The New Fuzzy Bottleneck Model to Improve The Axle Manufacturing System Performance

Abstract

Axles are the crucial undercarriage part of vehicles and affect the total number of manufactured vehicles. Therefore, they are essential parts since they directly affect the production quantity. Some uncertainties arise in the lead times of the machining process in the manufacturing system due to the variability in factors, such as human, machine, and material properties. In this study, the efficiency of the axle manufacturing process is investigated, and performance in the machining unit of an automotive spare part manufacturer company is improved. This study aims to increase the production capacity of the company by using a fuzzy logic-based bottleneck analysis. In this study, a new model is proposed by integrating fuzzy logic the Solberg's bottleneck model, and the performance of the manufacturing system is improved by applying the developed model in the machining unit of the company. At the end of the study, the increase in production rate and the benefit to the company is obtained.