Production scheduling in a process and assembly job shop

Abstract

In this paper, the problem of scheduling jobs with processing and assembly requirements in a job shop is addressed. Each job has a product structure of components and subassemblies that mate together to build up the end product. Each component or subassembly may also require additional processing before it can be assembled to its parent part. This paper models the problem using a mathematical programming approach under two production strategies. In one strategy, batches of identical items required by different end productsare aggregated together for production to take advantage of setup time reduction. In another strategy, no such aggregation is undertaken. A heuristic algorithm was developed to address the problem. To test model behaviour, some test prob lems were run for system analysis. Results from the test problems indicate that batch aggregation inhibits job flow when setup times are small and therefore worsens system performance. However, when the setup times are moderate to large relative to batch processing times, there is no performance dominance between the two strategies. The performance measure used in each case is production completion time. Results obtained also indicate that the heuristic algorithm is effective in solving the models based on solution quality and computational time requirement.