With the so-called Fourth Industrial Revolution dictating just about every operational facet of industry’s forward plan, actionable data is playing an ever-increasing role in measuring and defining a plant or enterprise’s operational capabilities.

Even if we step back just ten years, industry metrics looked at how fast raw materials could be turned into products and shipped to customers. However, the new Industry 4.0 paradigm is defined by how quickly actionable digital data can be created, analysed and shared in order to do the same process – but even quicker, even more accurately, in varying batch sizes, with multiple customer-driven options and, most importantly, without any sacrifice in quality levels.

In the industrial automation market, at machine- and line-level, this new data-driven agility and reactivity is relatively easily leveraged. Contemporary machines are exploiting smart automation and artificial intelligence (AI) solutions, which give them the ability to handle a wider variety of tasks and process steps, all of which can be modified at the touch of a button. Production lines also benefit from fewer variables in terms of issues and line stops; and when these do crop up they are relatively easily solved through simple logic controller interactions or minor operator interventions.

The materials handling industry also enjoys the benefits inherent with smart, connected technology; when everything goes well, it works well, but it can also present a slightly less rosy picture – not in terms of technological availability and adoption, but instead due to the sheer number of variables, with which even the most robust and well-educated AI would struggle. Even with well-formulated action plans and process flows, materials handling operations – especially when we talk about larger-scale movements relying on AGVs, forklifts and trolleys – can throw up myriad eventualities, which require a commensurately high level of potential solutions.

Ron Farr, manager of warehouse solutions at Yale EMEA, explains: “The complexity revolves around these exceptions. If an automated truck is told to go somewhere and pick something up and it ends up getting the wrong pallet, what do you do? Do you pick it up, ignore it, tell the controlling system to make a decision, reject it or drop it? The range of exceptions is potentially vast, as is the range of remedial solutions. And these can vary even more depending on the consignment. How do you solve this problem? In these situations, human interaction and a collaborative environment is necessary, especially when something more than just simple yes/no solutions are required.”

Don’t use ‘problems’ as an excuse

However, potential issues cannot be used as an excuse against adoption of smarter systems. The digital transformations that are underpinning many Industry 4.0 programmes define and almost demand a holistic approach to data infrastructures and capabilities. This, in a nutshell, dictates that anything that has an impact on throughput must live and operate in a more-connected digital realm in order to deliver the all-important ones and zeros to the enterprise controller. There can be no gaps or weak links.

Peter Ward, CEO of the United Kingdom Warehousing Association (UKWA), is adamant: “The message for the logistics industry, which has historically relied on an increased labour force to meet the needs of new client contracts, is ‘wake up and smell the coffee: automation and robotics are coming – and you ignore them at your peril’.”

He continues: “A number of factors are driving this trend and, of course, Brexit is one of them. The combination of falling unemployment levels, minimum wage rises and a potentially reduced labour pool from the post-Brexit EU has changed the cost equation. As a result, automation is stepping closer into the economic justification zone for more logistics operators who are juggling higher volumes, a growing demand for faster order fulfilment and greater value on the one hand, with rising staff costs on the other.”

Crystal Parrott, vice president of Dematic’s Robotics Centre of Excellence, backs this up: “The rapid expansion of e-commerce and the shift to single-item picking has placed huge pressure on traditional labour-intensive picking operations. Critically, this is being compounded by a growing shortage of available labour. Fulfilment efficiency and accuracy are being impacted, but luckily, robotics and its supporting technology is developing fast and now offers a wide range of flexible and scalable solutions that can be configured to meet a variety of needs, from large to micro DCs.

“There are a growing number of solutions that are becoming available,” Parrott continues. “Businesses are going to have to start looking at automation in order to get the productivity levels necessary to deliver to customer expectations. It’s this dynamic shift from big-box consignments to individual items, the sheer number of product types, along with ‘instant’ one-hour delivery that is really propelling the need for different robotic solution sets. The most significant innovations have been in the computational and analytical methods associated with advanced AI. These advances enable robots to fast-plan and auto-navigate, whilst taking in sensory data, enabling them to move dynamically and be safe in the environment. The ability to compute all that data simultaneously with multi-threading operations, is allowing big breakthroughs.”

Edward Hutchison, managing director of BITO Storage Systems, adds to this: “Manufacturers will invest in automation technology to gain a competitive edge and meet the challenge of rising labour costs, shortening order lead times and meeting high service levels. Automation can be a leveller for smaller operations and can often be a more palatable solution than throwing people at a challenge.

“For many, however, the capital expenditure required, and lack of flexibility, is often a barrier to taking this step,” he continues. “Overcoming this barrier requires a flexible, affordable, simple, yet productive solution. An internal driverless transport system – essentially simple robots travelling around a warehouse – is a good example of a solution that does not require complex infrastructure and software, but does offer flexible, future-proof and productive intralogistics for manufacturers.”

Ward further elaborates on the financial question: “It is not just the rising cost of human labour that is making automation a more attractive option. Traditionally, automated handling technology has required a relatively high level of investment over an extended period of time before it has secured a return. This has largely been at odds with the shifting client base of many third-party logistics providers, but there are signs that the third-party logistics (3PL)/client relationship is changing. The traditional reluctance to invest in automation results from 3PL contract durations of, typically, three years, by which time any return on investment in an automated system would only just be starting to become manifest.

“As automation’s advocates will readily agree, there are compelling arguments to be made for the use of some form of automation within most 3PL operations but, of course, before taking the plunge and deploying such technology, most companies will want some assurances that their investment will deliver a return.”

Key considerations

Commenting on the key aspects companies need to consider when looking to invest and implement new technologies into their operations, Parrott explains: “The first one is the level of automation needed to meet their operational needs. You want to be able to add automation where you are going to gain the highest efficiency improvements – and there are differences between addressing an existing facility or a new one. So you need to take a look at what level of automation is required to meet the needs, then select the solution to fulfil that need. You must also look at the maturity of the technology, because that will determine whether or not you start small and then scale up later, or whether you just mass implement.

“The operational requirements for companies differ according to the vertical market.” Parrott continues. “The solutions and the capacity needs are usually very different. So you want to select the robotic solution that works for the vertical. Presently, the technology cannot support every SKU type for random picking, placing or transport – but that doesn’t mean that you shouldn’t adopt robotic solutions now, because you can get big benefits – it just means you should look ahead and apply the latest technology when it becomes available. Every application is unique. The enabling technologies may be common, but the actual solution may be varied.”

Farr expands on the variation in solutions. “There are numerous technology approaches – such as simply robotising a standard forklift by adding a computer – and these are coupled to multiple ways of providing interaction,” he says. “The issue revolves around these multiple possibilities. There isn’t just one standard way of linking to other systems. You will see SAP, FTP file-exchange sites, SQL databases and even XML via website portals. This variety compounds the issues even when you use bespoke APIs. Hardware and software choice can also complicate things. Trucks needs Wi-Fi, but if you try to run this in parallel with in existing warehouse Wi-Fi infrastructures, you can end up creating more problems than you solve due to signal degradation. Ideally you would exploit existing systems, but then the issue of security arises, adding another challenge to the pot.

“The goalposts are forever moving,” Farr adds, “but the technology is there, it is just the cost and complexity of integration into existing systems that people perceive as outweighing the benefits. We have a system called Yale Vision – a device we can fit on any vehicle (not just Yale vehicles), which can be used to track assets. So as well as controlling access to vehicles and logging important parameters (such as service records, driver license validity, etc.) you can also upload information to a portal to monitor vehicles remotely.

“There is an awful lot of data to be captured,” he concludes. “What is more important is the intuitiveness of the whole system. The data has to have value! But if you have to trawl it to do anything useful, it wastes time. Dashboards delivering quick views, such as KPIs, alerts, equipment performance and license expiration certainly make life easier. Operators want a snap shot, with the added ability to drill down if they need to. This is part of the MO behind Yale Vision.”

It’s not all doom and gloom. The technology is certainly there, as are the suppliers willing to help. Almost every application will be bespoke, but as Peter Ward explained, automation and robotics are coming and you ignore them at your peril. You don’t need to start off big. Start small, fine tune, realise the benefits and then scale up or expand. And do it now! The market won’t wait for you.