BALANCING STOCHASTIC ASSEMBLY LINES USING CONSTRAINT PROGRAMMING AND QUEUEING NETWORKS

As an important component of flow type production systems, assembly lines are widely used from automotive, appliance to apparel industry. in this research, the aim is finding the optimum task assignment that minimizes the cycle time under the assumption that station quantities are constant which are described as type-2 assembly lines. stochastic assembly lines are considered in which task times are distributed according to a statistical distribution. a new algorithm which gives optimum solution using constraint programming and queuing network is proposed. in this algorithm, the possible combinations are determined by constraint programming, and then, the performance measures are evaluated by queuing network. the method is tested with several numerical experiments from literature and the applicability is confirmed.