Bottleneck improvement using simulation based optimization

Abstract: Manufacturing companies are constantly looking for new, innovative technologies andtools to find out the real constraints and bottlenecks that impede the performance oftheir production systems. There are several approaches and methods that have beendeveloping from decades to overcome these constraints of production processes butthey are not sufficient to pinpoint the exact location and its severity. They also generallyfall short to suggest the way to implement the right actions in the right order, to avoidsub-optimizations and wastes in time and expenses. So according to recent research inusing simulation based optimization, it is believed that some more accurate and efficientmethodology for supporting decision making in production systems development andimprovement is badly needed. SCORE (Simulation-based Constraint Removal) is apromising methodology for identifying and ranking the bottlenecks of productionsystems that utilizes simulation-based multi-objective optimization (SMO), which wasdeveloped by Pehrsson (2013) as a part of his PhD work. The main principle of thisnew methodology is the application of SMO with the objectives to maximize thethroughput and minimize the number of required improvement actions simultaneously.Additionally, by using post-optimality analysis to process the generated optimizationdataset, the precise improvement actions needed to attain a certain level of performanceof the production line are automatically put into a rank order. The main aim of thisproject is therefore to apply this new technique in a real-world context, in order tounderstand how far this technique will support for decision making, by conducting asimulation-based bottleneck analysis in one of the major Volvo group trucks facilities.This is to find out the bottlenecks and optimize it in order to increase the overallproductivity. Three research questions related to the effectiveness and accuracy of themethodology will be answered through this real-world application study.