The dilemma faced by many batch‐manufacturing operations is the trade‐off between reducing lead times and manufacturing throughput. Using Little’s Law and the theory‐of‐constraints analysis, the authors have developed a methodology to optimise such dilemmas. The solution to this problem is to find the point in the operation of the plant where throughput is maintained at acceptable levels, but the lead time through the plant is maintained at or near a minimum. At such a point, the optimum level of work in progress (WIP) will be obtained. Such principles have been applied in this research project to a metals manufacturer. The difficulty with this case study is that complexity of the product mix and manufacturing flow renders simple analysis incomplete. By utilising a discrete event simulation of the manufacturing facility, we have been able to identify bottlenecks within the plant. From here we have developed a tool that automatically predicts the optimum level of WIP, depending upon such parameters as product mix and batch sizes. The results show significant improvement over the current practices, and over maintaining a constant WIP level. The results highlight the power of the constraint principles, and the value in evaluating and choosing the best methods for managing change through simulation.
Gunn, B. and Nahavandi, S. (2000), "Determining the optimum level of work in progress using constraint analysis and computer simulation", Assembly Automation, Vol. 20 No. 4, pp. 305-312. https://doi.org/10.1108/01445150010353233Download as .RIS
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