Analysis of Barrel Electroplating Line with Process Mining and Petri-Net Model

Abstract

Nowadays, many companies carry out efficiency studies to increase their profitability. The most important step in productivity studies is to objectively analyze the processes and identify the points that can be improved. Process mining shows the actual functioning within the process. It also identifies points of improvement such as bottlenecks, waiting times and deviations in the process. In this article, it is aimed to analyze the production process of the barrel electrolytic coating line with the process mining method. In order to perform the analysis, firstly, the data related to the production process was obtained from the ERP system in. csvformat. Within the scope of process mining, data obtained from the event log were used to analyze and visualize the processes affecting the coating line and to identify areas where improvements can be made. Process mining techniques were applied to the event log of the production identified after the electrolytic coating process. ProM 6.12, a widely used open source tool for process mining, was used to perform our analysis. After examining the in-line processes of the product produced in the electrolytic coating line, the data from the event logs were processed and analyzed with process discovery algorithms. In the literature, there has been no research to date on using a process mining perspective to detect anomalous flows in electrolytic coating production. © 2024 IEEE.