Optimal inspection and preventive maintenance of units with revealed and unrevealed failures

Badía, F. G.; Berrade, María Dolores; Campos, Clemente A.

doi:10.1016/s0951-8320(02)00154-0

Cited by 104 publications

(42 citation statements)

References 6 publications

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“…The component terms for various probabilities in (14) and (15) can be calculated using (1), (2), (5), (6), (7), (9), (10), and (13) and the minimization of the long-run expected cost per unit time is chosen as the objective of the proposed joint inspection-based PM and spare ordering policy and the decisions variables are the inspection interval and the value of . Clearly, the system will be restored to be as good as new after each replacement.…”

Section: Casementioning

confidence: 99%

“…When the deterioration process could be determined in real time, most papers focus on the optimization of threshold levels, which are relevant to preventive replacement and corrective replacement [2][3][4]. However, not all plants can be checked online; therefore, inspection as a main PM program has been extensively studied and can be observed in the industry [5][6][7]. Based on inspectionbased PM policy, a system is checked regularly or irregularly such that the deterioration process is usually described as a discrete state space.…”

Section: Introductionmentioning

confidence: 99%

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A Joint Inspection-Based Preventive Maintenance and Spare Ordering Optimization Policy Using a Three-Stage Failure Process

et al. 2017

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Separated decision-making for maintenance and spare ordering is unrealistic in the industry, so this paper aims to optimize them together. A joint policy of inspection-based preventive maintenance (PM) and spare ordering considering two modes of spare ordering, namely, a regular order and an emergency order, is proposed for single-unit systems using a three-stage failure process. If the system is recognized to be in the minor defective stage, the original inspection interval is shortened and a regular order is placed. However, replacement is undertaken preventively or correctively if the severe defective stage is identified or a failure occurs. Depending on the system state and the state of the regular ordered spare when replacement is needed, all possible scenarios are considered to construct optimization model I. The decision variables are the optimal inspection interval and the times of shortening the original inspection interval. Additionally, model II on the basis of an assumption that the spare is always ordered at time 0 is also developed. The results from a numerical example illustrated the applicability and the effectiveness of model compared to model II, and the irregular inspection policy is validated to be cost-saving compared to the regular inspection policy.

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Section: Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Joint Inspection-Based Preventive Maintenance and Spare Ordering Optimization Policy Using a Three-Stage Failure Process

et al. 2017

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“…In the work of Chaudhuri and Sahu [31], the reliability of a system with increasing failure rates (IFR) and with imperfect PM was proved to be a concave function and optimum PM intervals for perfect and imperfect PM were found and compared. Other works on periodic PM optimization with imperfect maintenance are presented in [32], [33] and [34]. The work by Linderman et al [35] demonstrated considerable economic benefits by having an adaptive maintenance policy, where the interval of PM events adapts to the stability of the process.…”

Section: Reliability Based Maintenancementioning

confidence: 99%

Joint Maintenance and Production Operations Decision Making in Flexible Manufacturing Systems

Celen

Djurdjanović

2012

ASME 2012 International Manufacturing Science and Engineering Conference

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In highly flexible and integrated manufacturing systems such as those in semiconductor manufacturing, there exist strong dynamic interactions between the equipment condition, operations executed on the equipment and the resulting product quality. These interactions necessitate a methodology that integrates the decisions of maintenance scheduling and production operations. Currently, maintenance and production operations decision-making are two decoupled processes. In this paper we aim to devise an integrated decision making policy for maintenance scheduling and production sequencing with the objective of maximizing an adaptive profit function, while taking into account operation-dependent degradation models and a production target. In order to obtain the optimal decision policy, a metaheuristic method based on the results of discrete-event simulations of the target manufacturing system is used. The new approach is demonstrated in simulations of a generic cluster tool routinely used in semiconductor manufacturing. The results show that jointly making maintenance and production sequencing decisions consistently outperforms the current practice of making these decisions separately.

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“…The research has addressed equipment classification systems, preventive maintenance (PM) scheduling models, and work-order systems for prioritizing repair requests for industrial facilities and manufacturing companies, [8][9][10][11][12] but very few of these systems have addressed the specific needs of the healthcare management field. Commonly accepted maintenance policies include age-replacement PM, [13] as well as the periodic PM and sequential PM policies [14]. In the periodic PM policy, devices subject to degradation are maintained in fixed predefined time intervals, independent of machine failure rate, while in a sequential PM policy the PM time intervals become shorter and shorter as time passes (i.e.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Healthcare Management System: A New Approach in Work-order Prioritization for Medical Equipment Maintenance Requests

et al. 2010

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The effective maintenance management of medical technology influences the quality of care delivered and the profitability of healthcare facilities. Medical equipment maintenance in Jordan lacks an objective prioritization system; consequently, the system is not sensitive to the impact of equipment downtime on patient morbidity and mortality. The current work presents a novel software system (EQUIMEDCOMP) that is designed to achieve valuable improvements in the maintenance management of medical technology. This work-order prioritization model sorts medical maintenance requests by calculating a priority index for each request. Model performance was assessed by utilizing maintenance requests from several Jordanian hospitals. The system proved highly efficient in minimizing equipment downtime based on healthcare delivery capacity, and, consequently, patient outcome. Additionally, a preventive maintenance optimization module and an equipment quality control system are incorporated. The system is, therefore, expected to improve the reliability of medical equipment and significantly improve safety and cost-efficiency.

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Optimal inspection and preventive maintenance of units with revealed and unrevealed failures

Cited by 104 publications

References 6 publications

A Joint Inspection-Based Preventive Maintenance and Spare Ordering Optimization Policy Using a Three-Stage Failure Process

A Joint Inspection-Based Preventive Maintenance and Spare Ordering Optimization Policy Using a Three-Stage Failure Process

Joint Maintenance and Production Operations Decision Making in Flexible Manufacturing Systems

An Intelligent Healthcare Management System: A New Approach in Work-order Prioritization for Medical Equipment Maintenance Requests

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