Discrete event simulation approach considering scalable systems and non-expert users in the early phase of production planning for electric powertrains

Abstract

Electric vehicles will gain a significant market share within the next decade. Therefore, the automotive industry faces challenges regarding increasing number of units as well as technology uncertainty. To address these challenges production systems have to be developed that provide volume flexibility and reduce cost. It is essential to provide companies with planning methods that have the ability to assess manufacturing systems in a short time to react quickly in this disruptive environment. In this paper, we argue that through the use of discrete event simulation in an early phase, planning time can be reduced and the output quality increased. Conventional approaches focus mostly on the further improvement of existing manufacturing lines for a low uncertainty in production volume. The simulation of scalable production systems in the early phase requires a fully variable control between different modules. These modules have to be parametrical because of new technologies in the environment of electric mobility and the associated unsecure input data. Due to the high amount of scenarios production planners without simulation expertise have to be able to use the method. In this paper a method is proposed that uses predefined models to configure the scope of an assessment as well as to determine the required data. Preprogrammed modules are used to analyze the scalable concept of a manufacturing line efficiently. An application shows that the required accuracy can be achieved in a shorter time than using conventional methods.