Linking Discrete-Event Simulation with Artificial Intelligence: A Literature-Based Analysis of Existing Approaches in the Context of Manufacturing Planning and Control

Abstract

Although discrete-event simulation (DES) can successfully support the clarification of various issues in manufacturing, it is also subject to some limitations in practical applications. With the help of artificial intelligence (AI) some of these limitations may be overcome. The aim of this paper is to give a systematic overview of method combinations of DES and AI implemented in the context of manufacturing planning and control. For this purpose, a systematic literature review was conducted. The evaluation shows that there are five different approaches to combine DES and AI methods. On the one hand, DES can be used to test or train AI systems. On the other hand, AI is used to control, optimize, and analyze DES models of manufacturing systems. These combinations have been used, for example, to solve planning, decision-making, and assignment problems. The approaches found were analyzed and systematized in terms of the decision problems considered, the type of combination and the AI methods used. The results provide a basis for deciding which approaches can be applied best to a planning problem in the context of manufacturing.

Authors 2

1. Verena Nitsch Aachen Institute of Industrial Engineering and Ergonomics

   RWTH Aachen University

   Affiliation as printed

   Institute of Industrial Engineering and Ergonomics, RWTH Aachen University,Aachen,Germany

   Institute of Industrial Engineering and Ergonomics, RWTH Aachen University, Aachen, Germany

2. Susanne Mütze‐Niewöhner Aachen Institute of Industrial Engineering and Ergonomics

   RWTH Aachen University

   Affiliation as printed

   Institute of Industrial Engineering and Ergonomics, RWTH Aachen University,Aachen,Germany

   Institute of Industrial Engineering and Ergonomics, RWTH Aachen University, Aachen, Germany