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FPA method for optimal production planning under availability/degradation machine and subcontracting constraint.

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Title: FPA method for optimal production planning under availability/degradation machine and subcontracting constraint.
Authors: Ayed, Souheil1 (AUTHOR), Hajej, Zied2,3 (AUTHOR), Turki, Sadok2,3 (AUTHOR) Sadok.Turki@univ-lorraine.fr, Rezg, Nidhal2,3 (AUTHOR)
Source: International Journal of Production Research. Apr2017, Vol. 55 Issue 8, p2135-2148. 14p. 2 Diagrams, 2 Charts, 4 Graphs.
Subjects: Function point analysis, Production planning, Repairing, Subcontractors, Perturbation theory
Abstract: This work treats an industrial problematic of a manufacturing systemM1subject to random failure and that satisfies a random demand under required service level. To ensure the satisfaction of the demand, it calls up on a second manufacturing systemM2that is a subcontractor and has a stochastic service level. This paper aims to determine an optimal production plan taking into account the degradation of the manufacturing system following its production rate and its availability. The unavailability of the machineM1is due to the non-negligible preventive and corrective maintenance actions duration. To consider a realistic case of the subcontractor, we consider that is not able to respond to the variation of the demand, and then it assumed that the manufacturer can order a minimum fixed quantity. We then derive an optimal production plan taking into account the degradation of the machine and simultaneously minimising: inventory, degradation and production cost. An algorithm based on finite perturbation analysis is proposed to determine the optimal production plan and the sensitivity study of the availability is presented. [ABSTRACT FROM PUBLISHER]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: FPA method for optimal production planning under availability/degradation machine and subcontracting constraint.
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  Data: <searchLink fieldCode="AR" term="%22Ayed%2C+Souheil%22">Ayed, Souheil</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hajej%2C+Zied%22">Hajej, Zied</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Turki%2C+Sadok%22">Turki, Sadok</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> Sadok.Turki@univ-lorraine.fr</i><br /><searchLink fieldCode="AR" term="%22Rezg%2C+Nidhal%22">Rezg, Nidhal</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Apr2017, Vol. 55 Issue 8, p2135-2148. 14p. 2 Diagrams, 2 Charts, 4 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Function+point+analysis%22">Function point analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Production+planning%22">Production planning</searchLink><br /><searchLink fieldCode="DE" term="%22Repairing%22">Repairing</searchLink><br /><searchLink fieldCode="DE" term="%22Subcontractors%22">Subcontractors</searchLink><br /><searchLink fieldCode="DE" term="%22Perturbation+theory%22">Perturbation theory</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: This work treats an industrial problematic of a manufacturing systemM1subject to random failure and that satisfies a random demand under required service level. To ensure the satisfaction of the demand, it calls up on a second manufacturing systemM2that is a subcontractor and has a stochastic service level. This paper aims to determine an optimal production plan taking into account the degradation of the manufacturing system following its production rate and its availability. The unavailability of the machineM1is due to the non-negligible preventive and corrective maintenance actions duration. To consider a realistic case of the subcontractor, we consider that is not able to respond to the variation of the demand, and then it assumed that the manufacturer can order a minimum fixed quantity. We then derive an optimal production plan taking into account the degradation of the machine and simultaneously minimising: inventory, degradation and production cost. An algorithm based on finite perturbation analysis is proposed to determine the optimal production plan and the sensitivity study of the availability is presented. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1080/00207543.2016.1165879
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      – Code: eng
        Text: English
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        PageCount: 14
        StartPage: 2135
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      – SubjectFull: Function point analysis
        Type: general
      – SubjectFull: Production planning
        Type: general
      – SubjectFull: Repairing
        Type: general
      – SubjectFull: Subcontractors
        Type: general
      – SubjectFull: Perturbation theory
        Type: general
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      – TitleFull: FPA method for optimal production planning under availability/degradation machine and subcontracting constraint.
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            NameFull: Ayed, Souheil
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            NameFull: Hajej, Zied
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            NameFull: Turki, Sadok
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              M: 04
              Text: Apr2017
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              Y: 2017
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