Skip to main content
Top
Published in: Advances in Manufacturing 2/2024

07-12-2023

A condition-based maintenance policy for reconfigurable multi-device systems

Authors: Shu-Lian Xie, Feng Xue, Wei-Min Zhang, Jia-Wei Zhu

Published in: Advances in Manufacturing | Issue 2/2024

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The exploration of component states for optimizing maintenance schedules in complex systems has garnered significant interest from researchers. However, current literature usually overlooks the critical aspects of system flexibility and reconfigurability. Judicious implementation of system reconfiguration can effectively mitigate system downtime and enhance production continuity. This study proposes a dynamic condition-based maintenance policy considering reconfiguration for reconfigurable systems. A double-layer decision rule was constructed for the devices and systems. To achieve the best overall maintenance effect of the system, the remaining useful life probability distribution and recommended maintenance time of each device were used to optimize the concurrent maintenance time window of the devices and determine whether to reconfigure them. A comprehensive maintenance efficiency index was introduced that simultaneously considered the maintenance cost rate, reliability, and availability of the system to characterize the overall maintenance effect. The reconfiguration cost was included in the maintenance cost. The proposed policy was tested through numerical experiments and compared with different-level policies. The results show that the proposed policy can significantly reduce the downtime and maintenance costs and improve the overall system reliability and availability.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Zhai S, Gehring B, Reinhart G (2021) Enabling predictive maintenance integrated production scheduling by operation-specific health prognostics with generative deep learning. J Manuf Syst 61:830–855CrossRef Zhai S, Gehring B, Reinhart G (2021) Enabling predictive maintenance integrated production scheduling by operation-specific health prognostics with generative deep learning. J Manuf Syst 61:830–855CrossRef
6.
go back to reference Jamil N, Hassan MF, Lim SK et al (2021) Predictive maintenance for rotating machinery by using vibration analysis. J Mech Eng Sci 15:8289–8299CrossRef Jamil N, Hassan MF, Lim SK et al (2021) Predictive maintenance for rotating machinery by using vibration analysis. J Mech Eng Sci 15:8289–8299CrossRef
8.
go back to reference Xue B, Xu F, Huang X et al (2022) Improved similarity based prognostics method for turbine engine degradation with degradation consistency test. Appl Intell 52:10181–10201CrossRef Xue B, Xu F, Huang X et al (2022) Improved similarity based prognostics method for turbine engine degradation with degradation consistency test. Appl Intell 52:10181–10201CrossRef
9.
go back to reference Serradilla O, Zugasti E, Rodriguez J et al (2022) Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects. Appl Intell 52:10934–10964CrossRef Serradilla O, Zugasti E, Rodriguez J et al (2022) Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects. Appl Intell 52:10934–10964CrossRef
10.
go back to reference Serradilla O, Zugasti E, de Okariz JR et al (2022) Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge. Int J Comput Integr Manuf 35:1310–1334CrossRef Serradilla O, Zugasti E, de Okariz JR et al (2022) Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge. Int J Comput Integr Manuf 35:1310–1334CrossRef
11.
go back to reference Popescu TD, Aiordachioaie D, Culea-Florescu A (2022) Basic tools for vibration analysis with applications to predictive maintenance of rotating machines: an overview. Int J Adv Manuf Technol 118:2883–2899CrossRef Popescu TD, Aiordachioaie D, Culea-Florescu A (2022) Basic tools for vibration analysis with applications to predictive maintenance of rotating machines: an overview. Int J Adv Manuf Technol 118:2883–2899CrossRef
12.
go back to reference Ouadah A, Zemmouchi-Ghomari L, Salhi N (2022) Selecting an appropriate supervised machine learning algorithm for predictive maintenance. Int J Adv Manuf Technol 119:4277–4301CrossRef Ouadah A, Zemmouchi-Ghomari L, Salhi N (2022) Selecting an appropriate supervised machine learning algorithm for predictive maintenance. Int J Adv Manuf Technol 119:4277–4301CrossRef
14.
go back to reference Al Hanbali A, Saleh H, Ullah N (2022) Two-threshold control limit policy in condition-based maintenance. Qual Reliab Eng Int 38:2170–2187CrossRef Al Hanbali A, Saleh H, Ullah N (2022) Two-threshold control limit policy in condition-based maintenance. Qual Reliab Eng Int 38:2170–2187CrossRef
15.
go back to reference Olde Keizer MCA, Flapper SDP, Teunter RH (2017) Condition-based maintenance policies for systems with multiple dependent components: a review. Eur J Oper Res 261:405–420MathSciNetCrossRef Olde Keizer MCA, Flapper SDP, Teunter RH (2017) Condition-based maintenance policies for systems with multiple dependent components: a review. Eur J Oper Res 261:405–420MathSciNetCrossRef
16.
go back to reference Ruschel E, Santos EAP, Loures EdFR (2017) Industrial maintenance decision-making: a systematic literature review. J Manuf Syst 45:180–194CrossRef Ruschel E, Santos EAP, Loures EdFR (2017) Industrial maintenance decision-making: a systematic literature review. J Manuf Syst 45:180–194CrossRef
18.
go back to reference Nabi HZ, Aized T, Riaz F (2022) Modeling, analysis and optimization of carousel-based flexible manufacturing system. J Ind Prod Eng 39:479–493 Nabi HZ, Aized T, Riaz F (2022) Modeling, analysis and optimization of carousel-based flexible manufacturing system. J Ind Prod Eng 39:479–493
19.
go back to reference Zhang S, Li S, Wang H et al (2022) An intelligent manufacturing cell based on human–robot collaboration of frequent task learning for flexible manufacturing. Int J Adv Manuf Technol 120:5725–5740CrossRef Zhang S, Li S, Wang H et al (2022) An intelligent manufacturing cell based on human–robot collaboration of frequent task learning for flexible manufacturing. Int J Adv Manuf Technol 120:5725–5740CrossRef
20.
go back to reference Maganha I, Silva C, Ferreira LMDF (2018) Understanding reconfigurability of manufacturing systems: an empirical analysis. J Manuf Syst 48:120–130CrossRef Maganha I, Silva C, Ferreira LMDF (2018) Understanding reconfigurability of manufacturing systems: an empirical analysis. J Manuf Syst 48:120–130CrossRef
21.
go back to reference Rösiö C, Aslam T, Srikanth KB et al (2019) Towards an assessment criterion of reconfigurable manufacturing systems within the automotive industry. Procedia Manuf 28:76–82CrossRef Rösiö C, Aslam T, Srikanth KB et al (2019) Towards an assessment criterion of reconfigurable manufacturing systems within the automotive industry. Procedia Manuf 28:76–82CrossRef
22.
go back to reference Bortolini M, Galizia FG, Mora C (2018) Reconfigurable manufacturing systems: literature review and research trend. J Manuf Syst 49:93–106CrossRef Bortolini M, Galizia FG, Mora C (2018) Reconfigurable manufacturing systems: literature review and research trend. J Manuf Syst 49:93–106CrossRef
23.
go back to reference Dahmani A, Benyoucef L, Mercantini JM (2022) Toward sustainable reconfigurable manufacturing systems (SRMS): past, present, and future. Procedia Comput Sci 200:1605–1614CrossRef Dahmani A, Benyoucef L, Mercantini JM (2022) Toward sustainable reconfigurable manufacturing systems (SRMS): past, present, and future. Procedia Comput Sci 200:1605–1614CrossRef
24.
go back to reference Zhang WY, Gan J, Hou QY (2022) Joint decision of condition-based maintenance and production scheduling for multi-component systems. Proc Inst Mech Eng Part B J Eng Manuf 236:726–740CrossRef Zhang WY, Gan J, Hou QY (2022) Joint decision of condition-based maintenance and production scheduling for multi-component systems. Proc Inst Mech Eng Part B J Eng Manuf 236:726–740CrossRef
25.
go back to reference Zhai SM, Kandemir MG, Reinhart G (2022) Predictive maintenance integrated production scheduling by applying deep generative prognostics models: approach, formulation and solution. Prod Eng Res Dev 16:65–88CrossRef Zhai SM, Kandemir MG, Reinhart G (2022) Predictive maintenance integrated production scheduling by applying deep generative prognostics models: approach, formulation and solution. Prod Eng Res Dev 16:65–88CrossRef
26.
go back to reference Ghaleb M, Taghipour S, Zolfagharinia H (2021) Real-time integrated production-scheduling and maintenance-planning in a flexible job shop with machine deterioration and condition-based maintenance. J Manuf Syst 61:423–449CrossRef Ghaleb M, Taghipour S, Zolfagharinia H (2021) Real-time integrated production-scheduling and maintenance-planning in a flexible job shop with machine deterioration and condition-based maintenance. J Manuf Syst 61:423–449CrossRef
28.
go back to reference Ladj A, Tayeb FBS, Varnier C (2021) Hybrid of metaheuristic approaches and fuzzy logic for the integrated flowshop scheduling with predictive maintenance problem under uncertainties. Eur J Ind Eng 15:675–710CrossRef Ladj A, Tayeb FBS, Varnier C (2021) Hybrid of metaheuristic approaches and fuzzy logic for the integrated flowshop scheduling with predictive maintenance problem under uncertainties. Eur J Ind Eng 15:675–710CrossRef
29.
go back to reference Dong Y, Xia T, Fang X et al (2019) Prognostic and health management for adaptive manufacturing systems with online sensors and flexible structures. Comput Ind Eng 133:57–68CrossRef Dong Y, Xia T, Fang X et al (2019) Prognostic and health management for adaptive manufacturing systems with online sensors and flexible structures. Comput Ind Eng 133:57–68CrossRef
38.
go back to reference Cui PH, Wang JQ, Li Y (2021) Data-driven modelling, analysis and improvement of multistage production systems with predictive maintenance and product quality. Int J Prod Res 60:6848–6865CrossRef Cui PH, Wang JQ, Li Y (2021) Data-driven modelling, analysis and improvement of multistage production systems with predictive maintenance and product quality. Int J Prod Res 60:6848–6865CrossRef
39.
go back to reference Lu B, Zhou X (2019) Quality and reliability oriented maintenance for multistage manufacturing systems subject to condition monitoring. J Manuf Syst 52:76–85CrossRef Lu B, Zhou X (2019) Quality and reliability oriented maintenance for multistage manufacturing systems subject to condition monitoring. J Manuf Syst 52:76–85CrossRef
40.
go back to reference Wang YM, Liu PD, Yao YY (2022) BMW-TOPSIS: a generalized TOPSIS model based on three-way decision. Inform Sci 607:799–818CrossRef Wang YM, Liu PD, Yao YY (2022) BMW-TOPSIS: a generalized TOPSIS model based on three-way decision. Inform Sci 607:799–818CrossRef
Metadata
Title
A condition-based maintenance policy for reconfigurable multi-device systems
Authors
Shu-Lian Xie
Feng Xue
Wei-Min Zhang
Jia-Wei Zhu
Publication date
07-12-2023
Publisher
Shanghai University
Published in
Advances in Manufacturing / Issue 2/2024
Print ISSN: 2095-3127
Electronic ISSN: 2195-3597
DOI
https://doi.org/10.1007/s40436-023-00465-x

Other articles of this Issue 2/2024

Advances in Manufacturing 2/2024 Go to the issue

Premium Partners