Philips

Read what IRP Delft accomplished!

Predictive Maintenance

Philips Innovation Services (PInS) creates the bridge from idea to market for each innovation journey.  During the summer, the team worked in the Manufacturing Systems & Industry 4.0 department at PInS which builds scalable manufacturing solutions for its clients. The team developed a roadmap presenting all the technical steps to take and developed the business model to offer predictive maintenance as a service to clients.

Approach

The team started by dividing the problem into two parts: a study of potential business models for predictive maintenance and a roadmap for its technical development. For the business models, the team started by researching what options were available in the market already,  through literature research and interviews with knowledgeable people at Philips. Then, the maintenance options available at Philips Innovation Services were studied to understand what business models of predictive maintenance could be added in an incremental and accessible way. On the technical part, the team first conducted a literature review on the requirements for developing predictive maintenance as a service, making an overview of the associated development processes and the required expertise. Using the results of the literature review, the team defined a generalised approach for the development of a predictive maintenance service for future products of Philips Innovation Services. This approach was fine-tuned during a limited case study involving a production machine that is under development at Philips Innovation Services.

Results

As a result, the team was able to present to Philips Innovation Services a market research on predictive maintenance in the industry, three different business models to offer predictive maintenance to clients and a roadmap with all the specific steps to implement and use predictive maintenance on any machine. It was also made clear not only the advantages of implementing predictive maintenance but also the biggest challenges that come with it.

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