To keep pace with today’s productivity and efficiency demands, warehouses need to up their games. They’re not just storage facilities, but integral parts of complex global supply chains. Warehouse automation has become a vital tool to meet these demands.
Warehouse automation is the use of specialized equipment and systems to perform work. It is focused on taking over and reducing manual tasks that are rule-based, repetitive and prone to error. Performing the task the same way each time, without delays or deviations from a predefined process, is more important than judgment or discretionary capabilities.
Warehouse automation uses a wide variety of hardware and software, including robots to store and retrieve products, label inventory, and complete back-office processes like capturing data and generating reports. While diverse in terms of technology, the common business purpose is to streamline, accelerate, and ensure the consistency of operations. It delivers major productivity benefits, reduces labor costs, and creates a safer work environment.
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Warehouse automation is driven by varying economic forces, ranging from supply-side cost-saving, efficiency, and productivity pressures to demand-side imperatives for delivering products with greater speed and transparency. Over the last decade, delivery speed has been especially important, with e-commerce and "lot size one" consumer expectations pushing businesses and supply chains to be more agile.
Businesses not only need to increase gross output, but they also need more granularity in production and delivery capabilities. In addition, the COVID-19 pandemic demonstrated the need for increased supply chain resilience, with reduced reliance on human labor and greater diversity of production and storage locations.
Warehouse automation technologies can be classified into several types and can be implemented at varying levels of complexity. This ranges from simple, single-application technologies automating a particular task or process, to end-to-end systems automating clusters of interconnected tasks, processes, and technologies. It incorporates both:
Digital automation is the use of software to enhance the capabilities of information technology. Your initial investment is in standard hardware (such as mobile tablets and internet networks). It is then leveraged through task- or process-specific software ranging from basic applications and application programming interfaces (APIs) to data analytics platforms and machine-learning algorithms.
With cloud technology, the barriers to entry have been significantly lowered. Many types of automation that used to require on-site infrastructure for storage and computing is now available through and “as-a-Service” model via external providers.
The primary purpose of digital automation is to reduce manual workflows. For example, sortation systems using automatic identification and data capture (AIDC) technology, including radio frequency identification (RFID) and mobile barcode scanning, automate the process of identifying and tracking inventory. This creates a smoother and more convenient experience for workers and customers, boosting productivity and reducing the cost of manual errors.
Pick- and put-to-light systems combine sortation systems with digital lighting to guide workers to locations where they can place or retrieve an item.
The resulting data can then be combined with additional information, including workflows, in a warehouse management system (WMS) providing these benefits:
Enterprise resource planning (ERP) takes WMS a step further:
Physical automation uses mechanization, including robots, to assist or replace human employees in performing warehouse tasks. This encompasses a wide array of task-specific technologies frequently combined into larger systems to automate processes, such as combining AIDCs with conveyors to simplify movement and sortation of inventory across a warehouse.
For moving inventory around a warehouse, businesses can use automated guided vehicles (AGVs), which utilize magnetic strips, sensors, or cameras to navigate. These work well in large, relatively open spaces, but aren’t complex enough when people are working or the layout changes frequently.
In those cases, autonomous mobile robots (AMRs) are a better solution. Leveraging GPS to map out routes and laser guidance systems to detect and move around people and other obstacles, AMRs can navigate safely and efficiently, and are also easy to set up.
Automatic storage and retrieval systems (AS/RS), combine equipment with computerized controls (either operated partially by a human worker or completely automated and autonomous) to move, store, and retrieve products or equipment with a high degree of speed and accuracy.
AS/RS vary in scale and complexity, from small systems designed for simple or very specific tasks, to large systems automating storage and retrieval across an entire warehouse. They can also integrate into manufacturing and distribution processes. There are various AS/RS subtypes:
Goods-to-person (GTP) fulfillment systems combine several technologies to increase productivity and enhance efficiency of storage, throughput, and labor utilization. For example, cube-based storage is a high-density, GTP system leveraging robots to transport items to and from a cubical storage grid with inventory bins. Other variants may include vertical lifts, conveyors, and AMRs.
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Warehouse automation can help you improve productivity, reduce human error, minimize labor constraints, and enhance material handling coordination while improving workplace safety and worker well-being.
A well-designed warehouse automation system provides increased accuracy, less strain and fatigue, and fewer injuries, which creates an engaged and committed workforce.
Warehouse automation technologies can be combined into systems to meet the evolving requirements of different business and organizational contexts. For example, the AutoStore warehouse automation system is modular, meaning it is composed of smaller parts that can be assembled to create structures of varying dimensions, scales, and levels of complexity. It fits anywhere and into any business, regardless of size or operational demands.
If implemented intelligently, warehouse automation can reduce your carbon footprint and contribute to a more sustainable approach to industrial storage and manufacturing. Many automation solutions allow for denser storage and operations, reducing the physical area required perform the same functions, and the corresponding urban sprawl.
Similarly, a hyper-dense and efficient layout often requires less energy than traditional storage approaches. For example, AutoStore Robots require no heating, ventilation, lighting, or cooling. Additionally, they leverage smart charging schedules. As a result, AutoStore measurably reduces energy consumption and carbon emissions, with many customers using solar energy to power the system.
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Like all areas of the advanced industrial economy, the changing demands on warehouses cannot be understood in isolation. Based on Gartner’s infrastructure and automation predictions, warehouse automation is likely to be shaped by several wider trends in the coming years. The crucial throughline for warehouses is that automation is speeding up, with more and more organizations shifting toward entirely automated value chains supported by artificial intelligence (AI) capacities.
In this context, systems-level warehouse automation, including WMS, GTP fulfillment, and other advanced AS/RS will be increasingly necessary, as will further integration with ERP systems. This will both support and enable the integration of AI and machine learning (ML) capabilities, as greater quantities of data can be gathered, analyzed, and used to support decision making. The resulting plans can then be applied predictably using systems-level automation.
For example, ML can consolidate and analyze data from streams like WMS and individual devices (e.g., hand-held terminals) to make predictions about how long a given task or process will take. Data can be incorporated into dynamic workflows that coordinate behavior across the entire warehouse (or even supply chain). AI/ML and increased levels of automation are, therefore, mutually supporting: those who invest in automation will be in a better position to leverage AI/ML as the technologies evolve and gain traction.
When it comes to implementing warehouse automation, a holistic strategy is key to success and involves three main areas of focus: quantifying costs and returns, considering technology and spatial logistics, and managing processes and people.
The first and perhaps most fundamental issue to address is people and processes – the employees who will need to work alongside the new technology; the managers and leaders who oversee implementation and redesign business processes; and the consumers and other stakeholders who need to understand how the technology works and what to expect from it.
It will be necessary to redesign business processes to accommodate the technology. This should involve end-to-end consideration of existing infrastructure, including warehouse buildings, equipment, and IT systems. Owners also need to understand what levels of technical expertise currently exist versus what will be required. Employees must then receive the retraining and upskilling necessary to use the technology or comply with new business processes.
It is also important to plan the deployment and how you’ll quantify expected returns or benefits. Alignment between parties, delineation of responsibilities, and establishment of key performance indicators (KPIs) are vital to successful implementation. This includes an evolutionary element:
Finally, it is important to explain the relevant benefits to stakeholders, such as executives and shareholders (in terms of cost savings, productivity, and reliability), and consumers (in terms of transparency and fulfillment speed expectations).
Consideration of how to quantify costs and returns should inform both your initial investment and how you adapt your strategy over time. This involves:
When figuring out how to maximize your return on investment (ROI), you should consider the direct impacts of the solution and how processes can be reorganized to leverage the new technologies, and the balance of these two elements, i.e. savings on low-skilled labor but increased expenses due to retraining and specialized staff. Costs, meanwhile, should account for both up-front costs and total cost of ownership (TCO), including maintenance and software.
Finally, it is important for impact to be measurable over time, so that potential and actual performance align consistently. You should define metrics and practices to measure performance, assess what is going wrong if expectations are not being met, and redesign processes and procedures as needs dictate.
As with any complex business or technology development, logistics can make or break your strategy. Here, the key logistics to consider are implementation over time, data storage and handling, and scaling of the solution.
Before beginning implementation, assess what can be altered in your existing setup to create a smoother transition. Ensure you have enough physical space, clear out equipment, or reorganize the floor plan to accommodate the new technology. This should include both the absolute amount of space and its distribution throughout the warehouse.
For example, if you are installing AGVs, you may need to simplify the layout, create wider corridors, and ensure staff and AGV movement won’t clash. Additionally, check whether legacy systems are compatible with new solutions, remove outdated hardware or software, and purchase necessary replacements.
You will also need to consider how data will be stored, managed, and processed so it can be used in systems like WMS or ERP, and/or fed into ML or predictive analytics software. This may involve purchasing and maintaining on-site infrastructure or using cloud technologies.
In either case, both cost and management logistics need consideration.
Finally, you should visualize how the solution will scale. There are several factors to consider here, such as changing consumer preferences and an ever-evolving business landscape.
Assess how quickly you can adapt to new market entrants and system shocks, and how and where the technology supports the flexibility and reliability of key business functions. This will help you understand how easily you can scale order fulfillment up or down, or increase or decrease staff. In essence, the more adaptable you are, the better your chances of long-term success.
Automation in warehouses means using specialized systems and equipment for work previously performed by manual labor.
Broadly, there are two types of warehouse automation:
The benefits of warehouse automation are enhanced productivity, increased order-picking accuracy, streamlined warehouse and inventory management, improved workplace safety, reduced carbon footprint, and more.
Physical automation involves mechanization (robots, automated guided vehicles, and more) to assist in otherwise manual tasks. Functions like sorting inventory, simplifying material movements, and retrieving products are automated across the supply chain processes.
Digital automation, on the other hand, requires standard hardware (internet networks and mobile tables, for instance) and leverages process- or task-specific software such as data analytics platforms, APIs and machine learning algorithms. For example, with digital automation, warehouse inventories can be identified, tracked and sorted through automatic identification and data capture (AIDC). Furthermore, integrating a warehouse automation system (WMS) helps coordinate inventory flows and gives enhanced visibility for supply chain fulfillments.
Automating warehouses requires a holistic strategy, including measuring the return on investment (ROI) and total cost of ownership (TCO) of automation, assessing key logistics, and aligning and upskilling employees’ competencies to integrate the technology.
If you are interested in learning more about warehouse automation, read the AutoStore information guide here.
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