This paper deals with imperfect preventive maintenance optimization problem. The system to be maintained is assumed to be subject to random deterioration. To reduce the risk of failures, the proposed ...maintenance model takes into account two type of maintenance actions, namely corrective maintenance (CM) and preventive maintenance (PM). The system undergoes PM whenever its reliability reaches an appropriate value, while CM is performed at system failure. After a given number of maintenance actions, the system is preventively replaced by a new one. Both CM as well as PM are considered imperfect, i.e. they bring the system to an operating state which lies between two extreme states, namely the
as bad as old
state and
as good as new
state. The imperfect effect of CM and PM is modeled on the basis of the hybrid hazard rate model. The objective of the proposed imperfect PM optimization model consists on finding the optimal reliability threshold together with the optimal number of PM actions to minimize the expected total maintenance and replacement cost per unit of time. A mathematical model is then proposed. To solve this problem an algorithm is provided. A numerical example is also given to illustrate the proposed maintenance model.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The design of reverse logistics and remanufacturing processes and the recovery of end-of-life products have been well-studied in the literature. Quality, reliability, maintenance and warranty for ...recovered products and the remanufacturing activities that extend their life are integral issues in reverse logistics. This paper reviews recent and relevant literature on these issues in closed-loop supply chains, with a focus on remanufactured or second-hand products. The published literature is first classified into domain areas of research and practice. The wide array of mathematical tools and techniques used in the literature are then identified and mapped. Finally, the findings are summarised and the main research gaps are highlighted.
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BFBNIB, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
This book presents the recent work regarding the different approaches developed in the framework of the joint optimization of intelligent maintenance and production strategies. The originality of ...these strategies is that they take various constraints into account, including production management, subcontracting environmental degradation, inspection and product quality.
•The selective maintenance problem for large serial k-out-of-n:G systems is studied.•Imperfect maintenance levels are considered for both PM and CM actions.•Two nonlinear and two BIP formulations are ...proposed.•Experiments show the efficiency of the new 2-phase approach for complex structures.
The selective maintenance problem (SMP) arises in many large multicomponent systems which are operated for consecutive missions interspersed with finite breaks during which only a selected set of component repairs or replacements can be carried out due to limited time, budget, or resources. The problem is to decide which components and degree of repairs should be performed in order to guarantee a pre-specified performance level during the subsequent mission. Current SMP formulations in the literature are nonlinear, deal mainly with basic or series-parallel systems and mostly use heuristic methods to obtain solutions.
This paper introduces the first SMP model for serial k-out-of-n systems. Two nonlinear formulations are developed, which can be used to solve the problem for small to moderate size k-out-of-n systems. For large k-out-of-n systems or complex reliability structures, we develop a new two-phase approach which transforms the problem into a multidimensional multiple-choice knapsack problem (MMKP). The new approach is shown to be efficient through multiple sets of numerical experiments.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Existing maintenance optimization models for single-component repairable systems are extensively studied. However, maintenance optimization in multicomponent reparable systems (MCRS) is still a ...challenging problem, especially when dealing with stochastic dependent (s-dependent) competing risks between components. This paper develops a novel reliability-centered maintenance optimization model for MCRS operating under s-dependent competing risks. The s-dependency is captured by the joint reliability function constructed using Copula method and unknown parameters are estimated by maximum likelihood estimations (MLE). Maintenance strategies are carried out both at components and system levels. At components level, a preventive maintenance (PM) is performed whenever the reliability of the MCRS reaches a given threshold. PM actions are imperfect and modeled using the hybrid hazard rate approach. At system level, the whole system is preventively replaced after a certain number of PM cycles. The objective of the proposed maintenance strategies is to determine the optimal reliability threshold together with the optimal number of PM cycles that minimize the total expected maintenance cost rate in the infinite time horizon. The optimality conditions of the resulting maintenance optimization problem are formally discussed via two propositions. A case study that investigates a ball screw mechanism with multiple components is provided to validate the proposed approaches.
•A novel model for maintenance optimization in multicomponent system is proposed.•Both s-dependent competing risks and imperfect maintenance are accounted for.•Maintenance strategies are conducted both at system and component levels.•Optimization conditions for the proposed model are discussed mathematically.•The hybrid hazard rate model is extended from single to multicomponent system.
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This paper presents a novel column-generation-based approach for solving large-scale instances of the joint selective maintenance and repairperson assignment problem (JSM-RAP) for mission-oriented ...systems in industrial settings. Such systems perform consecutive missions separated by scheduled finite-duration breaks during which some of their components are imperfectly maintained by repairpersons, aiming to maximize system reliability in subsequent missions. The resulting mathematical model is computationally expensive, even for problems of moderate size. The proposed approach decomposes the JSM-RAP into a master problem and multiple subproblems that are solved to generate maintenance patterns, i.e., columns. Two methods are developed to handle the mixed-integer nonlinear subproblems: a piecewise-linear approximation and an exact reformulation into mixed-integer exponential conic programs. Branch-and-price algorithms are developed by embedding the column-generation method into a branch-and-bound tree to restore solution integrality and guarantee its optimality. Furthermore, we use a stabilization scheme to accelerate convergence. Numerical experiments validate the proposed approach and demonstrate its added value in terms of computation time and solution quality. Problem instances of very-large size, similar to real-life industrial production plants, are solved efficiently. Results also show that increasing the number of maintenance levels grants more flexibility to the optimizer to find combinations of components and maintenance actions that better use the limited resources.
•The joint selective maintenance and repairperson assignment problem is addressed.•New branch-and-price approaches are proposed to solve the problem efficiently.•Maintenance patterns are generated/added iteratively to a stabilized master problem.•Subproblems are reformulated as exponential conic programs or linearly approximated.•The proposed algorithms significantly outperform state-of-the-art solution methods.
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In closed-loop supply chain (CSLC) networks, low return quality reduces the number of usable cores and hence affects the strategic decision of facility location and sizing. This problem can be ...overcome by adding presorting centers in the CLSC network since presorting costs are typically lower than the costs incurred at subsequent processing stages. Presorting centers can separate poor quality products at the start of the reverse logistics cycle and reduce transportation costs and emissions. In this paper, a deterministic mathematical model and its robust variant are proposed to investigate the effects of the quality of returns on the CLSC network under the carbon cap (CC) and carbon cap-and-trade (CCT) policies. Numerical experiments conducted with data from a real resource recovery company show the effects of varying return quality on total emissions and profit, the impact of presorting center efficiency and transportation cost on the opening of presorting centers, and the impacts of CC and CCT policies on the configuration of the CLSC network. The main insight of this paper is that the carbon cap policy affects the network structure much more than does the carbon cap and trade policy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper investigates the problem of optimally integrating production quality and condition-based maintenance in a stochastically deteriorating single- product, single-machine production system. ...Inspections are periodically performed on the system to assess its actual degradation status. The system is considered to be in 'fail mode' whenever its degradation level exceeds a predetermined threshold. The proportion of non-conforming items, those that are produced during the time interval where the degradation is beyond the specification threshold, are replaced either via overtime production or spot market purchases. To optimise preventive maintenance costs and at the same time reduce production of non-conforming items, the degradation of the system must be optimally monitored so that preventive maintenance is carried out at appropriate time intervals. In this paper, an integrated optimisation model is developed to determine the optimal inspection cycle and the degradation threshold level, beyond which preventive maintenance should be carried out, while minimising the sum of inspection and maintenance costs, in addition to the production of non-conforming items and inventory costs. An expression for the total expected cost rate over an infinite time horizon is developed and solution method for the resulting model is discussed. Numerical experiments are provided to illustrate the proposed approach.
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BFBNIB, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
•A novel multiple missions selective maintenance (SM) optimization problem is proposed.•System components are subject to imperfect maintenance with several repair channels.•An integrated SM and ...repairpersons assignment optimization model is developed.•A genetic algorithm is derived to find the best assignment and main- tenance strategy.•The approach yields cost-effective solutions & accurate system reliability assessment.
This paper presents a new variant of the selective maintenance problem (SMP) to jointly optimize the maintenance planning and resource allocation problems for multiple missions. The classical SMP deals with components and maintenance level selection with the aim of maximizing the system reliability given limited budget and break duration. Of the few papers dealing with the multimission SMP, none addresses the repairperson assignment problem. This work develops an SMP model for jointly optimizing maintenance and assignment decisions in a system running multiple missions. The resulting SMP addresses five joint decisions: selection of components to maintain, selection of maintenance levels performed on the selected components, identification of breaks where maintenance tasks are performed, repairpersons selection, and maintenance tasks assignment to selected repairpersons. The objective is to minimize the total maintenance and labour costs for a maintenance plan that guarantees a given reliability threshold. The fundamental constructs and the relevant parameters of this SMP are developed and discussed. Given its combinatorial complexity, a heuristic method based on the genetic algorithm is developed and implemented as a solution technique. Results from numerical experiments carried out demonstrate the validity and the benefits of the proposed approach, and show the robustness and efficiency of the developed heuristic.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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