Statistical process monitoring by using process mining

Abstract

There is well known: whether the advantage of using a normal process model to monitor the stability of a manufacturing process can be gained lies in the model's ability used to realize its conformance to the manufacturing process trend. In other words, whether a manufacturing process can be stabilized depends on how much is about the conformance level between its processing trend and the norm regulated in the process model. Once there are differences between a normalized process model and a manufacturing process, it will have some interesting situations that are worthy to be investigated. In this paper, a process conformance technique discussed in process mining field will be newly applied to accomplish such the investigation. This technique will consider statistical process control (SPC) trending charts as the norms of normalized processes so to experimentally estimate and examine the conformance level between the SPC norms and a statistically generated manufacture running process, hereby to see how the proposed process conformance approach is to the stability of the simulated manufacturing process.