Process Mining in Dyeing Unit Using Control Flow Perspective:A Case Study

To gain competitive advantage, dyeing units are trying to streamline their processes. In order to do so, it is essential to have an accurate view of the “control flows” under consideration. In this paper, it is applied the process mining techniques to obtain meaningful knowledge about these flows that is for example to discover typical paths followed by particular group of colors. This is a non-trivial task given the dynamic nature of dyeing unit processes.
So, every process in the dyeing is stored in the form of event logs to discover the new mining model. This paper demonstrates the applicability of process mining using a real case of a shade difference process in Emerald Dyeing Unit. The process mining techniques has different mining perspectives:(1) control flow perspective, (2) organizational perspective and (3) performance perspective. In this paper, it is analyzed that how control flow perspective was useful for the dyeing process and also to discover new methods for dyeing processing. To implement these perspectives, a ProM framework is used; it is a software tool for process mining. Hence, the new mined model shows that process mining can be used to provide new insights that facilitate the improvement of existing dyeing process colouring control flows.