A Decison-Making Approach for Job Shop Scheduling with Job Depending Degradation and Predictive Maintenance

Fitouri, Cyrine; Fnaiech, Nader; Varnier, Christophe; Fnaiech, Farhat; Zerhouni, Noureddine

doi:10.1016/j.ifacol.2016.07.782

Cited by 30 publications

(17 citation statements)

References 13 publications

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“…for job-shop scheduling depending on degradation rates and forecasting failures moments cf. (Mokhtari and Dadgar 2015) and time-varying machine failure rate (Fitouri et al 2016)).…”

Section: Review Of Related Kbm Approachesmentioning

confidence: 99%

PriMa: a prescriptive maintenance model for cyber-physical production systems

Ansari

Grepl

Nemeth

2019

International Journal of Computer Integrated Manufacturing

134

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Cyber-physical production systems (CPPS), as an emerging Industry 4.0's technology, trigger a paradigm shift from descriptive to prescriptive maintenance. In particular, maintenance management approaches nowadays are more and more transformed to (semi-) automated knowledge-based decision support systems. This paper is intended to examine existing approaches and challenges towards rethinking maintenance in the context of Industry 4.0 and thus contributes to the literature of production management and planning, by introducing a novel prescriptive maintenance model (PriMa). PriMa is comprising of four layers (i.e. data management, predictive data analytic toolbox, recommender and decision support dashboard as well as an overarching layer for semantic-based learning and reasoning). The integrated approach of PriMa enhances two functional capabilities, namely i) efficiently processing large amount of multi-modal and heterogeneous data collected from multidimensional data sources and ii) effectively generating decision support measures and recommendations for improving and optimising forthcoming maintenance plans correlated with production planning and control (PPC) systems. An industry-oriented proof-of-concept study has been conducted to explore the feasibility of applying PriMa in real production systems by implementing a decision support solution and achieving a significant reduction of downtime. Finally, future research directions in this area are outlined. ARTICLE HISTORY

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“…for job-shop scheduling depending on degradation rates and forecasting failures moments cf. (Mokhtari and Dadgar 2015) and time-varying machine failure rate (Fitouri et al 2016)).…”

Section: Review Of Related Kbm Approachesmentioning

confidence: 99%

PriMa: a prescriptive maintenance model for cyber-physical production systems

Ansari

Grepl

Nemeth

2019

International Journal of Computer Integrated Manufacturing

134

View full text Add to dashboard Cite

show abstract

“…In [19], the integrated planning of production, maintenance and quality in deteriorating systems is investigated. Scheduling with job specific deterioration: The authors of [20] and [21] were the first to present the integrated JSSP in an job specific manner. While [20] introduced the JSSP with job specific deterioration and PdM and presented a heuristic to solve it, [21] divided the scheduling problem in three parts, namely the production scheduling problem, the PHM problem, and the PdM scheduling problem.…”

Section: B Integrated Production and Maintenance Schedulingmentioning

confidence: 99%

“…Scheduling with job specific deterioration: The authors of [20] and [21] were the first to present the integrated JSSP in an job specific manner. While [20] introduced the JSSP with job specific deterioration and PdM and presented a heuristic to solve it, [21] divided the scheduling problem in three parts, namely the production scheduling problem, the PHM problem, and the PdM scheduling problem. While the production scheduling problem made the common assumptions for a single machine, the PHM problem formulation assumed that the machine's condition is continuously monitored.…”

Section: B Integrated Production and Maintenance Schedulingmentioning

confidence: 99%

“…As deduced from the literature review, an integrated scheduling model requires information about the probability of an unplanned machine breakdown. Therefore, the machine's historic deterioration as well as its future stress load have to be taken into account when modeling the machine's health [20,21]. For this purpose, the proposed framework distinguishes an operation-focused deterioration estimation and a machinefocused failure probability prediction.…”

Section: The Model Of Operation Specific Stress Equivalentsmentioning

confidence: 99%

“…RULik defines the point in time the machine Mk processing only operation Oi is fully deteriorated and will most likely fail. Given a certain processing time p i the level of deterioration imposed on a machine by an operation Oi can be determined as its share in the machine's RULik [20,21]. Consequently, the Operation Specific Stress Equivalent (OSSE) is defined as =   Fig.…”

Section: A Deterioration Estimationmentioning

confidence: 99%

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Formulation and Solution for the Predictive Maintenance Integrated Job Shop Scheduling Problem

Zhai¹,

Rieß²,

Reinhart³

2019

2019 IEEE International Conference on Prognostics and Health Management (ICPHM)

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Predictive Maintenance has gained a lot of attention in recent years due to the development of improved sensors and intelligent algorithms. These allow for monitoring the health condition of production machinery and predict its future deterioration. In order to generate added value for industrial use cases, two more steps are required: considering the machine's time-varying operational conditions and integrating its dependent deterioration prediction in a holistic scheduling approach. This publication identifies a shortage of deterioration estimation frameworks under time-varying operational conditions as well as a lack of Predictive Maintenance integrated scheduling problems in the literature. Subsequently, a new conceptual framework to model future machine deterioration under time-varying operational conditions and its application in production scheduling is introduced. The Operation Specific Stress Equivalent (OSSE) represents the load of a future production job on the machine and supports a general formulation of the maintenance integrated job shop scheduling problem (MIJSSP). This formulation is presented together with benchmark instances and corresponding sample data. Finally, the formulation is tested with the help of a genetic algorithm that illustrates the potential of using new objective functions for decision support, such as the Reliability Weighted Makespan Cmax R .

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Simultaneous Scheduling of Production and Maintenance in a Flexible Job-Shop Workshop

Bencheikh,

Bettayeb

2024

Lecture Notes in Networks and Systems

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A Decison-Making Approach for Job Shop Scheduling with Job Depending Degradation and Predictive Maintenance

Cited by 30 publications

References 13 publications

PriMa: a prescriptive maintenance model for cyber-physical production systems

PriMa: a prescriptive maintenance model for cyber-physical production systems

Formulation and Solution for the Predictive Maintenance Integrated Job Shop Scheduling Problem

Simultaneous Scheduling of Production and Maintenance in a Flexible Job-Shop Workshop

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