Optimisation of an Order Picking System Using Simulation Software in the Chemical Industry

Purpose: Manual order picking is one of the most costly and labour-intensive processes in logistics. In order to avoid planning errors and the resulting costs, detailed knowledge about the performance of the order picking system is crucial. Therefore, this study aims to demonstrate the suitability of discrete event simulation for determining the performance of an order picking system. Furthermore, it is investigated whether optimisations can be derived from the simulation model to increase performance. Methodology: The research gap was identified through a systematic literature review. The process software ‘Process Simulator’ was used to analyse a case study in the chemical industry. Findings: No research has been published analysing the maximum performance of a complex picking system with many process steps. This study fills this research gap. The results of the study demonstrate that it is possible to adequately model complex processes in the ‘Process Simulator’ software and to derive appropriate adjustments for different simulation scenarios. Both the process model and the simulation software were found to be effective tools for determining the maximum performance of an order picking system. Process simulation has the potential to improve the performance of order picking systems through ‘what-if’ simulations. This study extends the research by using ‘Process Simulator’ software and considering the characteristics of the process industry. Moreover, it provides practitioners with a process model and success factors to support the implementation of the approach, thereby increasing the likelihood of successful implementation.