Predictive Maintenance 4.0

Predict the unpredictable

Predictive maintenance is surely one of the most talked-about topics in maintenance and asset management. In order to find out where companies currently stand regarding predictive maintenance, and where they plan to be in the near future, we surveyed 280 companies in Belgium, Germany and the Netherlands.

In order to assess current practices, we have used a framework that identifies four levels of maturity in predictive maintenance. As companies move through these levels, there is an increase in how much data they use to predict failures. Level four involves applying the power of machine learning techniques to identify meaningful patterns in vast amounts of data and generate new, actionable insights for improving asset availability. We call this Predictive Maintenance 4.0, or PdM 4.0.

PdM 4.0 offers you the potential to predict failures that had been unpredictable up to now.

The potential of predictive maintenance with big data is enormous

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Key findings

We found that two thirds of survey respondents are still at maturity levels one or two. Only 11% have already achieved level four. The resources, capabilities and tools respondents use match their maturity levels: skilled technicians, standard software tools and maintenance logs play a dominant role in their current predictive maintenance processes.

But we also found that respondents are quite ambitious about improving their predictive maintenance maturity. Around one in three companies plan to be using PdM 4.0 in some form within five years, provided they can successfully implement it. The potential of PdM 4.0 is widely recognized.

Uptime improvement is the main reason why respondents have plans for PdM 4.0. Other important reasons relate to other traditional value drivers in maintenance and asset management such as cost reductions, lifetime extension for aging assets and the reduction of safety, health, environment and quality risks.

Successful PdM 4.0 implementation

To successfully implement PdM 4.0 you will have to take both technical and organisational aspects into account. The report presents a framework for the step-by-step implementation of the technical core of a PdM 4.0 model, in a way that contributes tot business strategy.

Organisational aspects are also important if PdM 4.0 is to be successful. We have focused on two such aspects: building skills and capabilities needed for PdM 4.0, and building a digital culture. A culture where everyone from the boardroom to the shop floor understands the power of data analytics. Companies with a robust digital culture possess the confidence and ambition to become increasingly data-driven in their decision-making.