A simheuristic approach for throughput maximization of asynchronous buffered stochastic mixed-model assembly lines

Abstract

Mixed-model assembly lines are large scale production layouts that often operate under uncertainties such as stochastic product sequences. Balancing such lines can be particularly challenging as throughput estimation can be difficult to determine, especially when asynchronous pace and buffers are considered. Recent works have addressed problem variants with a given target throughput, but few authors consider a variant of the throughput maximization of mixed-model assembly line balancing problem. This paper addresses the balancing optimization problem for an assembly line with a given number of workstations and buffers between them. A make-to-order environment is considered, modeled as stochastic sequence of products with known demand rates. A novel specialized cycle time simulator (CTS) is introduced, as well as a simheuristic approach (PSH) that exploits CTS to assess the cycle time of an assembly line and provide good balancing solutions. The proposed simheuristic PSH is applied to a dataset with several buffer layouts, and its solutions are then compared to those of literature benchmarks. Performance comparisons show that PSH’s solutions outperform the benchmarks’ ones, with statistically significant differences. Furthermore, the solution quality difference was greater for instances with more buffers, highlighting PSH capacity to conveniently exploit buffers in assembly lines. Lastly, analyses on the average processing times of stations, obtained for each buffer layout, partially verifies and question established results of the “bowl phenomenon” on unpaced assembly lines.