A New Heuristic Method for Solving Joint Job Shop Scheduling of Production and Maintenance

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

doi:10.1016/j.ifacol.2015.06.348

Cited by 12 publications

(5 citation statements)

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“…For the breakdown case, a revised schedule was produced by the right shifting method, and the affected operations were impacted from the time of breakdown on the broken machine. Fnaiech et al (2015) proposed a new heuristic method to address a JSP where machines were subject to fixed PM planning. They combined a Modified Genetic Algorithm (MGA) and Heuristic Displacement of Genes (HDG) to solve the considered problem to minimize 𝑐 𝑚𝑎𝑥 .…”

Section: Integrated Production-maintenance Scheduling Problem For Job...mentioning

confidence: 99%

Energy-aware flexible job shop scheduling problem and preventive maintenance under the limited resource constraints

Mirahmadi¹

2022

Preprint

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<p>This thesis presents the development of a novel model for solving the flexible job shop scheduling problem with maintenance activities where maintenance activities are limited by a maintenance crew constraint. Moreover, in order to extend it in terms of energy consumption, the cost of energy usage associated with different states of the machines is considered in the objective function. The objective is to minimize the total cost of hiring repairmen, energy consumption, and tardiness penalties. We assume the production machines in this environment may break down which causes the unavailability of the machines for the production. In the maintenance phase, a threshold-based maintenance strategy is applied based on the obtained optimal replacement age of each machine. Accordingly, the required maintenance action is divided into two categories: minimal repair or replacement activities. Furthermore, opportunistic maintenance is considered in the scheduling to minimize the required number of repairmen to be hired. In fact, the main aims are to find the optimal machine assignment and operation sequence, to determine if preventive maintenance is required to be executed between two consecutive operations, and to specify the optimal number of maintenance crew to be hired for the shop floor to minimize the expected total cost.</p>

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Section: Integrated Production-maintenance Scheduling Problem For Job...mentioning

confidence: 99%

Energy-aware flexible job shop scheduling problem and preventive maintenance under the limited resource constraints

Mirahmadi¹

2022

Preprint

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“…for flexible job-shop scheduling using heuristic methods cf. (Li, Pan, and Tasgetiren 2014), (Fnaiech et al 2015) and (El Khoukhi, Boukachour, and Alaoui 2017), minimising makes pan under availability constraints cf. (Benttaleb, Hnaien, and Yalaoui 2016), energy-efficient flexible job-shop scheduling cf.…”

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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“…The objective was to optimize the total profit, which was modelled as production values minus production costs, maintenance costs including PM and replacement costs, as well as tardiness costs. A new heuristic is proposed by [18] to solve the joint JSSP of production and maintenance actions by extending the standard GA with the idea of enhancing its random character by guiding the steps in a logical procedure. In [19], the integrated planning of production, maintenance and quality in deteriorating systems is investigated.…”

Section: B Integrated Production and Maintenance Schedulingmentioning

confidence: 99%

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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A New Heuristic Method for Solving Joint Job Shop Scheduling of Production and Maintenance

Cited by 12 publications

References 11 publications

Energy-aware flexible job shop scheduling problem and preventive maintenance under the limited resource constraints

Energy-aware flexible job shop scheduling problem and preventive maintenance under the limited resource constraints

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

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

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