Application of Process Mining in Automobile: A Case Study for MG Motors

Abstract

To gain competitive advantage, automobile shops try to streamline their processes. In order to do so, it is essential to have an accurate view of the “careflows” under consideration. In this paper, we apply process mining techniques to obtain meaningful knowledge about these flows, e.g., to discover typical paths followed by particular groups of Motor Cycles. This is a non-trivial task given the dynamic nature of automobile processes. The paper demonstrates the applicability of process mining using a real case of a Hero Honda Motor Cycle process in a MG Motors automobile company located at Chennai in India. Using a variety of process mining techniques, we analyzed the automobile process using the control flow perspective. In order to do so we extracted relevant event logs from the automobile shop information system and analyzed these logs using the ProM framework. The control flow perspective algorithm Heuristics Miner (HM) algorithm of the ProM and Weka Library were used to predict the knowledge from the automobile log. The results show that process mining can be used to provide new insights that facilitate the improvement of existing careflows.

Keywords: Process mining, careflows, automobile log, ProM framework, control flow, Weka, Knowledge.