A Hybrid Model to Support Decision Making in Manufacturing

In the context of Industry 4.0, the adoption of new technologies for process improvement purposes makes the environment more complex and sensitive. Process Mining (PM) is a technology that has been used to support these improvements. The same happens to Discrete Event Simulation (DES) that’s mainly used to analyze scenarios for decision-making. Further, Multicriteria Decision-Making (MCDM) methods are techniques to guide the scenarios’ choice, especially in such complex environments. By using a log database from a manufacturing process, this paper exemplifies the combination of these techniques (PM, simulation, and MCDM) in a small application to check their usefulness. Furthermore, it is based on a previous paper of Design Principles of Digital Twin (DP). This study is done by first reaching the process model using PM to feed simulation in Python to provide analysis of different scenarios. Finally, MCDM is used to check those scenarios and give an answer that best fits the current process’ constraints.