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A new policy for joint optimization of age replacement and spare provisioning has been proposed by incorporating a continuous review (s, S) type inventory policy, where s is the reorder level and S is the maximum stock level. Gives cost formulations for a single operating unit situation and outlines simulation procedure to determine optimal values of the decision variables by minimizing total cost of replacement and inventory. Studies the behaviour of this policy for a large number of case problems and highlights the effects of different cost elements, item failure characteristics and lead time characteristics. Also determines, for all case problems, optimal (s, S) policies to support Barlow‐Proschan age policy. Simulation results clearly indicate that the jointly optimal policy is more cost‐effective than Barlow‐Proschan policy.

The purpose of this paper is to determine optimal replacement threshold and optimal inspection interval for an item subjected to condition-based maintenance (CBM). The primarily assumption is that the item's failure replacement cost depends on the item's degradation state at which failure occurs and/or the time the item fails. The cost of inspection is also taken into account.

The control limit replacement policy framework, already reported by some research referred to in this paper, is first extended to include the non-decreasing failure replacement cost assumption. Then, for alternative inspection intervals, replacement thresholds together with their associated total cost including the inspection cost are computed. By comparing the total costs, the optimal inspection interval and its corresponding optimal replacement threshold are simultaneously identified.

The mathematical formulation required for the determination of optimal replacement threshold and optimal inspection interval for an item subjected to CBM under the assumption of non-decreasing failure cost is provided.

In some practical situations where CBM is implemented, the failure replacement cost may depend on the time the failure happens and/or may depend on the system's degradation state. In addition, inspections often incur cost. Under such circumstances, findings of this paper can be utilized for the determination of optimal replacement threshold and optimal inspection interval for the underlying system.

Using the approach proposed in this paper, one could obtain the optimal replacement threshold and the optimal inspection interval for a system subjected to CBM.

Wind power is an important source of renewable energy and accounts for significant portions in supplying electricity in many countries and locations. The purpose of this paper is to develop a method for wind power system reliability assessment and condition-based maintenance (CBM) optimization considering both turbine and wind uncertainty. Existing studies on wind power system reliability mostly considered wind uncertainty only and did not account for turbine condition prediction.

Wind power system reliability can be defined as the probability that the generated power meets the demand, which is affected by both wind uncertainty and wind turbine failures. In this paper, a method is developed for wind power system reliability modeling considering wind uncertainty, as well as wind turbine condition through health condition prediction. All wind turbine components are considered. Optimization is performed for maximizing availability or minimizing cost. Optimization is also conducted for minor repair activities to find the optimal number of joint repairs.

The wind turbine condition uncertainty and its prediction are important for wind power system reliability assessment, as well as wind speed uncertainty. Optimal CBM policies can be achieved for optimizing turbine availability or maintenance cost. Optimal preventive maintenance policies can also be achieved for scheduling minor repair activities.

This paper considers uncertainty in both wind speed and turbine conditions and incorporates turbine condition prediction in reliability analysis and CBM optimization. Optimization for minor repair activities is studied to find the optimal number of joint repairs, which was not investigated before. All wind turbine components are considered, and data from the field as well as reported studies are used.

Elevator manufacturers are responsible for securing the safety and maintaining the performance, cleanliness and cosmetic appearance of the elevators which they sell.The purpose of this paper is to develop a cost‐optimized after‐sales strategy for the maintenance of an elevator part. First, in order to find an optimum maintenance method, the replacement probability and the inspection probability of the part are theoretically derived using each of the three maintenance methods: Time Based Maintenance (TBM), Condition Based Maintenance (CBM), and Breakdown Maintenance (BM). Then, the approach to plan a cost‐optimized maintenance method is presented and the relationship between the failure characteristics of the part and the cost‐optimized maintenance method is discussed.The results of using the proposed approach are compared with those obtained by Online Quality Engineering (Taguchi methods). Finally, from numerical experiments, it is shown that this approach can provide a more cost‐effective and better maintenance method than the method provided by Online Quality Engineering.

Service systems that require failure rate below a predetermined value usually need maintenance in order to operate at that level of reliability. One major issue in maintenance systems is the optimal maintenance schedule that incurs minimum total cost. Considering fixed inflation rate and failure rate variation after maintenance, an algorithm of balanced maintenance scheduling is developed. The algorithm provides an optimal number of replacement and preventive maintenance to minimize the total maintenance cost over a certain planning period. A numerical example is demonstrated and compared with the results reported by other researchers.

In this paper, an optimal periodic replacement strategy is proposed. This strategy suggests new items to perform replacements at failure. Preventive replacements, scheduled at instants kT (k=1, 2,…) are carried out only if the item's age exceeds a threshold to be determined. Parameters T and b are derived from an optimization model aiming to maximize the steady state availability under budgetary constraints or to minimize the expected total cost per unit of time over an infinite horizon, while the steady state availability must be higher than some given threshold. Costs and durations associated with replacement actions are supposed to be known.

Employs mathematical models to investigate the expected cost rate and the steady state availability with illustrative examples.

Analytical and numerical results have been obtained for a system whose lifetime is distributed according to an Erlang distribution.

The proposed strategy seems more efficient than the basic block replacement strategy aiming to maximize the steady state availability. It is also easy to implement.

This new strategy would appear to be more efficient than the previous basic block replacement strategy.

The purpose of this article is to compare maintenance policies based on Weibull and q-Weibull models.

This paper uses analytical developments, several figures and tables for graphical and numerical comparison. Previously published hydropower equipment data are used as examples.

Models for optimal maintenance interval determination based on q-Weibull distribution were defined. Closed-form expressions were found, and this allows the application of the method with small computational effort.

The use of the q-Weibull model to guide the definition of maintenance strategy allows decision-making to be more consistent with sample data. The flexibility of the q-Weibull model is able to produce failure rate modeling with five different formats: decreasing, constant, increasing, unimodal and U-shaped. In this way, the maintenance strategies resulting from this model should be more assertive.

Expressions for determining the optimal interval of preventive maintenance were deduced from q-Weibull distribution. Expected costs per maintenance cycle of Brazilian hydropower equipment were calculated with q-Weibull and Weibull distributions. These results were compared in terms of absolute values and trends. Although a large number of works on corrective and preventive maintenance have been proposed, no applications of the q-Weibull distribution were found in literature.

The purpose of this paper is to represent replacement policies (rules) in the form of a matrix. Visualization of replacement rules is useful for maintenance records. Matrix representation is more effective than the verbal description usually provided, as it allows better understanding of the specifics of the different replacement rules without careful research of their mathematical models.

This approach employs mathematical models to investigate the simple conditions (requirements) for replacement of system component with illustrative examples. When comparing the different replacement rules a cost structure is applied to takes into account the nature and technology of disassembly assembly actions for the repair unit.

Representation of replacement rules in the matrix form is useful when describing planned replacement models, opportunity replacement models, group replacement models and others, as well as computer modeling of the renewal process. Forming simple conditions for the replacement of system components ensures the total average repair cost is minimized. These conditions can be applied in the early stages of creating a maintenance program for the machine.

Replacement matrices can be specified in a technical manual for maintenance of machines to achieve reliable operation and to reduce repair costs. Replacement matrices can be put into practical use for maintenance records and may be included in the maintenance procedures library of CMMSs. Developed in the paper, the replacement matrix, the conditions for replacement of system components and the cost structure will help engineers to make decisions at the time of repair for assembly units.

Proposed in the paper is a new approach to the visualization of the replacement rules and cost structure which simplifies the analysis of options for repair actions. The proposed technique contributes to the record of maintenance actions and the decision making process for replacement.

This paper develops a model that allows consideration of not only the total maintenance costs but also the overall probability of a system breakdown when determining the time intervals between preventive maintenance activities. Using the model, which assumes that component failures follow a Weibull distribution, managers can determine the required preventive maintenance interval to achieve a desired probability of system failure, and they can calculate the total expected costs of both breakdowns and maintenance actions. The model’s application is illustrated using the impact of four different maintenance policies. The model assures top management that the unavailable system time due to equipment breakdown will be within a specified limit.

The findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.

We have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.

BA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.

There are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.