Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 2 Dec 2020, available online: https://www.tandfonline.com/doi/abs/10.1080/00207543.2020.1849847
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Production Planning and Control in Multi-Stage Assembly Systems
T2 - An Assessment of Kanban, MRP, OPT (DBR) and DDMRP by Simulation
AU - Thurer, Matthias
AU - Fernandes, Nuno Octavio
AU - Stevenson, Mark
N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 2 Dec 2020, available online: https://www.tandfonline.com/doi/abs/10.1080/00207543.2020.1849847
PY - 2022/3/31
Y1 - 2022/3/31
N2 - Multi-stage assembly systems where the demand for components depends on the market-driven demand for end products, are commonly encountered in practice. Production Planning and Control (PPC) systems for this production context include Kanban, Materials Requirement Planning (MRP), Optimised Production Technology (OPT), and Demand Driven MRP (DDMRP). All four of these PPC systems are widely applied in practice and literature abounds on each of these systems. Yet, studies comparing these systems are scarce and remain largely inconclusive. In response, this study uses simulation to assess the performance of all four PPC systems under different levels of bottleneck severity and due date tightness. Results show that MRP performs the worst, which can be explained by the enforcement of production start dates. Meanwhile, Kanban and DDMRP perform the best if there is no bottleneck. If there is a bottleneck then DDMRP and OPT perform the best, with DDMRP realising lower inventory levels. If there is a severe bottleneck, then the performance results for DDMRP and OPT converge. This identification of contingency factors not only resolves some of the inconsistencies in the literature but also has important implications for the applicability of these four PPC systems in practice.
AB - Multi-stage assembly systems where the demand for components depends on the market-driven demand for end products, are commonly encountered in practice. Production Planning and Control (PPC) systems for this production context include Kanban, Materials Requirement Planning (MRP), Optimised Production Technology (OPT), and Demand Driven MRP (DDMRP). All four of these PPC systems are widely applied in practice and literature abounds on each of these systems. Yet, studies comparing these systems are scarce and remain largely inconclusive. In response, this study uses simulation to assess the performance of all four PPC systems under different levels of bottleneck severity and due date tightness. Results show that MRP performs the worst, which can be explained by the enforcement of production start dates. Meanwhile, Kanban and DDMRP perform the best if there is no bottleneck. If there is a bottleneck then DDMRP and OPT perform the best, with DDMRP realising lower inventory levels. If there is a severe bottleneck, then the performance results for DDMRP and OPT converge. This identification of contingency factors not only resolves some of the inconsistencies in the literature but also has important implications for the applicability of these four PPC systems in practice.
KW - Production control
KW - Kanban
KW - MRP
KW - Theory of constraints
KW - Demand driven material requirements planning
U2 - 10.1080/00207543.2020.1849847
DO - 10.1080/00207543.2020.1849847
M3 - Journal article
VL - 60
SP - 1036
EP - 1050
JO - International Journal of Production Research
JF - International Journal of Production Research
SN - 0020-7543
IS - 3
ER -