Trends in Maintenance 4.0

An expert interview with Wim Vancauwenberghe

Maintenance 4.0 is transforming the way that organisations approach maintenance and reliability. In this expert interview we asked Wim Vancauwenberghe, director of BEMAS and coordinator of the Asset Performance 4.0 initiative, for his thoughts on the evolution of Maintenance 4.0 and on its broader implications for maintenance processes.

Over the years, new technologies and practices have emerged.  Do you view Industry 4.0 and Maintenance 4.0 to be a continuation of trends, or are we seeing fundamental changes in the O&M discipline?

In my view, maintenance 4.0 is a non-fundamental evolution that will fundamentally change maintenance. Since the Nowlan and Heap report was published in 1978, we know random failures are very common. When thinking about the right maintenance plan based on an RCM exercise, we find that, based on the failure behaviour, in many cases condition-based maintenance is the optimal maintenance strategy.

However, there is an important question in the decision diagram: is the condition inspection or monitoring technically and economically justifiable? In the past, that question often had to be answered negatively because of the human effort needed and the investment in CM technology. Today, thanks to the current digital innovations with affordable sensors, the internet of things, AI algorithms and predictive analytics, it is now possible and affordable to automate inspections.

The technical disruptions make it technically and economically justifiable to implement in many more cases condition-based maintenance. In other words, the fundamental principles of maintenance continue to apply, but the decision criteria have changed dramatically. That is why today many organisations switch to condition-based maintenance 4.0.

The industrial sector is in a period of unprecedented uncertainty. To what extent do you think that digitalisation will be part of the “next normal?”

We already lived in a VUCA-world* before Covid-19. Nowadays uncertainties and changes pop up even faster. On the production floor this translates into more flexibility, faster product innovations and increasingly smaller production batches. In other words, there is an increasing need for a quickly adjustable and adaptable production equipment. In such a complex operational context, it is impossible to set up a flexible and reliable production without the proper digital tools. That is why digitization will indeed be an integral part of the next normal. At the same time, manufacturing companies are being forced to work very cost-efficiently, and maintenance 4.0 can prevent unnecessary maintenance and expensive failures, which of course offers a competitive advantage.

*Volatile, Uncertain, Complex and Ambiguous

Do you think AI for Industrial Analytics and Remote Monitoring will be integral to plants’ future plans?  How will this impact the role of plant level O&M employees?

AI and Industrial Analytics will not only be part of factories in the future, but already are part of factories today. Market estimates claim that by the end of 2020 up to 50% of the connectable factory assets will be somehow connected to a data collection system. Remote monitoring and predictive maintenance is use case number one.

When looking at maintenance employees, there are quite a few important things that have an impact. First of all, by seeing failures earlier and predicting them, there is now enough time to (also) prepare breakdown maintenance. As a result, the intervention itself can be scheduled at a more convenient time without pressure from operations, with a positive impact on downtime, job efficiency and safety.  Secondly, due to the fact that AI and Remote Monitoring enable the elimination of unnecessary preventive maintenance tasks, an organisation may require a fewer number of technicians than today.

Finally, intervention quality becomes of the utmost importance. There is no point in having a sophisticated system predicting failures and at the same time execute low quality interventions. In this scenario, a next failure is already developing as soon as you press the start button. In fact, by estimating remaining useful life based on asset performance after an intervention, predictive maintenance algorithms could also be used to check intervention quality. It will quickly become clear which technicians carry out qualitative interventions and which technicians need training.  In the new normal technician skills and competencies become even more important.  And in a digitized production environment, it is obvious that the technical team should also have a broad set of digital competencies.

Some OEMs are moving to a Hardware as a Service model.  Going forward, do you foresee changes in the role and/or business models of OEM’s servicing plants?

It is logical that the servitization trend makes OEMs think fundamentally about how they maintain and service the assets made available to their customers. Where there used to be a drive to sell more service in order to make more profit, in the servitization model there now is a drive to do as little service as possible, without of course undermining the guaranteed asset performance. In such a way of thinking, OEM’s are encouraged to invest in fundamental equipment reliability, remote monitoring and predictive analytics.

In the last couple of years, many Maintenance 4.0 initiatives have been stuck in so-called “pilot purgatory.”  As companies move to a more agile approach, do you think it will accelerate or slow the adoption of new initiatives and programs that support digitalization?

A pilot phase allows to get a feeling of the possibilities of the new technologies entering the market. In addition, such a pilot is often applied to ‘low hanging fruit’ cases where the investment in maintenance 4.0 quickly pays for itself through lower maintenance costs and higher availability. That’s why I feel pilots make sense in many cases.

There is however a big gap between such a pilot and a large-scale rollout of a technology throughout a wide array of applications, because many pilot projects are developed and implemented for a very specific application. The results are great, but each dedicated application needs considerable dedicated efforts. This makes many asset owners currently waiting for a ‘killer application’ that can be easily deployed across a wide variety of assets and applications.

I guess that it might take some time before this type of technology will be readily available. On the other hand, it does not seem wise to wait too long to deepen and broaden maintenance 4.0, because the return on investment is already there with the current solutions on the market.

How do plants facing significant short-term challenges (e.g., supply chain disruptions, fluctuations in demand) balance these challenges yet continue to invest in long-term initiatives?

Just as it took in recent years a leap of faith to start investing in reliability and maintenance in order to achieve optimal cost performance of your equipment, it also requires today a fundamental belief in the added value of digitization in maintenance in order to be and stay competitive in the near future. That belief can move mountains and help to come up with creative solutions enabling investments even in times of economic turmoil.

There are several areas of Maintenance 4.0 including AI, robotics, 3D printing of spare parts. What areas will become the highest priority within plants’ solutions roadmaps?

The highest priority will be where the highest profits can be made. This can be in terms of availability and costs, but also in terms of safety and sustainability. That profit/application will strongly depend on the environment and the type of assets. My feeling is that AI algorithms are widely applicable in many industries. Moreover, AI algorithms not only impact maintenance costs and reliability, but also product quality, energy consumption and production yield. As a result of this multiplier effect, they are often at the top of the list of priorities. However, this does not detract from the fact that in hazardous environments, for example, it is very sensible to use robots to carry out dangerous inspections or maintenance jobs that require a lot of preparation. In locations far away from normal industrial supply chains, it is undoubtedly wise to first invest in 3D printing of spare parts. So all Maintenance 4.0 technologies can figure on top of the priority list at some point…

Wim Vancauwenberghe is director of BEMAS, the Belgian Maintenance Association since 2000. He holds a master’s degree in industrial engineering, is Certified Maintenance & Reliability Professional (CMRP) and Technician (CMRT) by SMRP and Certified Reliability Leader by the Association of Asset Management Professionals. Through his activities in the European Federation National Maintenance Societies (EFNMS) and in the Global Forum of Maintenance and Asset Management Societies, Wim has the privilege to meet world’s most advanced thought leaders in the field of maintenance & asset management. Having a keen interest in Maintenance 4.0, safe maintenance and skill & competency development, Wim was and is also involved in several international and local projects in the field of maintenance.

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