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    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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Production Planning and Control in Multi-Stage Assembly Systems: An Assessment of Kanban, MRP, OPT (DBR) and DDMRP by Simulation

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Production Planning and Control in Multi-Stage Assembly Systems : An Assessment of Kanban, MRP, OPT (DBR) and DDMRP by Simulation. / Thurer, Matthias; Fernandes, Nuno Octavio; Stevenson, Mark.

In: International Journal of Production Research, Vol. 60, No. 3, 31.03.2022, p. 1036-1050.

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Thurer, Matthias ; Fernandes, Nuno Octavio ; Stevenson, Mark. / Production Planning and Control in Multi-Stage Assembly Systems : An Assessment of Kanban, MRP, OPT (DBR) and DDMRP by Simulation. In: International Journal of Production Research. 2022 ; Vol. 60, No. 3. pp. 1036-1050.

Bibtex

@article{a833be4330af4175b913de92c0aacd14,
title = "Production Planning and Control in Multi-Stage Assembly Systems: An Assessment of Kanban, MRP, OPT (DBR) and DDMRP by Simulation",
abstract = "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.",
keywords = "Production control, Kanban, MRP, Theory of constraints, Demand driven material requirements planning",
author = "Matthias Thurer and Fernandes, {Nuno Octavio} and Mark Stevenson",
note = "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",
year = "2022",
month = mar,
day = "31",
doi = "10.1080/00207543.2020.1849847",
language = "English",
volume = "60",
pages = "1036--1050",
journal = "International Journal of Production Research",
issn = "0020-7543",
publisher = "Taylor and Francis Ltd.",
number = "3",

}

RIS

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 -