Throughput accounting and performance of a manufacturing company under stochastic demand and scrap rates

Theory of constraints (TOC) has emerged as an effective management philosophy suggesting practical solutions to various complex problems including product mix problem. Scholars have shown the superiority of various optimization (and artificial intelligence) approaches over the TOC-based heuristic to a "static" product mix problem, but have failed to see TOC as a whole, i.e. to take into consideration the impact of resource inter-dependencies, feedback loops, and importantly, statistical fluctuations ever present in any dynamic business environment. We proposed a system dynamics (SD) based simulation model to investigate product-mix problem under stochastic demand and scrap rates. We analyzed various scenarios by employing the drum-buffer-rope approach and constraint focused systematic scrap rate reduction approach, and importantly, evaluating performance using throughput accounting based global measures such as throughput and inventory. We conclude this paper by suggesting that future research efforts should be directed to develop an enabling hybrid expert simulation system to learn fundamental and powerful concepts underlying the theory of constraints. Develops simulation model from original PQ company example.Modeled uncertainty leads in both product mix scenarios to significant losses.Scrap production should not be analyzed in isolation, but to ensure material flow.Preference on product Q leads to lower performance in nearly all measures.Scrap production is troublesome preferring product P due to higher volume.