Framework for the integration of Process Mining into Life Cycle Assessment

Abstract

An increasing product variance, shorter life cycles and the integration of new products and technologies into existing factories lead to a high complexity in today’s production systems. This makes it difficult to carry out Life Cycle Assessments (LCA) continuously and effectively. Major challenges of LCA are on the one hand a high expenditure of time and on the other hand a static evaluation of individual products. In order to perform dynamic and continuous process analyses, companies increasingly rely on new technologies and methods. Numerous studies have already been able to tap promising potentials by using Process Mining (PM). In contrast to traditional methods of process modeling, PM uses event log data to model the actual production processes. Based on this data, a real-time model is built to identify waste. In a holistic approach, PM is able to automatically uncover social and organizational networks and map them in a simulation model. According to the current state of research, there is no concept for integrating PM into LCA. Therefore, the present work focuses on the investigation of interfaces between PM and LCA in order to systematically identify and evaluate the potentials of using PM. The results are applied to a use case in the sector of commercial vehicles.