This paper addresses the problem of capacity estimation of a multi-product production line composed of m unreliable workstations and (m − 1) intermediate buffers. A simulation-based experimental design methodology is proposed to improve the performance of this flexible production line, which is expressed as the cycle time. The modelling approach integrates, in a more representative manner, the many parameters that impact the capacity of the manufacturing system. These are: workstation failure, repair, and set-up as product type changes. An experimental optimization to judiciously locate/allocate buffers between workstations is used to determine the maximum contribution of buffers on the overall performance of this serial manufacturing system. A case study is presented to show the modelling steps and to assess the contribution of each buffer. Analysis of the results shows the trade-offs between the different levels of buffers and the cycle time of the production line. The results present the percentage of workstations' operation, set-up downtime, blocking and starving. In addition, for each combination of buffer sizes, the bottleneck workstation is identified. Changing a buffer size impacts directly the cycle time and, in some cases, a new bottleneck workstation evolves. The results provide insights into the performance of the system, including detection of important interactions and critical parameters. Considering various design scenarios, our methodology helps to identify the best strategy of buffer location/allocation that ensures a minimum cycle time, while considering other criteria. This could be achieved with less experimental effort and the manager could make the selection of the best design scenario. An analysis of the dynamic behaviour of buffers and their effectiveness is also given and commented upon.
