Dynamical multi-parameter sizing of DDMRP buffers in finite capacity flow-shops
The DDMRP (Demand Driven Material Requirements Planning) methodology uses buffer stocks to (i) maintain a high level of service, (ii) stop the spread of uncertainty and (iii) adapt to market changes. According to theory, the size of these buffer stocks should be defined regularly. This sizing involv...
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| Published in | Computers & industrial engineering Vol. 175; p. 108858 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.01.2023
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0360-8352 1879-0550 1879-0550 |
| DOI | 10.1016/j.cie.2022.108858 |
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| Abstract | The DDMRP (Demand Driven Material Requirements Planning) methodology uses buffer stocks to (i) maintain a high level of service, (ii) stop the spread of uncertainty and (iii) adapt to market changes. According to theory, the size of these buffer stocks should be defined regularly. This sizing involves several parameters and policies to update them, but very little information is available on this subject. We aim to help practitioners choose sizing policies, while maximizing the performance of a given workshop. We have developed an experimental design to compare many combinations of flow-shops and bottleneck constraints, taken from industrial use-cases, and using discrete event simulation. The results show that (i) different degrees of dynamism are needed depending on the performance metric chosen by practitioners, (ii) completely dynamic control does not systematically lead to better performance, and (iii) contrary to what the existing literature on DDMRP suggests, varying buffer sizes may be less effective than fixed ones for an important part of use-cases.
•Multiple dynamic parameter setting for DDMRP is only useful in specific situations.•Constant buffer sizes in DDMRP are also efficient in many situations.•We provide alternative functions to update the DDMRP buffers if necessary.•The results are backed by significance studies of the effects. |
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| AbstractList | The DDMRP (Demand Driven Material Requirements Planning) methodology uses buffer stocks to (i) maintain a high level of service, (ii) stop the spread of uncertainty and (iii) adapt to market changes. According to theory, the size of these buffer stocks should be defined regularly. This sizing involves several parameters and policies to update them, but very little information is available on this subject. We aim to help practitioners choose sizing policies, while maximizing the performance of a given workshop. We have developed an experimental design to compare many combinations of flow-shops and bottleneck constraints, taken from industrial use-cases, and using discrete event simulation. The results show that (i) different degrees of dynamism are needed depending on the performance metric chosen by practitioners, (ii) completely dynamic control does not systematically lead to better performance, and (iii) contrary to what the existing literature on DDMRP suggests, varying buffer sizes may be less effective than fixed ones for an important part of use-cases. The DDMRP (Demand Driven Material Requirements Planning) methodology uses buffer stocks to (i) maintain a high level of service, (ii) stop the spread of uncertainty and (iii) adapt to market changes. According to theory, the size of these buffer stocks should be defined regularly. This sizing involves several parameters and policies to update them, but very little information is available on this subject. We aim to help practitioners choose sizing policies, while maximizing the performance of a given workshop. We have developed an experimental design to compare many combinations of flow-shops and bottleneck constraints, taken from industrial use-cases, and using discrete event simulation. The results show that (i) different degrees of dynamism are needed depending on the performance metric chosen by practitioners, (ii) completely dynamic control does not systematically lead to better performance, and (iii) contrary to what the existing literature on DDMRP suggests, varying buffer sizes may be less effective than fixed ones for an important part of use-cases. •Multiple dynamic parameter setting for DDMRP is only useful in specific situations.•Constant buffer sizes in DDMRP are also efficient in many situations.•We provide alternative functions to update the DDMRP buffers if necessary.•The results are backed by significance studies of the effects. |
| ArticleNumber | 108858 |
| Author | Lauras, Matthieu Baptiste, Pierre Martin, Guillaume |
| Author_xml | – sequence: 1 givenname: Guillaume orcidid: 0000-0002-3588-9132 surname: Martin fullname: Martin, Guillaume email: gmartin@mines-albi.fr organization: Centre Génie Industriel IMT Mines Albi, Albi, France – sequence: 2 givenname: Matthieu surname: Lauras fullname: Lauras, Matthieu organization: Centre Génie Industriel IMT Mines Albi, Albi, France – sequence: 3 givenname: Pierre surname: Baptiste fullname: Baptiste, Pierre organization: Polytechnique Montréal, Montréal, Canada |
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| Cites_doi | 10.1016/j.ijpe.2007.02.005 10.1080/00207543.2018.1464230 10.1016/j.cie.2013.04.013 10.1016/S0925-5273(98)00016-4 10.1080/002075497195498 10.1016/j.ejor.2005.03.015 10.1198/000313006X118430 10.1155/2019/6496309 10.3926/jiem.2654 10.1287/opre.9.3.383 10.24846/v22i3y201302 10.1016/j.arcontrol.2007.02.007 10.1287/mnsc.40.12.1678 10.1108/eb054675 10.1080/002075498193750 10.3926/jiem.3331 10.1287/mnsc.33.1.95 10.1080/00207549008942735 10.1080/00207540802603759 10.1007/s00170-008-1462-0 10.1016/j.ijpe.2015.07.030 |
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| Keywords | Flow shop Discrete event simulation Dynamical sizing DDMRP Demand driven materials requirement planning |
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| SubjectTerms | DDMRP Demand driven materials requirement planning Discrete event simulation Dynamical sizing Engineering Sciences Flow shop |
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