Developments in recent years have shown that the majority of industrial companies find themselves in a situation of cost and competitive pressure as well as a volatile environment. In order to be able to establish themselves here, the aim is to maximize logistics performance vis-à-vis customers and to minimize the costs incurred internally. These target figures can be measured on the basis of lead time and delivery reliability of orders on the one hand and the capacity utilization of operational machinery and the amount of stock in circulation in production on the other. The selection of the “right” production control method turns out to be an essential factor for the financial stability and success of industrial companies with regard to the above-mentioned key figures.
In this thesis, it was explained which production control methods have the greatest theoretical potential today and which results have already been achieved in scientific studies. The five methods KANBAN, POLCA, CONWIP, COBACABANA and LUMSCOR were discussed in more detail. In addition, a simulation experiment was set up based on the mechanical production of a medium-sized make-to-order company, which illustrates the effects of applying the described processes in relation to the aforementioned key figures.
Using an analysis of variance (ANOVA) based on the application of a Discrete Event Simulation, significant differences within and between the respective processes were identified. In general, the LUMSCOR (Lancaster University Management School Corrected Order Release) method achieved the best results in this case study. Accordingly, this production control method shows up to a 20% reduction in lead times and work in progress compared to the other methods considered. While delivery reliability can be maintained at a consistently high level of 96%, LUMSCOR is only outperformed by POLCA by half a percentage point in terms of machine utilization.