Evaluation of setup time and batch size reduction plans for G. T. flow line workcells

Setup time and batch size reductions are often viewed as pathways leading to lower work-in-process (WIP) inventory levels and reduced manufacturing lead times. However, setup time and batch size reductions may not always yield such improvements because the increased workload due to the additional setups can lead to a deterioration of system performance.; In this research, we propose analytical models for the design and evaluation of reduction plans which incorporate setup time and batch size reductions in Group Technology (GT) flow line workcells.; A workload balancing model is presented to determine the required setup time reduction schemes for different levels of batch size reduction in order to maintain the cell's system stability and improve its performance. The model is based on balancing the flow line and limiting the workload at each workstation such that the reserved capacity constraint is satisfied.; To make rapid evaluation for reduction plans, we developed a regenerative theory-based analytical model to analyze the performance of flow line workcells. This regenerative model considers workstation skipping and simultaneous job services in the cellular manufacturing environment. The central modeling issue is to solve the average waiting time for the first transfer batch of each job.; To solve the average waiting time for the first transfer batches, we initially developed a regenerative model under the assumption that jobs coming to the cell follow a predetermined schedule. We used the techniques of regenerative method to solve the steady state probability for each of the determined cycles and the average number of jobs in a cycle. In conjunction with the inherent information in the regenerative cycles, we then solved the average waiting time for the first transfer batches.; We further extended our regenerative model to include the stochastic arrival process. We first derived a model, using Pollaczek's (1961) integral equations and double transform, to formulate the average number of jobs in a regenerative cycle. We then developed a numerical algorithm, based on the Pollaczek's (1965) formula, to solve the average waiting time for the first transfer batches.