A two-stage dynamic capacity planning approach for agricultural machinery maintenance service with demand uncertainty

Hu, Y; Liu, Y; Wang, Z; Wen, J; Li, J; Lu, J

A two-stage dynamic capacity planning approach for agricultural machinery maintenance service with demand uncertainty

Hu, Y Liu, Y Wang, Z Wen, J Li, J Lu, J

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Biosystems Engineering, 2020, 190, pp. 201-217
Issue Date:: 2020-02-01

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Field	Value	Language
dc.contributor.author	Hu, Y
dc.contributor.author	Liu, Y
dc.contributor.author	Wang, Z
dc.contributor.author	Wen, J
dc.contributor.author	Li, J
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732
dc.date.accessioned	2021-06-18T01:52:34Z
dc.date.available	2021-06-18T01:52:34Z
dc.date.issued	2020-02-01
dc.identifier.citation	Biosystems Engineering, 2020, 190, pp. 201-217
dc.identifier.issn	1537-5110
dc.identifier.uri	http://hdl.handle.net/10453/149611
dc.description.abstract	Reasonable capacity planning is important to improve the efficiency of agricultural operations and reduce the operating cost for maintenance service providers during the harvesting season. Many studies involve staffing and scheduling approaches that account for nonstationary demand. However, these methods are not applicable in the field of agricultural operations because of the explosive growth of the failure rate during the harvesting season. In addition, few studies have involved allocation methods and related models between different planning levels, especially for the uncertain demand in agricultural machinery maintenance service, which has a strong reliance on results between the different management levels. Motivated by this observed gap, this paper proposes a two-stage analytical methodology that connects the data between different planning levels and aims to develop a dynamic capacity planning method of maintenance service for agricultural machinery fleets. At the first stage, we develop a scheduling model for agricultural machinery fleets based on the time window of harvesting. At the second stage, we propose a following-service mode and a dynamic covering model based on the scheduling results, in which queuing theory is used to solve the service parameters. This study satisfies the needs of service providers to find the optimum balance between high service quality and reasonable costs. A real-life case study is presented to illustrate the applicability of the proposed model as well as the effectiveness of the designed approach.
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	Biosystems Engineering
dc.relation.isbasedon	10.1016/j.biosystemseng.2019.12.005
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0999 Other Engineering
dc.subject.classification	Agronomy & Agriculture
dc.title	A two-stage dynamic capacity planning approach for agricultural machinery maintenance service with demand uncertainty
dc.type	Journal Article
utslib.citation.volume	190
utslib.for	0999 Other Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	closed_access	*
dc.date.updated	2021-06-18T01:52:33Z
pubs.publication-status	Published
pubs.volume	190

Abstract:

Reasonable capacity planning is important to improve the efficiency of agricultural operations and reduce the operating cost for maintenance service providers during the harvesting season. Many studies involve staffing and scheduling approaches that account for nonstationary demand. However, these methods are not applicable in the field of agricultural operations because of the explosive growth of the failure rate during the harvesting season. In addition, few studies have involved allocation methods and related models between different planning levels, especially for the uncertain demand in agricultural machinery maintenance service, which has a strong reliance on results between the different management levels. Motivated by this observed gap, this paper proposes a two-stage analytical methodology that connects the data between different planning levels and aims to develop a dynamic capacity planning method of maintenance service for agricultural machinery fleets. At the first stage, we develop a scheduling model for agricultural machinery fleets based on the time window of harvesting. At the second stage, we propose a following-service mode and a dynamic covering model based on the scheduling results, in which queuing theory is used to solve the service parameters. This study satisfies the needs of service providers to find the optimum balance between high service quality and reasonable costs. A real-life case study is presented to illustrate the applicability of the proposed model as well as the effectiveness of the designed approach.

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http://hdl.handle.net/10453/149611