Predictive maintenance delivers on promises

Beyond the hype: PdM 4.0 brings improvements

Predictive maintenance 4.0, the use of data analysis to predict when, for example, an asset is in need of replacement, has been seen as the great promise of Industry 4.0 in the world of maintenance and asset management for some years. However, extensive research into concrete results was not yet available. This sometimes made companies reluctant to venture the investment and try the technology. Now those concrete results are there, and they are promising.

The PwC report Predictive Maintenance 4.0 - Beyond the hype: PdM 4.0 delivers results shows that 95% of the companies that use PdM 4.0 already achieve positive results. On average, they have achieved 9% more uptime. This is a fantastic result, because the cost of downtime - not being operational because assets break down or equipment fails - are extremely high. With the relatively limited investment needed to implement and execute PdM 4.0, a much higher return can be achieved. A small increase in uptime is already worth its weight in gold.

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PdM4.0 Predict the Unpredictable

More and more companies are thinking about predictive maintenance 4.0

Mainnovation specializes in maintenance and asset management and, together with PwC, conducted research for the second year in a row into the use of predictive maintenance at asset-intensive companies in the Netherlands, Belgium and Germany. Two important developments emerge from the study. Firstly, the number of companies that are in the process of implementing or planning to implement the technology is increasing further. In addition, almost all companies that already work with the technology at the highest level (PdM 4.0) see considerable results.

11% of the respondents are currently at level 4. This is the same percentage as in 2017, but there is still a development going on: 60% said they have concrete plans to implement PdM 4.0, compared to only 49% last year. Most companies that indicate that they do not have implementation plans yet, mention a lack of budget as their main reason. As a result, they cannot complete the business case.

Use of data characterizes highest level

The use of big data in the maintenance of assets and equipment characterizes the fourth level of maturity in predictive maintenance. The structure of the levels is as follows:

Level 1 - Visual inspections: periodic physical inspections; conclusions are based solely on inspector’s expertise.

Level 2 - Instrument inspections: periodic inspections; conclusions are based on a combination of inspector’s expertise and instrument read-outs.

Level 3 - Real-time condition monitoring: continuous real-time monitoring of assets, with alerts based on pre-established rules or critical levels.

Level 4 - PdM 4.0: continuous real-time monitoring of assets and external data (such as environmental and usage data), with alerts based on predictive techniques such as regression analysis, for at least one important asset.

Start small and become a PdM 4.0 champion as well

How can companies take the step to PdM 4.0? Start small. Firstly, create a pilot with the most business-critical asset. Also, consider whether it is easy to obtain data about that specific asset, because only then the asset is suitable for the pilot. With aged assets, you often see that this is not so easy.

The report also shows what PdM 4.0 champions, companies that already had the biggest successes with PdM 4.0, have in common. Successful common denominators are mainly the amount of external data (data not directly related to the asset itself) that is used, the use of sensors, good hardware and software and the use of data analysts and IT specialists.

Concrete examples need to convince companies to take the initiative

Besides making a comparison with last year's results, an important research objective was to map out concrete examples of successful use of predictive maintenance. Until now, the lack of examples has usually been the reason why companies have not dared to invest in the technology. We now have those examples. The Belgian infrastructure manager Infrabel is already way ahead in the field of PdM 4.0. Because fewer physical inspections along the tracks are now required, the company has improved the safety of its employees.

Collaboration PwC and Mainnovation

PwC and Mainnovation have been working together for several years now and have been conducting research into predictive maintenance 4.0 for the second consecutive year.

Mainnovation has all the expertise in the field of maintenance and asset management, and PwC in the field of data analysis and regulations. By entering into this partnership, we can really offer our customers the complete advice. Because the implementation of this technique involves, on the one hand, more technical questions such as "what is the most suitable asset to run a pilot?" and, on the other hand, questions such as "how do we unlock the data, who's actually owns the data, and how do we ensure that we comply with privacy rules?” Together we can strategically advise and guide our clients in the implementation of PdM 4.0.

Contact us

Bas Weber

Bas Weber

Partner, PwC Netherlands

Tel: +31 (0)61 037 60 45

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