• Tracking and combining order-specific product flows from different streams on the outbound.
• Operations of labor and resources like loaders, unloaders, forklift trucks, de-palletizing and palletizing cells, all simulated as agents.

Warehouse Model 3D Animation

Each agent type had its own properties, like speed, reliability, operation times for equipment, dimensions, cases per layer, and layers per pallet for each SKU. The input data was taken from real life information.

It was especially important for the modelers to simulate various interactions between the automation system and human operators. This included receiving incoming deliveries, replenishing stock, both automated and non-automated parts of the warehouse fulfilling customer orders in an optimized sequence, and combining them at the dock-doors in the exact manner it would happen in the projected system. Models also took into account system reaction in case of equipment breakdowns, shift schedules and lunch-breaks for the human operators. The models featured warehouse 3D animation and graphical display of key metrics to provide strong presentation instruments for salespeople and allow the clients to see their future reorganized warehouses in action.

The models were tested on the historic order data from each client, usually for a six month period. To compare warehouse operations, with and without the automation solutions introduced, Symbotic engineers gathered the following statistics in the model:

• Throughput capacity (cases per hour handled)
• Number of human operators required and associated costs
• Number of warehouse resources required (e.g. dock doors) and their utilization
• Time needed to fulfill daily outbound shipment orders, especially during the peak periods

These outputs were used by the clients to evaluate warehouse design alternatives and justify capital investments.

AnyLogic allowed Symbotic to design their simulation models in a way that made it possible to easily change warehouse layout, operating procedures, SKU properties, etc., so that model elements could be reused in multiple projects with relatively small effort. Also, 3D animation allowed the company to utilize these simulations as a powerful selling tool.

Project presentation by Dr. Larry M. Sweet, CTO at Symbotic LLC:

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• Open access
• Published: 27 June 2020

Case study: evaluation of the automation of material handling with mobile robots

• Adriana F. Melo 1 &
• Lindsay M. Corneal   ORCID: orcid.org/0000-0002-9102-2859 1  

International Journal of Quality Innovation volume  6 , Article number:  3 ( 2020 ) Cite this article

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The automation of material handling is one of the solutions that many companies are relying on to reach their goals related to productivity increment, floor space optimization, higher standards for factory’s safety, and allocation of workers to value-added activities. Therefore, the objective of this study was to evaluate the current state of the material flow of finished goods for an automotive parts supplier plant and the technology available on the market to verify if it was worthwhile to invest in material handling automation. The analysis included the use of discrete event simulation to evaluate the different layout approaches combined with the mobile robots’ performance. It was proven that the tandem layout was the most beneficial approach to the analyzed plant’s reality with a minimal of three robots. Improvements to the material flow and automation of the labeling process were also proposed based on the study.

Introduction

Automated guided vehicles (AGVs) first started to be used in the 1950s for manufacturing. This technology began the trend of automation of material transportation. They have proved to be reliable and efficient technological equipment for more than 50 years. However, the need of fixed routes and the minimal on-board intelligence were restricting the use of AGVs to applications that required little variability on the pickup and drop off points of materials, as well as no interruption to its path. Changes to the pathways were simply too expensive and disruptive to be cost-effective as they are typically installed in the floor.

In response to the AGV’s drawbacks, a more sophisticated solution to material handling was recently introduced to the market, the autonomous mobile robots (AMRs). These robots have on-board intelligence and real-time adaptive capabilities, which support the increasing market demand for flexibility and for agility to comply with modification to products or processes [ 1 ].

In contrast with fixed route required by the AGVs, AMRs navigate via maps that its software constructs on-site or via pre-loaded facility drawings. The AMR uses data from cameras and built-in sensors and laser scanners as well as sophisticated software that enables it to detect its surroundings and choose the most efficient route to the target. To change its mission, the AMR only needs simple software adjustments. This functionality allows the same robot to perform a variety of different tasks at different locations, automatically adjusting to meet changing environments and production requirements. This flexibility also makes the AMRs more cost-effective as an AMR does not need wires, magnetic stripes, or other costly modifications to the building infrastructure.

Regarding the safety of these mobile systems, many of them are based on the same technology as is used for autonomous vehicles, which apply LIDAR (light detection and ranging) sensors [ 1 ]. These sensors are commonly used for pedestrian recognition. When compared with cameras, LIDARs can provide accurate range information and a larger field of view [ 2 ]. From a safety standpoint, this technology has what is recognized as a capable safety system to detect objects and people and to react appropriately [ 1 ].

It is important to emphasize, however, that new safety concerns are being raised due to this new technology. As the mobile robots are becoming more autonomous, correcting their path while in motion and the integration of new features and attachments on them, the robotics online marketing team within the Robotic Industries Association states that the existing safety standards present gaps that fail to cover some of these latest technologies to ensure the well-being of other laborers. To overcome this issue, the outlining guidelines for robot manufacturers and system integrators are being developed. The fast pace of the development of the safety standards reflects not only the urgent need for safety standards but the expectation that industrial mobile robots will continue to be implemented at a rapid rate [ 3 ].

Regarding its implementation, Gutta et al. state that facility layout design methodology is one of the primary aspects to be dealt with for an efficient and economical working of a mobile robot system. The decisions concerning material handling within the facility can have a significant impact on the effectiveness of the layout plan. Hence, for proper sequential working of a manufacturing system, it is important that the layout plan and material handling system for a facility are designed simultaneously [ 4 ].

For this study, two aspects were studied to evaluate the best way to automate the material handling at the selected plant: the plant layout and the material flow.

Facility layout design involving the implementation of mobile robots is categorized into layout design, pickup and delivery points, and flow path design. In layout design, the workspace can be seen as a set of complex polygons known as cells. The material flow system, in its turn, is characterized in terms of flow path design and direction of vehicle flow, and number and location of pickup and delivery points [ 5 ]. The flow path and location of pickup and delivery points must be determined effectively as they influence the path that a mobile robot must track, which impacts the flexibility and operational costs of a manufacturing system [ 6 ].

Typically, there are three main types of layout designs in the AMRs: single loop, tandem, and conventional layout. In a single-loop layout, AMRs travel in a unidirectional loop. When this system is used, the vehicle flow is constrained to travel only in one direction. As all the vehicles travel in the same loop, it requires less complexity in the control system. However, with this layout, the distance traveled by the vehicle might be greater when moving from one point to another, as each vehicle must travel the whole loop to visit the same point again. Another disadvantage of this kind of layout is that a vehicle breakdown can destroy the whole system [ 7 ].

The tandem layout overcomes some of the disadvantages presented by the single-loop layout. This layout design decomposes into non-overlapping loops, which can contain one or more vehicles. Previous studies showed that the tandem loop with multiple vehicle (TLMV) layout has out-performed single loop and tandem with single-vehicles layouts in terms of mean flow time and vehicle utilization. The main advantage of TLMV is it is less susceptible to vehicle breakdown [ 8 ].

The conventional layout design mainly includes unidirectional layout, bidirectional layout, and multi-lane hybrid layout. The main advantage of a bidirectional layout lies in the achievement of less vehicle travel time by reducing the travel distance due to the possibility of taking shortcuts and/or using a smaller layout space. However, the complexity of the control system is very high [ 9 ].

To compare these layout different approaches and to support the decision-makers within the company, this study made use of discrete simulation modeling. The design of the simulation model is subordinated to the method which is closely connected to the chosen software solution. The software used on this project was FlexSim 2018 Update 1, and the following steps were followed for the creation of the simulation models:

Creation of pathways and control points for vehicle movement

Add the AMR process flow template

Adapt the process flow template to fit the scenario being analyzed

Develop additional programming to imitate the variability and randomness of the real world

Verification and validation of the created model

The devolvement of this study was focused on proposing a solution to address the shortage of labor in an automotive parts supplier’s factory and to prepare the plant for the projected increase in demand in the coming years. It is important to emphasize that the automation of material handling includes not only the implementation of mobile robots but also the automation of the labeling process and the changes to the feeding system for the production cells, sorting area, receiving/shipping area, and the warehouse. To enable this, it may be necessary to change the layout of the plant.

Case description—automotive parts supplier

With the economic growth associated with the trend to automation and Industry 4.0, the company being studied has heavily invested in robotics. For the last 5 years, this company has identified the need to automate the material handling in order to meet customer demand. This decision was based on the lack of labor on the production floor, combined with the need to increase traceability of the materials and to reduce the production lead time.

As the turnover of operators is considerably high at the company, it is essential to allocate the qualified employees to more value-added activities, such as operating complex machines. Also, a lot of effort has been expended to trace material or to adjust inventory due to human errors while scanning the products or by misplacing them.

The three main goals of this project were as follows:

Minimize the labor required on material

Improve floor space utilization to allow the installation of more production cells

Optimize the current material handling flow

The challenge of this application was due to the desire to implement mobile robots on the production floor rather than warehouses.

Current state

The current state analysis was focused on the finished goods and on the processes that were impacted with the automation of the material handling. There were six production cells that would be impacted with the use of mobile robots—cells SD1, BK1, BK2, DF4, DF5, and DF6—plus the sorting area and the shipping area.

Figure 1 shows the layout of the plant at the beginning of this project development. The representation of the material flow in Fig. 1 shows the material flow that is standardized. The labeling process flow was not represented there because the forklift driver has the flexibility to go to any of the labeling stations, as well as frequently the supervisor provides the label to the cell’s operator when the quantities and weight are known.

Current material flow and plant layout

Analyzing this initial layout, it could be easily verified that the flow of material of the finished goods was not linear. For example, the location of the sorting area added unnecessary travel distance. Also, SD1 was placed close to the shipping area due to its high volume. However, if the parts built there needed to be sorted, the flow was increased tremendously as they must travel to the sorting area.

It is important to highlight that the location of the production cells could not be easily modified, as they are complex-automated cells with constraints of infrastructure installation and ceiling height. Therefore, they were considered fixed locations for this analysis.

The general process for the material handling in these cells was the forklift driver brings the raw material from the receiving area to the cell. With a hand scan, the driver scans the material to execute the warehouse transfer between the previous location and its current destination. Once the parts are assembled and one tote is full, the forklift driver scans the tote and takes it to a labeling station. The tote is weighed, and a raw material (RM) label is printed. The RM label executes the transaction in the enterprise resource planning (ERP) system, which deducts the raw materials used and adds to the inventory the amount of material produced. After this label is applied to the tote, the driver takes it to its destination, which can be either the BK1 cell, the BK2 cell, the sorting area, or the shipping area. Once the tote is at its destination, the driver must scan it again, so the virtual warehouse transfer takes place.

This current process was susceptible to many errors due to its dependency on the manual labor.

Layout proposal

With the understanding of the current state of the production floor, changes were proposed to enable the automation and to improve the utilization of the mobile robots.

One way to increase the AMR efficiency was by reducing its traveling distance. Knowing that changing the location of the production cells was to be avoided, this study focused on the investigation of changes in the sorting area, shipping area, and in the labeling process.

For the sorting area, its reallocation to an area close to shipping or near to the cells which demand the most inspection was studied. Analyzing the plant layout, a solution was to move the sorting area to the market place (see Fig. 2 ).

Proposed material flow and plant layout

With the sorting happening at the market place, the traveling distances of the parts coming from the DF4, DF5, DF6, BK1, and BK2 would be reduced significantly. On the other hand, evaluating the parts coming from SD1, the flow of material would still not be desirable as the parts’ traveling distance would more than double for the scenario when a quality inspection is required.

To solve this, it was proposed that the sorting for this cell was done in line. The high volume of SD1 supported this decision. Thus, the parts would always leave SD1 and go straight to the shipping area. Figure 2 shows the flow of material according to the changes proposed.

Regarding the shipping area, it was proposed to create an area dedicated to the SD1 parts due to the high demand. As the interaction between the mobile robots and the forklift is to be avoided, it was suggested to place the shipping area for these parts on the same side of the aisle as the cell. This would help to eliminate forklift and AMRs traveling on the same aisle in some of the layout approaches that will be discussed in the following sections. Implementing a path dedicated to the mobile robots, as well as putting in place processes that minimize the interruption of the AMRs’ flow promotes the learning curve necessary when a new automation is implemented.

The end goal of the material handling automation was to have one piece flow between the production cells and the shipping area. To enable this, some enhancements were proposed to the production cells, such as the implementation of vision inspection to ensure the quality of the parts and the automation of the final packaging.

The modifications proposed in this study reduced the products lead time as they reduce their traveling distance, and decrease their cycle time by minimizing the need of manual sorting, manual labeling, and manual packaging. It also reduces the amount of labor needed.

Layout scenarios

As discussed previously, three scenarios were developed to decide which layout concept would be most appropriate for this application. The first scenario is the conventional layout, presented in Fig. 3 . In this scenario, every AMR can handle the material from any production cell. This concept allows the mobile robot to judge the best route to be taken to reach its destination, and it guarantees a balanced workload between the robots. It also optimizes the priority rules, as it is applied on the whole system and not just within a section.

Conventional layout scenario

In addition, this concept gives more flexibility for storage location and parking spots. Also, the failure mode for this situation is less critical when compared with the other two approaches, as the tasks can be delegated to a different AMR, and the robots have more flexibility to choose a path in a blockage situation.

One of the drawbacks is that all the aisles on which the AMR will be running need to be wider to permit the passage of two AMRs on the same aisle. It requires a robust control system. This scenario also does not support the interaction avoidance between AMRs and forklifts for the SD1 cell.

The second scenario used the tandem layout, shown in Fig. 4 . This approach presents a mix between the single loop concept and the conventional layout. For this simulation, the cells were divided into two sections: the first group consists of the SD1 cell and the second group handles the sorting and all the DF cells. The difference between this approach and the single loop is that more than one AMR can be placed in one section.

Tandem layout scenario

The tandem approach minimizes some of the drawbacks associated with the single loop (as identified below). It reduces the number of locations dedicated to storage, as all the totes for the DF cells can be put in the same place, and it permits the implementation of only one labeling station. It also gives the AMR more flexibility to select the best path to reach its destination.

This concept also allows the isolation of the SD1 cell. By putting one AMR dedicated to the SD1, a unidirectional aisle can be dedicated to the mobile robot translation which eliminates the interaction between AMRs and forklifts.

The disadvantage of the tandem layout is that if more than one AMR is allocated within one section, it necessitates wider aisles. This fact also increases the complexity of system control as the deadlock and collision situations must be addressed.

The last model followed the single loop approach, presented in Fig. 5 (3 single loops) and Fig. 6 (4 single loops). In this scenario, the plant was divided into sections where only one AMR would be responsible to handle the materials. The advantage of this solution is the reduced complexity of the control system, as the deadlock avoidance and the collisions do not need to be addressed. Also, it minimizes the width of the aisle as the AMR would not need to cross each other.

Single loop layout scenario with 3 loops

The single loop layout increases the number of storage places, parking areas, and labeling stations. It also required an intermediate location for the parts produced in DF5 and DF6 that need to go to the BK1 or BK2 cells. This scenario might also generate significant imbalanced workloads between the AMRs, and a failure mode of one robot could have a tremendous impact on the production schedule of its section. Modification on how the sections are divided would require a substantial amount of effort in programming the robots and in reallocating parking spots, storage locations, and labeling stations.

In this scenario, the AMR always follows the same path and every AMR must have a unique path.

Two options of this scenario were analyzed. In the first option, shown in Fig. 5 , the production cells were divided into three sections: the first area was designated to the SD1 cell, both finished goods and brackets. The second section was for DF4 and sorting, and the third area was for DF5 and DF6. The general shipping area would have to allow the delivery of parts from both sides.

The second option was to add one more segment to separate DF5 and DF6. Thus, the workstations were divided into four sections as shown in Fig. 6 . The first area was dedicated to SD1, both finished goods and brackets. The second section was dedicated to DF4. The third area was for sorting and DF5. The last one was dedicated to DF6.

Single loop layout scenario with 4 loops

It was not proposed to have a single loop with 5 divisions because it would be counterproductive due to the lack of paths to the shipping area and the high amount of intermediate storage that would be required. In both the single loop and tandem approaches, it was desired to leave SD1 by itself due to its volume and its physical separation from the rest of the cells. In all the scenarios where there is more than one AMR responsible for the material handling within a section, it was necessary to create unidirectional double paths rather than bidirectional single paths. The reason for that was the extensive blockage situations presented when single paths were applied.

Comparison of scenarios

To decide which approach would be most appropriate with the plant’s reality, all three layout scenarios were simulated using FlexSim. For each layout, multiple scenarios were considered. The model parameter value that changed in each scenario was the number of mobile robots.

The performance measures were the percentage of idle time of the AMRs and the percentage of time each cell had a tote waiting for transportation. The maximum and minimal value was captured to verify the statistical dispersion of the results, as well as the confidence intervals with 99% degree of confidence. As a waiting tote can stop the cell from running, it was required that the average cells blockage be below 2%.

Blockage for the DF cells means the cell is unable to produce parts due to the lack of empty totes for the new parts. A low percentage of waiting time is acceptable as the cells can manage a small buffer. However, the goal is to design a process where the wait for transportation is zero. Table 1 shows a summary of the scenarios simulated.

Also, the charging base of the AMRs was placed in their parking spots, where there was one charger for each AMR. The AMR was charging every time it was located at the parking spot. Each AMR would go to its parking spot whenever it was idle. Therefore, the amount of time the AMR was charged was equivalent to the idle time. Reviewing the specifications of the AMRs, it was decided that the AMR had to charge on average 30% of its operational time.

With respect to the demand for work, it was decided to use the production cells maximum real capacity, which accounts for machines unavailability and manufacturing errors. These measurements reduce the cells’ capacity to 75% or 80% depending on the cell. This decision was based on the fact that it was completely undesired for the AMRs to be the bottleneck. For the sorting area because there are parts built in work cells other than the DF cells that need to be sorted, the data from a normal work week was used.

The average hourly demand was used with the normal distribution for internal variability of the demand estimated between 11 and 20% of the mean. The estimation of the variability was selected by analyzing 1 week of the main cells’ historical data.

For safety measures, even though the majority of AMRs on the market can go up to 2 m/s, the maximum speed of all the AMRs was set to 0.8 m/s. When the robot was carrying a load, the maximum speed was reduced to 0.6 m/s. On a curved path, the speed was set to 0.6 m/s when empty and 0.5 m/s when loaded. The loading and unloading time were considered as 40 s, and the labeling time was set to 60 s. Table 2 summarizes the system’s parameters.

From the results of the scenarios simulated, showed in Table 1 , there were 4 scenarios that were feasible and of interest. To define if the scenario were feasible and of interest, it was analyzed using the average, the maximum, and the minimum percentage of the idle time of the robots, as well as the percentage of the cells, blocked time. Tables 3 and 4 show the overall results of each selected scenario. It also presents the confidence interval with a 99% degree of confidence level. Comparing these results, the best layout approach was the tandem layout, where the plant was divided into two sections. The AMRs presented higher average idle time when compared with the conventional layout scenarios using 3 robots. Also, the results from scenario 4 Conv did not justify the cost of adding one more robot.

When compared with the single loop, the tandem is more beneficial due to a better workload balance between the AMRs and a better material flow.

Discussion and evaluation

The key performance indicators (KPIs) that were chosen to evaluate the material handling automation system were throughput, response time, total labor dedicated to material handling, management of buffers, starvation avoidance, blocking avoidance, deadlock avoidance, dealing with disruptions, and capital cost of automation. Evaluating the chosen layout with regards to the KPIs identified, the tandem layout satisfies the throughput of the cells when 3 AMRs are used, and the starvation avoidance. This was proven by the low percentage of blockage time. This layout also provides the ability of quick response time in both sections of the system. In the DF cells section, if there is an urgency, one of the AMRs can be easily selected to execute the task. In the SD1 section, on the other hand, the AMR is dedicated to the one unique cell which will also allow for an immediate response.

Analyzing the flexibility to deal with disruptions and the blocking and deadlock avoidance, there is a tradeoff to be studied for this approach. The DF cells present a more flexible set up to deal with disruptions, as one AMR can be removed, and the cells will still be fed. However, the blockage avoidance and the deadlock avoidance need more sophisticated programming to be accomplished in this section. On the other hand, the SD1 section does not require this complex programming as there will be only one AMR operating. However, having just one AMR reduces the ability to deal with disruptions, such as breakdowns. These last two aspects need to be considered when choosing the AMR, as well as when deciding the interface between the mobile robots and the cells.

Conclusions

The next step of this project is the actual implementation. As Haneayah et al. state, the automation of the material handling is a complex installation that comprises various processes, such as inbound, storage, batching, sorting, picking, and outbound processes [ 10 ]. Therefore, it is important that the management support it as well as a culture change on the production floor.

The 5S concepts are vital for the success of this project. The cells and aisles need to be kept organized, allowing the flow of the mobile robots. The blockage of aisles can have major impacts on the performance of the AMRs.

Another important point is the cooperation of the forklifts’ drivers. As the material will be handled by AMRs and forklifts, the forklifts must be trained and be attentive to the AMRs to avoid blockage or damage.

With the changes required and the learning curve, it is recommended that during the first phase of the implementation the interaction between forklifts and the AMRs be avoided. This can be done by creating a separate aisle for the AMRs or creating traffic rules limiting the flow of forklifts in certain areas.

As manufacturing plants are not static places and pathways in them tend to collapse to the minimum allowable over time, this theorical study presents potential limitation regarding the adequacy for the real-world operation. However, the discrete simulation tool can be easily edited to represent the reality over time.

Availability of data and materials

The data that support the findings of this study are available from the company for which the study was completed but restrictions apply to the availability of these data, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the company for which the study was completed.

Abbreviations

Automated guided vehicles

Autonomous mobile robots

Key performance indicators

Light detection and ranging

Tandem loop with multiple vehicle

Raw material

Enterprise resource planning

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Acknowledgements

The authors would like to acknowledge the contributions of Dr. Charles R. Standridge and Dr. David W. Zeitler of Grand Valley State University for their review of the analysis completed for this study.

Funding for this study came from the company for which the study was completed. An author of this paper (AM) was an employee of the company for which the study was completed. The company’s management had no role in the collection, analysis, or interpretation of the data.

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AM prepared the simulation model, ran the simulations, and was a major contributor in writing the manuscript. LC reviewed all simulation results, provided guidance on the analysis of the results, and contributed to the writing of the manuscript. Both authors read and approved the final manuscript.

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Melo, A.F., Corneal, L.M. Case study: evaluation of the automation of material handling with mobile robots. Int J Qual Innov 6 , 3 (2020). https://doi.org/10.1186/s40887-020-00037-y

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Received : 07 February 2020

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Published : 27 June 2020

DOI : https://doi.org/10.1186/s40887-020-00037-y

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Home > 4 Warehouse Management System Case Studies

4 Warehouse Management System Case Studies

• July 23, 2020

Successful WMS Implementation Case Studies

Warehouse Management Systems (WMS) represent a major investment in your supply chain and operational efficiency. While it can be difficult to gauge your estimated time to value, these four cases featuring enVista clients provide a warehouse management system business case and showcase outcomes after successful WMS implementations.

In this post, we’ll cover four examples of WMS implementations and how they helped companies to optimize warehouse operations :

• Nature’s Best
• Performance Bike
• Bradshaw International
• Men’s Wearhouse

Four  WMS Implementation Examples

1. nature’s best.

*Note: Since project completion, Nature’s Best has been acquired by KeHE.*

Leading the market of health and natural foods distribution, Nature’s Best serves Certified Organic products in over twelve states. Nature’s Best was experiencing high labor costs based on time and manpower to transport temperature-controlled food products between four buildings on its DC campus. The company’s zones were organized to suit either small or large clients – a key competitive differentiator. Because of the facility layout, the overall distribution process was inefficient; each product was touched 18 times on its way to the customer. Nature’s Best technology, distribution processes and buildings also needed updating to keep pace with growth projections.

enVista was called upon to address and resolve the challenges Nature’s Best was facing and did so using its consult, implement and operate (CIO) methodology to create a customized solution.

Phase One: Consult

A supply chain strategy that met Nature’s Best’s business goals was developed. enVista conducted a material flow analysis and redesigned the internal flow processes to increase efficiencies. As a result, a global WMS was selected that addressed all of Nature’s Best’s concerns and determined construction needs for the distribution center (DC). Operations would be consolidated to one DC, and enVista designed the new facility with various temperature-controlled zones.

Phase Two: Implement

As Nature’s Best began construction, enVista supervised the integration and implemented a Manhattan Associates WMS including interface design, configuration, training, facility preparation and labor standards among other features. Nature’s Best shifted from a mechanized to non-mechanized system and from paper to radio-frequency (RF) devices with voice-based technology. enVista managed the move of $25 million of inventory and trained the company team on new system processes.

Phase Three: Operate

During go-live, enVista ensured a seamless transition into Nature’s Best new facility, systems and processes. Throughout the Consult, Implement, and Operate phases, sales were steady – even growing – and upon completion, the project was delivered on time and within budget. The chosen system required few modifications for Nature’s Best’s business model, which would lower costs and allow for easier upgrades in the future.

The new system reduced labor costs by over 30 percent and more than doubled productivity. Ninety-seven percent of full-time employees were retained, and temporary and non-value-added positions were eliminated. Nature’s Best went consultant-free only four weeks after go-live.

Download Nature’s Best Case Study

Example 2: Performance Bike

Performance Bike is a privately-held, specialty retailer focused on bicycles and accessories. The company had expanded to over 110 retail locations since its founding in 1982. Performance Bike had a DC in Chapel Hill, NC, with over 60 associates and partners with a 3PL in Long Beach, CA.

Due to compliance issues with the U.S. Postal Service barcodes, Performance Bike had to make system changes to its Manhattan PkMS WMS. The company’s experience with Manhattan Associates gave it a flexible approach when considering an upgrade. enVista’s enABLE methodology was used for the upgrade, and many of the roles typically filled by software or consulting companies were completed by Performance Bike.

Because of the prior experience and flexibility of Performance Bike and enVista, the WMS implementation was under budget and on time. Team members from both enVista and Performance Bike worked together to complete and implement the WMS. The vice president of warehouse operations for Performance Bike noted enVista’s customer-centric approach and flexibility.

The WMS upgrade was implemented in less than 6 months. There were very minor changes to the user experience, so trainings were seamless and increased productivity. Performance Bike experienced a pick per hour increase of 50 to 100 units per hour, exceeding the company’s executives’ expectations.

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Example 3: Bradshaw International

Bradshaw International’s Good Cook™ brand is sold in over 30,000 U.S. retail stores. Bradshaw is a leading marketer of kitchenware products and launched Good Cook to incorporate quality, value and service into every product. This philosophy has allowed Good Cook to achieve the best position for kitchen tools and gadgets with 43 percent of the market.

Bradshaw was asked to participate in Wal-Mart’s direct store delivery consolidation (DSDC) program as Good Cook is distributed in the stores. The program was designed to allow shippers to directly replenish Wal-Mart stores in less-than-case-pack quantities. To do so, Bradshaw had to make changes to several parts of its current distribution systems.

Changes to electric data interchange (EDI), order management, and a pick/pack operation integrated with a new WMS would be required to handle the new variable volumes. enVista was asked to help design and integrate the DSDC program. To meet Walmart’s DSDC objectives, the team had to design and build a new pick/pack module, select the technology to be used by the picking team, and integrate it with the WMS. The order management software , EDI software and billing system had to be modified to accommodate the structures required by Walmart’s DSDC program.

The team profiled SKU movements, identified pick and storage mediums to model replenishment rates, and formulated labor plans and proper work flows. Bradshaw IT and enVista worked together to make configuration changes to the RedPrairie WMS and integrate it with the Pick from Light System and EDI software. The joint team also specified data maps from order capture to order management to WMS through EDI transmissions to move the infrastructure to industry standards.

With enVista’s help, Bradshaw successfully integrated the DSDC program into operations. Shipping volumes increased beyond expectations, but the new WMS has allowed Bradshaw to keep up with demand. The program was implemented with almost no customer disruption.

Example 4: Men’s Wearhouse

Founded in 1973, Men’s Wearhouse is one of the country’s largest specialty retailers of men’s apparel with over 700 stores. The stores carry a full selection of high-end men’s clothing and accessories.

Men’s Warehouse’s main DC was a 1.1-million square foot facility in Houston, Texas. It is the core retail distribution center for Men’s Warehouse retail stores, as well as 60 percent of merchandise from K&G Retail stores, acquired in 1999. A significant percentage of its garment-on-hanger merchandise is shipped by dedicated fleet to regional hubs across the country. enVista’s main objective was to consolidate retail and e-commerce systems to run all operations on a single platform and a central material handling equipment (MHE) integration point.

enVista acted as the program management role for supply chain execution and MHE software functions for all facilities. The implementation of the new systems platform occurred in two distinct phases.

The first phase focused on using the new systems platform to more efficiently meet Men’s Wearhouse’s growing e-commerce business needs. A new WMS and distributed order management system were implemented and integrated to an e-commerce web platform. These systems allowed strategic decision making regarding e-commerce order fulfillment and room for growth, along with the accuracy and flexibility necessary for seamless execution and delivery.

Phase two focused on implementing the new WMS and a consolidated warehouse control system (WCS) in Men’s Wearhouse’s Retail Distribution Operation. The WMS replaced the retailer’s legacy system, and the WCS consolidated the management of several operations into one system. Men’s Wearhouse now has the ability to dynamically change product flow, unit allocation, and achieve more effective utilization of Case Level ASN receiving with the new WMS. The system’s ability to recognize and execute on cross-docking opportunities created improved throughput and lower overall processing costs.

With the implementation of a common WMS and standardized processes, Men’s Wearhouse was able to share recourses across operations and respond to seasonal increases in workload more effectively. The implementation of WMS and WCS gives the company the ability to consolidate its distinct Men’s Wearhouse and K&G distribution operations to reduce costs and increase overall processing efficiency.

Download Men’s Wearhouse Case Study

Conclusion: enVista’s WMS Expertise

Getting your WMS right and making sure it’s integrated properly across your supply chain technology stack is critical to realizing quick ROI and improved operational efficiencies. 

enVista has completed hundreds of WMS implementation projects in its nearly two decades of experience, and our vendor agnostic approach to consulting and implementation ensures you get objective help for your most critical projects. We’re passionate about supply chains and delivering solutions that are the right fit for our clients and would love to help you optimize your supply chain.

If you have a WMS project on the horizon or want to learn more about how we can help you, let’s have a conversation .

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Roboteon Enhances its Innovation Lab Focused on Software Platform for Robots, Warehouse Automation

SAN JOSE, CA / May 29, 2024 / Roboteon, a provider of an innovative software platform that helps companies achieve success with their investments in warehouse robotics, has recently added new capabilities to its multi-function Innovation Lab near San Jose.

The 3000-square foot lab, located just minutes from the San Jose airport, features Roboteon's Robotics Fulfillment Platform software working with different types of robotics and hardware systems from a variety of vendors. The lab supports demonstrations of many different applications and use cases.

Those applications include:

• Basic warehouse and manufacturing robotic transport functions using a variety of Autonomous Mobile Robots (AMRs) • Full interoperability of robots of different types and vendors, all managed and optimized in the single Roboteon platform with a unified interface • Cart picking with optimal order mapping of picks to the cart and optimal routing to minimize travel time • Collaborative picking with a human associates and AMRs working together as one • Enterprise Fleet Management, which provides traffic control and visualization across mobile robotics from different vendors

Roboteon is committed to continuous investment in the lab. Recent additions include the deployment of automated picking arms to support piece picking ("pick and place") and case picking applications, optionally working in conjunction with AMRs, and leveraging an advanced vision picking system.

The lab already has mobile robots from multiple vendors working together, as can be seen in a short video: https://www.roboteon.com/innovation-lab-video.php

The lab serves multiple purposes, including the following:

• Providing potential adopters of robotics a chance to gain a hands-on feel for relevant equipment and software • A facility to bring on new robot types and vendors for rapid integration and testing of the robot(s) with the Roboteon software platform • A flexible, dedicate area for research and development of new warehouse automation capabilities.

"The Innovation lab is a competitive advantage for Roboteon," said CEO Gana Govind, adding "It allows us to accelerate development of our platform, and showcase to customers many options and applications for warehouse automation."

Contact Roboteon today to discuss your warehouse automation and robotics opportunities or to schedule a tour of the lab.

About Roboteon

Roboteon is the market leader in software to enable successful deployment and operation of robotics in distribution. Our Robotics Fulfillment Platform is a cloud-based, end-to-end software system that enables companies to quickly test, deploy, and drive maximum value from investment in robotics and complementary warehouse automation. It enables interoperability across robots from different vendors, optimizes robotic picking workflows, synchronizes human and robotic resources and more. This is achieved in part through advanced use of AI. Combined with deep domain expertise, our technology speeds time-to-value for robotics deployments and increases productivity and throughput from operations. You can learn more at www.roboteon.com.

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