As the growth for fulfillment warehouses, ecommerce and third-party logistics skyrockets and unique customer demands evolve, more companies are exploring the concept of dark warehouses – fully automated, “lights-out” facilities that use intelligent, interconnected devices to operate without human labor. Much in part to labor availability, cost-benefit analysis, technological advancements and more, the shift toward these facilities continues.
Dark Warehouse Drivers
While the reasons for advanced technology integration, including robotic automation, will vary from one enterprise to another, there are multiple key concepts and/or innovations prompting the gradual move toward “darker” warehouse utilization.
Refined Robotic Tools
More affordable, robust and energy-efficient robots can now be easily integrated into a wider variety of operations for increased capacity. Intelligent peripherals, including sophisticated vision, sensor technology and flexible end-of-arm tooling (EOAT), all work together to facilitate fluid product flow with improved quality.
Traditionally ideal for highly repetitive tasks with structured pre-programmed jobs – where little environmental awareness is required – robots can now operate in unstructured settings where there is limited knowledge of object, size, shape and orientation. From upstream processes to end-of-line operations, feature-rich hardware/software solutions are integral for optimal throughput for on-time delivery.
Enabling the shift toward fully autonomous warehouses and distribution centers these technologies are effectively transitioning fixed automation centers with task-specific machinery into flexible automation layouts.
Once a novelty, packaging robots for pick and place, packing, palletizing/depalletizing, sortation and more are now a staple for maintaining production workflow. Especially true for ecommerce, food and beverage, and pharmaceutical sectors, the adoption of high-performance, flexible handling robots with intelligent peripherals is expected to grow at a (CAGR) of 10% by 2032
1. As a result, pure fulfillment warehousing – where daily activities can be complete with little-to-no human interaction – will continue to permeate the industrial landscape.
Improved Workplace Conditions
It is no secret that many manufacturing and warehousing tasks are extremely repetitive and prone to worker injury. Associated with worker burnout and low employee morale, monotonous manual jobs subject to high turnover are ideal for very flexible and capable robotic automation. In turn, this usage can free skilled workers to focus on other value-added tasks and custom orders for greater productivity and profitability.
Where labor scarcity is concerned, the tasks that can be automated for self-sustaining operations—whether it be manufacturing, distribution or assembly—can radically reduce the requirement for human workers. Realistically, with careful planning, spending, integration and management, companies may be able to operate as a dark warehouse for several shifts, consolidating the most difficult work to a single shift or single day per week.
Enhanced Smart Technology
As mentioned, a growing number of advanced technologies, such as vision-guided robotics (VGR), are making it easier to configure, program and integrate robotic solutions, especially for structured high-volume tasks. Well-suited for dynamic factory or distribution settings, adaptable autonomous mobile robots (AMRs) are also enabling highly flexible and efficient operations. The robotic platforms, equipped with robots, vision systems and custom EOAT, maneuver with ease and safety throughout a facility to perform assigned tasks. Ideal for picking, sorting and on-demand material transport, AMRs are becoming an essential piece of the dark warehouse puzzle. With an anticipated CAGR of 20% by 2029
2, these impressive machines will continue to drive lights-out production.
Similarly, digital twin technology is also making strides to improve workflow management and alleviate operational challenges in production environments. An accurate 3D model of a robotics operation that is imposed into the virtual world for testing and enhancement before being implemented in an existing line or workcell, a robotics digital twin helps make predictions about future outcomes for the utmost accuracy, safety and efficiency for a specific task. Whether using computer simulation, pre-programmed algorithms or iterative machine learning, the data gained via digital twin utilization can pre-emptively assist with positioning accuracy, throughput quotas and other perplexing or demanding conditions.
As robotic automation is optimized to better align with digital twin technology and other leading advancements, significant improvements for artificial intelligence (AI), machine learning software and offline programming are also being made. Ideal for robot dexterity and the speed for acquisition and recognition of objects, intelligent machine hardware (i.e., VGR, force/torque sensors, LiDARs, micro-location devices, etc.) combined with AI is addressing the simulation-to-reality (Sim2Real) gap. Learning data resembling a real environment can now be generated via simulation and used to expertly train a robot. As a result, production applications and new workflows are being validated without physical disruption to facility floorplans, boosting performance for competitive edge.
Optimized Cost Savings
Along with improved operations and accelerated throughput (or order fulfillment for on-time delivery), many organizations are experiencing tangible cost savings. The ability to simultaneously operate lean yet productive facilities while maximizing the human worker skillsets needed is a financial win-win – not only for business owners, but customers as well. Once initial payback is reached by the end user, robotic systems and fully automated facilities have the potential to provide considerable return on investment, even with regularly scheduled maintenance.
While it is true the price of full automation can have substantial upfront capital expenditure, the long-term benefits are clear, making dark facilities with full or near-full automation an extremely attractive option for certain industries.
Data-Driven Management Planning
As high-performance robots and their intelligent peripherals, including an influx of smart sensors and devices, are integrated into current operations, decision makers leaning toward dark warehouses should monitor where throughput and quality are lagging, along with tracking excess waste. Whether through a labor-management system or feature-rich monitoring platform, the ability to accumulate real-time data to track operations is key to deciding how to move forward.
Extremely effective, OPC-UA platforms, such as
Yaskawa Cockpit™, facilitate an integrated, intelligent and innovative (i
3-Mechatronics) approach to data collection and enterprise monitoring, allowing company leaders to customize operations to better fulfill organizational goals. Furthermore, the information gained will shed light on internal bottlenecks and other limitations, providing valuable feedback for what may be needed in the future to go completely dark.
While significant breakthroughs are still required to complete a substantial shift to widespread, fully automated facilities, the future demand for them seems strong. Subsequently, more aggressive R&D focused on AIoT (AI and the Internet of Things) and logistics management is being directed toward this need. The more complex the task, the slower the transition will be. However, careful planning and the addition of robots and other smart technologies may currently allow companies to operate during dark modes —where qualifying tasks are consolidated and automated during a specific time. For example, automated equipment may completely carry out part processing during a night shift, allowing experienced workers to provide finishing product touches during the day.
Currently, select facilities – especially for ecommerce and cold warehouses for food and beverage production – may have the ability to operate with very little human interaction. As advances in artificial intelligence and machine learning algorithms evolve, more solutions with proprietary perception tools using AI-driven data from simulation settings will enable robots to complete more complex applications. This, along with adequate planning, monitoring and restructuring of operations over the next decade will make great strides in this realm, igniting much anticipation for a “darker,” more productive future.
1 Packaging Robot Market to Exceed $10 Bn by 2032, GlobalNewswire, 2023
2 Mobile Robotics Market 2023 Driving Factors Forecast Research 2029, OpenPR, 2023