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Finite Horizon Degradation Control of Complex Interconnected Systems
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics.ORCID iD: 0000-0001-5429-7223
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics. (Predictive Maintenance)ORCID iD: 0000-0001-7340-4629
2021 (English)In: Proceedings of the 17th IFAC Symposium on Information Control Problems in Manufacturing Budapest, Hungary, June 7-9, 2021, Elsevier , 2021, p. 319-324Conference paper, Published paper (Refereed)
Abstract [en]

In industrial production, it is of great importance to have high availability in its production equipment. Well-functioning maintenance is a significant factor for a high level of availability. This can be achieved by minimizing the number of reactive maintenance stops and optimizing scheduled maintenance. New methods for predictive maintenance provide a good opportunity for this, but most technologies that are available today are designed for individual sub-systems and they are rarely designed for a complex, interconnected machine. In the process industry, raw materials are rocessed into a finished product in a continuous flow through several subsystems and if one subsystem stops, the entire process flow stops. For these processes, it is more important to optimize the maintenance efforts for subsystems so maintenance can take place synchronized. This paper describes a method of supervised control that includes maintenance aspects; health parameters indicating deterioration are included in a MIMO controller. The method is verified in a simulation of a rolling mill with three rollers. The results show that it is possible to optimize the whole complex process including several subprocesses by using a health parameter as a control parameter and broadening the controllability of the system by dividing the workload in a way that all the subsystems reach the desired degradation level for maintenance in a desired optimum time. 

Place, publisher, year, edition, pages
Elsevier , 2021. p. 319-324
Series
IFAC-PapersOnLine, ISSN 2405-8963 ; 54(1)
Keywords [en]
Intelligent maintenance systems, Production planning and control, Model-driven systems engineering, Control of multi-scale systems, Design of fault tolerant/reliable systems
National Category
Control Engineering
Research subject
Intelligent Industry
Identifiers
URN: urn:nbn:se:hig:diva-36246DOI: 10.1016/j.ifacol.2021.08.036ISI: 000716937600054Scopus ID: 2-s2.0-85120705793OAI: oai:DiVA.org:hig-36246DiVA, id: diva2:1566699
Conference
INCOM 2021, 17th IFAC Symposium on Information Control Problems in Manufacturing, Budapest, Hungary, June 7-9, 2021 
Note

The research project is financed by the European Commission within the European Regional Development Fund, the SwedishAgency for Economic and Regional Growth, Region Gävleborg, and the University of Gävle. 

Available from: 2021-06-15 Created: 2021-06-15 Last updated: 2024-11-20Bibliographically approved
In thesis
1. Health-Aware Control
Open this publication in new window or tab >>Health-Aware Control
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Health-aware control is essential for enhancing the longevity and efficiency of complex systems by integrating machine health metrics into production and maintenance planning. Traditional methods often treat production and maintenance as separate tasks, overlooking their interdependencies and thus failing to achieve optimal system performance. A key challenge in addressing this problem and considering the mutual effects of production and maintenance is establishing a cohesive framework that bidirectionally connects high-level decision-making with low-level operational control, optimizing production and maintenance at the same time. To address this challenge, the shop-floor machinery must be aware of its state of health (SOH), and the high-level planning should be able to include this information about SOH as an influential parameter in production planning. Doing this involves not only developing physically interpretable and cost-effective methods for identifying degradation but also implementing adaptive control strategies that respond to real-time conditions. Moreover, it is critical to study how lifespan control affects other system parameters to ensure optimal performance. To this end, this research first tackles the challenges in identifying and controlling degradation at the shop-floor level. It then bridges the gap between high- and low-level control by proposing a framework that integrates both levels into a unified, health-aware production and maintenance system. The thesis first explores the controllability of machine lifespan in interconnected systems. It then proposes methods for identifying degradation as a physically interpretable and controllable system parameter. The thesis further investigates the application of advanced control strategies such as model predictive control and linear quadratic regulators to manage degradation at both the low and high levels. A novel contribution is made by introducing the concept of state-action cost estimation for degradation cost, which links machine degradation directly to control actions, allowing for real-time degradation management without the need for costly physical modeling. The proposed approach is validated through simulations of various industrial systems and publicly accessible datasets, demonstrating its capability to optimize machine health and performance while maintaining product quality and minimizing degradation. Finally, bridging the gap between high-level strategic planning and low-level operational execution, this thesis provides a pathway to more efficient and resilient manufacturing systems where health-aware control is fully integrated.

Abstract [sv]

Statusmedveten reglering är väsentlig för att förbättra livslängden och effektiviteten hos komplexa system genom att integrera maskinens hälsotillstånd i produktions- och underhållsplaneringen. Traditionella metoder behandlar ofta produktion och underhåll som separata uppgifter, vilket bortser från deras ömsesidiga beroenden och därmed misslyckas med att uppnå optimal systemprestanda. En nyckelutmaning i att adressera detta problem och beakta de ömsesidiga effekterna av produktion och underhåll är att etablera ett sammanhängande ramverk som, i båda riktningar, kopplar samman beslutsfattande på hög nivå med operativ reglering på låg nivå, optimerar produktion och underhåll och gör det möjligt att följa planen vid varje tillfälle. För att möta denna utmaning måste maskinerna på verkstadsgolvet vara medvetna om sitt hälsotillstånd (SOH), och högnivåplaneringen måste kunna inkludera denna information som en inflytelserik parameter i produktionsplaneringen. Att göra detta innebär inte bara att utveckla fysiskt tolkningsbara och kostnadseffektiva metoder för att identifiera försämring av SOH utan också att implementera adaptiva styrstrategier som agerar i realtid. Dessutom är det kritiskt att studera hur styrning av livslängd påverkar andra systemparametrar för att säkerställa optimal prestanda. För detta ändamål adresserar denna forskning först begränsningar i identifiering och kontroll av förslitningar på verkstadsgolvnivå och fyller sedan gapet mellan hög- och lågnivåstyrning genom att föreslå ett ramverk som integrerar båda nivåerna i ett sammanhängande, statusmedvetet produktions och underhållssystem. Avhandlingen utforskar först styrbarheten av maskinens livslängd i sammankopplade system. Den föreslår sedan metoder för att identifiera försämring av SOH som en fysiskt tolkningsbar och kontrollerbar systemparameter. Avhandlingen undersöker vidare tillämpningen av avancerade styrstrategier såsom modellprediktiv styrning och linjär kvadratisk reglering för att hantera förslitning på både låg och hög nivå. Ett nyskapande bidrag görs genom att introducera konceptet med en kostnadsestimering av förslitning baserad på både maskinens tillstånd och handling, vilket länkar maskinförsämring direkt till styråtgärder. Det möjliggör i sin tur reglering i realtid av förslitningar utan behov av kostsam fysikalisk modellering. Den föreslagna metoden valideras genom simuleringar av olika industriella system och offentligt tillgängliga dataset. Resultaten visar dess förmåga att optimera maskinhälsa och prestanda samtidigt som produktkvaliteten upprätthålls och förslitningarna minimeras. Slutligen, genom att överbrygga gapet mellan högnivå strategisk planering och lågnivå operativ exekvering, erbjuder denna avhandling en väg till mer effektiva och resilienta tillverkningssystem där statusmedveten styrning är fullt integrerad.

Place, publisher, year, edition, pages
Gävle: Gävle University Press, 2024. p. 70
Series
Doctoral thesisDoctoral thesis ; 53
Keywords
health-aware control, degradation control, state-of-health control, lifespan planning, production and maintenance planning, statusmedveten reglering, försämringskontroll, livslängdsplanering, produktions- och underhållsplanering
National Category
Control Engineering Reliability and Maintenance Production Engineering, Human Work Science and Ergonomics
Research subject
Intelligent Industry
Identifiers
urn:nbn:se:hig:diva-45854 (URN)978-91-89593-48-0 (ISBN)978-91-89593-49-7 (ISBN)
Public defence
2025-01-15, 12:108, Kungsbäcksvägen 47, Gävle, 13:00
Opponent
Supervisors
Available from: 2024-12-17 Created: 2024-10-16 Last updated: 2025-01-20

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Björsell, NiclasHosseinzadeh Dadash, Amirhossein

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