WMS and Robotics

The growth in robotics and automation in the warehouse and wider supply chain is accelerating. The ever-increasing demand to make the best possible use of resources and emergence of new technologies are driving a surge in demand. What if any are the implications for warehouse management software (WMS) and associated applications?

Robotics and automation in the warehouse are not new. Conveyor and sortation systems have been around for decades. AGVs (autonomous guided vehicles) have been available for almost as long but were initially relatively expensive. Robotic arms are commonplace in manufacturing and, increasingly, logistics applications. Even humble lift trucks and order pickers have evolved to incorporate functions such as automatic lift height selection which enable a degree of “automation” and features such as wire-guidance and digital motors which help them integrate with other technologies.

The majority of this automation equipment was designed to fulfil repetitive tasks in a fixed position or a specific and well-defined area. The difference now is “autonomy” with many of the recent advances being in equipment that can operate on its own and move freely around a facility. Costs have decreased while advances in applications and supporting technologies have made it possible to integrate solutions more easily while meeting many more requirements. At the same time, with real estate prices and labour costs increasing, there is the constant pressure to make the best possible use of infrastructure and people, and maximise capacity, throughput, efficiency, and productivity. In short, the investment required can be more easily justified in a much wider range of settings.

The impact is stark. In its Intralogistics Robots 2023  study, MMH magazine found that 43% of companies who took part planned to use robots within the next three years. Only 4% said they had no plans to use robots, suggesting that over time almost every warehouse will be using them one way or another. While these figures are largely based on responses from US-based companies, the UK and Europe will not be far behind, especially as the business pressures may be even more intense here. In any case it is clearly one of the leading trends in the supply chain at the moment. MMH also reports that Gartner predicts 75% of large warehouses will be using some form of robotics by 2026 and that Mordor Intelligence predicts the market for warehouse robotics will be $23bn by 2027. Elsewhere, logistics giant DHL estimates that up to 30% of its global material-handling equipment fleet will use some form of robotic automation by 2030.  Data Bridge Market Research estimates that the value of the Global Robotic Arm Market will reach $75bn by 2029, treble the value in 2019.

Supply chain robotics and automation falls into two broad categories. The first is equipment installed in a fixed position in the warehouse. This includes, for example, conveyor, carousel, and sortation systems, as well as pallet wrappers, crane/tower systems, and pick-and-place robots. There are other examples and in most cases these systems or devices carry out their repetitive duties as part of the wider materials handling infrastructure. Many have their own control systems and applications which allow them to integrate with other systems. WMS, for example, commonly interface with these systems to oversee stock management and order picking.

The second, and one attracting all the interest at the moment, is the autonomous or free-ranging robot. These include autonomous lift trucks, AGVs, shelf-stacking lifts, and self-driving dollies for handling items such as trolleys, picking bins, and pallets. In the wider supply chain context, delivery buggies and drones fulfil a similar role and are an increasingly familiar sight in urban areas. Many of these technologies are replacing the more traditional type of warehouse operations that relied on human labour.

What does this mean for the WMS? At a simplistic level, a WMS issues an instruction to move an item from point A to point B and the “system” works out how to do it. From a WMS perspective the information required to manage the flow of items through the warehouse is more or less the same whether they are handled by conventional or automated equipment. Despite achieving often very high levels of accuracy, and no matter how well designed, systems which incorporate people-based interactions always contain a risk of human-error. Properly configured automated processes, on the other hand, should eliminate such potential errors and deliver even higher levels of accuracy and speed. However, this assumes that information is correct at all stages of the supply chain which is not always the case. Therefore, additional checks may be required before items enter the “automated” sections of the supply chain to minimise subsequent errors and WMS may need to incorporate new/different exception handling capabilities to capture the small number of errors that remain.

With fixed-position equipment the tasks involved are repetitive and relatively predictable. The control systems work with the WMS to work out what to do, in real-time and with high levels of accuracy. Things can be more complex if there is a choice or decision to be made. This might be the case, for example, if manual and automated picking are taking place simultaneously. In this example, the WMS and robotic equipment should work together to “decide” which is the most efficient way to complete the pick. Much if not all of this can itself be automated or pre-programmed with the decisions made by the systems based on predetermined rules or logic. For example, if a single item needs to be picked quickly for rapid despatch the best option could well be to instruct an operative to complete the task. Or it might not be. The point is, a well-designed and configured system will be able to make this type of decision based on its underlying programming, perhaps using a growing and evolving knowledge base of historic data. In other words, the system learns over time (sometimes a very short time) what is the best solution to any given new task. None of this is rocket science in the WMS world and many systems work this way. But the emergence of new forms of AI could take this decision making in new directions because the underlying systems will identify new patterns and be able to respond more flexibly than current systems.

Most operators with an existing facility will see the biggest benefit from automating certain aspects of their warehouse, most likely the high-volume and fast-moving areas. WMS such as ProWMS enterprise-level Advanced Warehouse Management have the inherent flexibility to support whatever processes (and changes) the operator decides. Ideally this will be achieved with minimal recoding. However, with its own modular design, ProWMS allows operators to add new functions and processes such as voice, pick-and-pack and so on whenever they choose rather than expecting them to specify a fully featured application from day one. This modular model also sits well with a rapidly evolving ecosystem such as we are currently seeing with new types of robots and automation. This is because creating a new module typically avoids the complexities of reworking a larger, non-modular code base.

Comments are closed.