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Recognizing malfunctions in an ongoing process and providing reliable prognoses…

….that is the aim of the „operational performance support” concept, the usage scenarios and benefits of which are explained in theory and practice by Prof. Scheer in the fifth chapter of his book.

When speaking here of „post mortem“ processes, feeling a certain degree of discomfort cannot be ruled out. But the phrase sounds more fatal in meaning than it is intended to be. It has much more to do with the fact that processes are usually looked at and analysed in the “rear-view mirror” after they have run – ideally via the best-practice approach of process mining, as described in Chapter 4 (link here to Blog 4) of the book. One learns from the analysis and, where appropriate, optimizes processes or entire process chains in order to look at them once again in the rear view mirror – the “post mortem”. In many cases this makes sense on a continuing basis. If, however, individual process instances, such as in the manufacturing process, run in a matter of seconds and malfunctions that occur call into question the entire production process and, as a consequence, the quality of the product, then other solutions are required and in the meantime have become possible.

Buch von August-Wilhelm Scheer

Modern sensors connected with technologies for the evaluation of big data make it possible to attach key performance indicators (KPIs) to individual process instances (for example the continuously repeating 60 second welding procedure on a vehicle component) and to then monitor this mini process. Multiple sensors which are needed anyway for industry 4.0 production processes make this possible. The value added by real-time evaluation lies not only in the ability to intervene immediately in case of error, but the data also makes possible further important prognoses – about the condition of the welding apparatus as well as for its optimal use and thereby also the optimal result; in this case the welded seam. Operational process support does not therefore place its focus on the entirety of a complex process chain, but on the continual evaluation of mini and micro processes during operations. This represents a significant advance in the optimization of quality, not only in production, but everywhere where usable data is created, and also in the service sector.

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