Degradation modeling to predict the residual life distribution of parallel unit systems on benchmark instances

Akshay Chandra, Muneeb Ahsan, Somnath Lahiri, Suraj Panigrahi, Vijay Manupati, Eric Costa

Research output: Chapter in Book/Report/Published conference proceedingChapter

Abstract

A manufacturing system often consists of multiple units as workcells with complex work systems to achieve the desired outcomes in an efficient and effective manner. Uncertain events such as machine down time or scheduled maintenance are unavoidable in any manufacturing unit. In this paper, we are trying to find the maximum workload of the remaining machines to fulfill the production requirements. To achieve this, a dynamic workload adjustment strategy has been proposed with dynamic upgradation of residual life distribution model. With parallel configurations and different benchmark instances the simulation experiments has been conducted to evaluate the degradation rate of different units. Results show that the proposed method is effective for finding the residual life of multi-unit systems.
Original languageEnglish
Title of host publicationLecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017
EditorsS. I. Ao, L. Gelman , D. Hukins , A. Hunter , A. Korsunsky
Pages783-787
Number of pages5
Publication statusPublished - 2017
EventWorld Congress on Engineering 2017 - London, United Kingdom
Duration: 5 Jul 20177 Jul 2017

Publication series

NameLecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 (WCE 2017)
PublisherNewswood Limited
VolumeII
ISSN (Print)2078-0958
ISSN (Electronic)2078-0966

Conference

ConferenceWorld Congress on Engineering 2017
Abbreviated titleWCE 2017
CountryUnited Kingdom
CityLondon
Period5/07/177/07/17

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Chandra, A., Ahsan, M., Lahiri, S., Panigrahi, S., Manupati, V., & Costa, E. (2017). Degradation modeling to predict the residual life distribution of parallel unit systems on benchmark instances. In S. I. Ao, L. Gelman , D. Hukins , A. Hunter , & A. Korsunsky (Eds.), Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 (pp. 783-787). (Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 (WCE 2017); Vol. II).
Chandra, Akshay ; Ahsan, Muneeb ; Lahiri, Somnath ; Panigrahi, Suraj ; Manupati, Vijay ; Costa, Eric. / Degradation modeling to predict the residual life distribution of parallel unit systems on benchmark instances. Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017. editor / S. I. Ao ; L. Gelman ; D. Hukins ; A. Hunter ; A. Korsunsky . 2017. pp. 783-787 (Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 (WCE 2017)).
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abstract = "A manufacturing system often consists of multiple units as workcells with complex work systems to achieve the desired outcomes in an efficient and effective manner. Uncertain events such as machine down time or scheduled maintenance are unavoidable in any manufacturing unit. In this paper, we are trying to find the maximum workload of the remaining machines to fulfill the production requirements. To achieve this, a dynamic workload adjustment strategy has been proposed with dynamic upgradation of residual life distribution model. With parallel configurations and different benchmark instances the simulation experiments has been conducted to evaluate the degradation rate of different units. Results show that the proposed method is effective for finding the residual life of multi-unit systems.",
author = "Akshay Chandra and Muneeb Ahsan and Somnath Lahiri and Suraj Panigrahi and Vijay Manupati and Eric Costa",
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Chandra, A, Ahsan, M, Lahiri, S, Panigrahi, S, Manupati, V & Costa, E 2017, Degradation modeling to predict the residual life distribution of parallel unit systems on benchmark instances. in SI Ao, L Gelman , D Hukins , A Hunter & A Korsunsky (eds), Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017. Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 (WCE 2017), vol. II, pp. 783-787, World Congress on Engineering 2017, London, United Kingdom, 5/07/17.

Degradation modeling to predict the residual life distribution of parallel unit systems on benchmark instances. / Chandra, Akshay; Ahsan, Muneeb; Lahiri, Somnath; Panigrahi, Suraj; Manupati, Vijay; Costa, Eric.

Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017. ed. / S. I. Ao; L. Gelman ; D. Hukins ; A. Hunter ; A. Korsunsky . 2017. p. 783-787 (Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 (WCE 2017); Vol. II).

Research output: Chapter in Book/Report/Published conference proceedingChapter

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T1 - Degradation modeling to predict the residual life distribution of parallel unit systems on benchmark instances

AU - Chandra, Akshay

AU - Ahsan, Muneeb

AU - Lahiri, Somnath

AU - Panigrahi, Suraj

AU - Manupati, Vijay

AU - Costa, Eric

PY - 2017

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AB - A manufacturing system often consists of multiple units as workcells with complex work systems to achieve the desired outcomes in an efficient and effective manner. Uncertain events such as machine down time or scheduled maintenance are unavoidable in any manufacturing unit. In this paper, we are trying to find the maximum workload of the remaining machines to fulfill the production requirements. To achieve this, a dynamic workload adjustment strategy has been proposed with dynamic upgradation of residual life distribution model. With parallel configurations and different benchmark instances the simulation experiments has been conducted to evaluate the degradation rate of different units. Results show that the proposed method is effective for finding the residual life of multi-unit systems.

M3 - Chapter

SN - 9789881404831

T3 - Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 (WCE 2017)

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BT - Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017

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Chandra A, Ahsan M, Lahiri S, Panigrahi S, Manupati V, Costa E. Degradation modeling to predict the residual life distribution of parallel unit systems on benchmark instances. In Ao SI, Gelman L, Hukins D, Hunter A, Korsunsky A, editors, Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017. 2017. p. 783-787. (Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2017 (WCE 2017)).