Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System

J.B.H.C. Didden; Quang-Vinh Dang; Ivo J.B.F. Adan

doi:10.1109/WSC57314.2022.10015489

Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System

J.B.H.C. Didden
, Quang-Vinh Dang
, Ivo J.B.F. Adan

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

2 Citaten (Scopus)

45 Downloads (Pure)

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Order release in High-Mix-Low-Volume machine environments is often difficult to control due to the high variety of these shops. This paper, therefore, proposes an extension to a Multi-Agent System to control order release. Intelligence is introduced to the agent that is responsible for order release to autonomously learn which jobs to release into the shop through the use of sequencing rules, depending on the current environment. The objective is to minimize the mean weighted tardiness of all jobs. Computational results show that the proposed sequencing rules outperform other more common dispatching rules in terms of mean weighted tardiness. Further analysis of the results also reveals that a more accurate prediction of the lead time of jobs can be made, which is one of the main interests of practitioners in High-Mix-Low- Volume environments.

Originele taal-2	Engels
Titel	Proceedings of the 2022 Winter Simulation Conference, WSC 2022
Redacteuren	B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C.G. Corlu, L.H. Lee, E.P. Chew, T. Roeder, P. Lendermann
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	1806-1817
Aantal pagina's	12
ISBN van elektronische versie	978-1-6654-7661-4
DOI's	https://doi.org/10.1109/WSC57314.2022.10015489
Status	Gepubliceerd - 23 jan. 2023
Evenement	2022 Winter Simulation Conference, WSC 2022: Reimagine Tomorrow - Singapore, Singapore Duur: 11 dec. 2022 → 14 dec. 2022 https://meetings.informs.org/wordpress/wsc2022/

Congres

Congres	2022 Winter Simulation Conference, WSC 2022
Land/Regio	Singapore
Stad	Singapore
Periode	11/12/22 → 14/12/22
Internet adres	https://meetings.informs.org/wordpress/wsc2022/

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10.1109/WSC57314.2022.10015489

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Didden, J. B. H. C., Dang, Q.-V., & Adan, I. J. B. F. (2023). Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System. In B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C. G. Corlu, L. H. Lee, E. P. Chew, T. Roeder, & P. Lendermann (editors), Proceedings of the 2022 Winter Simulation Conference, WSC 2022 (blz. 1806-1817). Artikel 10015489 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WSC57314.2022.10015489

Didden, J.B.H.C. ; Dang, Quang-Vinh ; Adan, Ivo J.B.F. / Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System. Proceedings of the 2022 Winter Simulation Conference, WSC 2022. redacteur / B. Feng ; G. Pedrielli ; Y. Peng ; S. Shashaani ; E. Song ; C.G. Corlu ; L.H. Lee ; E.P. Chew ; T. Roeder ; P. Lendermann. Institute of Electrical and Electronics Engineers, 2023. blz. 1806-1817

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title = "Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System",

abstract = "Order release in High-Mix-Low-Volume machine environments is often difficult to control due to the high variety of these shops. This paper, therefore, proposes an extension to a Multi-Agent System to control order release. Intelligence is introduced to the agent that is responsible for order release to autonomously learn which jobs to release into the shop through the use of sequencing rules, depending on the current environment. The objective is to minimize the mean weighted tardiness of all jobs. Computational results show that the proposed sequencing rules outperform other more common dispatching rules in terms of mean weighted tardiness. Further analysis of the results also reveals that a more accurate prediction of the lead time of jobs can be made, which is one of the main interests of practitioners in High-Mix-Low- Volume environments.",

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booktitle = "Proceedings of the 2022 Winter Simulation Conference, WSC 2022",

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Didden, JBHC, Dang, Q-V & Adan, IJBF 2023, Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System. in B Feng, G Pedrielli, Y Peng, S Shashaani, E Song, CG Corlu, LH Lee, EP Chew, T Roeder & P Lendermann (reds.), Proceedings of the 2022 Winter Simulation Conference, WSC 2022., 10015489, Institute of Electrical and Electronics Engineers, blz. 1806-1817, 2022 Winter Simulation Conference, WSC 2022, Singapore, Singapore, 11/12/22. https://doi.org/10.1109/WSC57314.2022.10015489

Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System. / Didden, J.B.H.C.; Dang, Quang-Vinh ; Adan, Ivo J.B.F.
Proceedings of the 2022 Winter Simulation Conference, WSC 2022. reds. / B. Feng; G. Pedrielli; Y. Peng; S. Shashaani; E. Song; C.G. Corlu; L.H. Lee; E.P. Chew; T. Roeder; P. Lendermann. Institute of Electrical and Electronics Engineers, 2023. blz. 1806-1817 10015489.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System

AU - Didden, J.B.H.C.

AU - Dang, Quang-Vinh

AU - Adan, Ivo J.B.F.

PY - 2023/1/23

Y1 - 2023/1/23

N2 - Order release in High-Mix-Low-Volume machine environments is often difficult to control due to the high variety of these shops. This paper, therefore, proposes an extension to a Multi-Agent System to control order release. Intelligence is introduced to the agent that is responsible for order release to autonomously learn which jobs to release into the shop through the use of sequencing rules, depending on the current environment. The objective is to minimize the mean weighted tardiness of all jobs. Computational results show that the proposed sequencing rules outperform other more common dispatching rules in terms of mean weighted tardiness. Further analysis of the results also reveals that a more accurate prediction of the lead time of jobs can be made, which is one of the main interests of practitioners in High-Mix-Low- Volume environments.

AB - Order release in High-Mix-Low-Volume machine environments is often difficult to control due to the high variety of these shops. This paper, therefore, proposes an extension to a Multi-Agent System to control order release. Intelligence is introduced to the agent that is responsible for order release to autonomously learn which jobs to release into the shop through the use of sequencing rules, depending on the current environment. The objective is to minimize the mean weighted tardiness of all jobs. Computational results show that the proposed sequencing rules outperform other more common dispatching rules in terms of mean weighted tardiness. Further analysis of the results also reveals that a more accurate prediction of the lead time of jobs can be made, which is one of the main interests of practitioners in High-Mix-Low- Volume environments.

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DO - 10.1109/WSC57314.2022.10015489

M3 - Conference contribution

SP - 1806

EP - 1817

BT - Proceedings of the 2022 Winter Simulation Conference, WSC 2022

A2 - Feng, B.

A2 - Pedrielli, G.

A2 - Peng, Y.

A2 - Shashaani, S.

A2 - Song, E.

A2 - Corlu, C.G.

A2 - Lee, L.H.

A2 - Chew, E.P.

A2 - Roeder, T.

A2 - Lendermann, P.

PB - Institute of Electrical and Electronics Engineers

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ER -

Didden JBHC, Dang QV , Adan IJBF. Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System. In Feng B, Pedrielli G, Peng Y, Shashaani S, Song E, Corlu CG, Lee LH, Chew EP, Roeder T, Lendermann P, redacteurs, Proceedings of the 2022 Winter Simulation Conference, WSC 2022. Institute of Electrical and Electronics Engineers. 2023. blz. 1806-1817. 10015489 doi: 10.1109/WSC57314.2022.10015489

Workload Control in High-Mix-Low-Volume Factories Through the Use of a Multi-Agent System

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