Guide to the development of predictive maintenance systems

A few years and decades ago, predictive maintenance systems only seemed possible in science fiction movies. Thanks to improved and cheaper sensor, transmission and data storage technology, predictive maintenance of production processes is already a reality in some industries today and shows high potentials in the context of Industry 4.0.

Guidelines for action developed

Today, companies should be able to independently develop and offer predictive maintenance systems and services. For this purpose, the Department of Corporate Development of the Chair of Production Systems at the Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University has developed a generic action guideline in cooperation with various series producers and toolmaking companies. For the successful application of predictive maintenance, a close and cooperative collaboration between series producers and tool making companies is indispensable in order to synergistically combine the advantages of tool and process knowledge in series production. The target group of the guide includes in particular companies that increasingly experience tool-related failures in their series production due to repeated unforeseen disturbances. Predictive maintenance can help them to forecast malfunctions such as tool failure and to derive concrete measures based on this. For toolmaking companies, this offers the opportunity to expand their existing service portfolio with predictive maintenance solutions in order to significantly increase customer benefits over the entire life cycle of the tool and to open up additional business areas.

Procedure for company-specific implementation

Predictive maintenance is based on the collection, transmission, storage and near-real-time utilization of extensive amounts of data. Based on complex analysis methods and algorithms, deviations in the recorded operating parameters of a machine-tool system can be identified and necessary maintenance can be anticipated. Since both the technical implementation and the embedding of the technical solutions in the existing product and service portfolio often represent major challenges for series producers and toolmaking companies, the guideline is based on a comprehensive study which, in addition to concrete research results, is also based on expert knowledge from the participating partners from industry. The generic guideline presents a systematic procedure for the development of predictive maintenance solutions in three phases with a total of six steps. In the analysis phase, all relevant prerequisites and requirements for a predictive maintenance solution are first recorded. In the design phase, these are transferred into tool-, infrastructure- and service-related solutions. Finally, in the implementation phase, the algorithm is put into operation, trained, and interaction points and workflows are defined.

Increase machine availability

The results of the study show that the use of a predictive maintenance solution offers great potential for increasing machine availability. This potential lies in particular in a significant reduction of unplanned downtime with a simultaneous reduction of maintenance costs through better plannable, condition-based maintenance in series production. By providing corresponding services, toolmaking companies have the opportunity to expand their range of products and services, to effectively differentiate themselves from the competition and to increase their profitability. Through the cooperative development of predictive maintenance solutions, both sides can benefit equally from the corresponding service concepts.