Optimal CBM policy with two sampling intervals

2017 ◽  
Vol 23 (1) ◽  
pp. 95-112 ◽  
Author(s):  
Farnoosh Naderkhani ◽  
Leila Jafari ◽  
Viliam Makis
Keyword(s):  
Average Cost ◽  
Hazard Function ◽  
Sampling Interval ◽  
Mean Residual Life ◽  
Maintenance Policy ◽  
Economic Point ◽  
Content Type ◽  
Proposed Model ◽  
Sampling Intervals ◽  
Optimal Maintenance Policy

Purpose The purpose of this paper is to propose a novel condition-based maintenance (CBM) policy with two sampling intervals for a system subject to stochastic deterioration described by the Cox’s proportional hazards model (PHM). Design/methodology/approach In this paper, the new or renewed system is monitored using a longer sampling interval. When the estimated hazard function of the system exceeds a warning limit, the observations are taken more frequently, i.e., the sampling interval changes to a shorter one. Preventive maintenance is performed when either the hazard function exceeds a maintenance threshold or the system age exceeds a pre-determined age. A more expensive corrective maintenance is performed upon system failure. The proposed model is formulated in the semi-Markov decision process (SMDP) framework. Findings The optimal maintenance policy is found and a computational algorithm based on policy iteration for SMDP is developed to obtain the control thresholds as well as the sampling intervals minimizing the long-run expected average cost per unit time. Research limitations/implications A numerical example is presented to illustrate the whole procedure. The newly proposed maintenance policy with two sampling intervals outperforms previously developed maintenance policies using PHM. The paper compares the proposed model with a single sampling interval CBM model and well-known age-based model. Formulas for the conditional reliability function and the mean residual life are also derived for the proposed model. Sensitivity analysis has been performed to study the effect of the changes in the Weibull parameters on the average cost. Practical implications The results show that considerable cost savings can be obtained by implementing the maintenance policy developed in this paper. Originality/value Unlike the previous CBM policies widely discussed in the literature which use sequential or periodic monitoring, the authors propose a new sampling strategy based on two sampling intervals. From the economic point of view, when the sampling is costly, it is advantageous to monitor the system less frequently when it is in a healthy state and more frequently when it deteriorates and enters the unhealthy state.

Sequential imperfect preventive maintenance policy with random maintenance quality under reliability limit

2011 ◽  
Vol 225 (8) ◽  
pp. 1926-1935 ◽  
Author(s):  
Z Wang ◽  
J Yang ◽  
G Wang ◽  
G Zhang
Keyword(s):  
Failure Rate ◽  
Preventive Maintenance ◽  
Average Cost ◽  
Numerical Control ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Proposed Model ◽  
Optimal Maintenance ◽  
Average Cost Rate ◽  
Optimal Maintenance Policy

To determine the optimal maintenance number for a system with random maintenance quality in infinite time horizon, a sequential imperfect preventive maintenance model considering reliability limit is proposed. The proposed model is derived from the combination of the Kijima type virtual age model and the failure rate adjustment model. Maintenance intervals of the proposed model are obtained through an iteration method when both failure rate increase factor and maintenance restoration factor are random variables with a uniform distribution. The optimal maintenance policy is presented by minimizing the long-run average cost rate. A real numerical example for the failures of numerical control equipment is given to demonstrate the proposed model. Finally, a discussion is presented to show how the optimal average cost rate depends on the different cost parameters. The results show that in order to satisfy the practical requirements of high reliability, it is necessary and worthwhile to consider the system's reliability limit in preventive maintenance practice.

Joint reliability based design and periodic preventive maintenance policy for systems sold with warranty

2016 ◽  
Vol 22 (1) ◽  
pp. 2-17 ◽  
Author(s):  
M.N. Darghouth ◽  
Daoud Ait-Kadi ◽  
Anis Chelbi
Keyword(s):  
Average Cost ◽  
Numerical Procedure ◽  
Optimal Solution ◽  
Design Stage ◽  
Maintenance Policy ◽  
Content Type ◽  
Warranty Period ◽  
Reliability Based Design ◽  
Total Average Cost ◽  
Total Average

Purpose – The authors consider a system which is a part of a complex equipment (e.g. aircraft, automobile, medical equipment, production machine, etc.), and which consists of N independent series subsystems. The purpose of this paper is to determine simultaneously the system design (reliability) and its preventive maintenance (PM) replacements periodicity which minimize the total average cost per time unit over the equipment useful life, taking into account a minimum required reliability level between consecutive replacements. Design/methodology/approach – The problem is tackled in the context of reliability-based design (RBD) considering at the same time the burn-in of components, the warranty commitment and the maintenance strategy to be adopted. A mathematical model is developed to express the total average cost per time unit to be minimized under a reliability constraint. The total average cost includes the cost of acquiring and assembling components, the burn-in of each component, preventive and corrective replacements performed during the warranty and post-warranty periods. A numerical procedure is proposed to solve the problem. Findings – For any given set of input data including components reliability, their cost and the costs of their preventive and corrective replacements, the system design (reliability) and the periodicity of preventive replacement during the post-warranty period is obtained such as the system’s total average cost per time unit is minimized. The obtained results clearly indicate that a decrease in the number of PM actions to be performed during the post-warranty period increases the number of components to be added at each subsystem at the design stage. Research limitations/implications – Given that the objective function (cost rate function) to be minimized is non-linear and involves several integer variables, it has not been possible to derive the optimal solution. A numerical procedure based on a heuristic approach has been proposed to solve the problem finding a nearly optimal solution for a given set of input data. Practical implications – This paper offers to manufacturers a comprehensive approach to look for the most economical combination of the reliability level to be given to their products at the design stage, on one hand, and the PM policy to be adopted, on the other hand, given the offered warranty and service for the products and reliability requirements during the life cycle. Originality/value – While the RBD problem has been largely treated, most of the published works have focussed on the development or the improvement of solving techniques used to find the optimal configuration. In this paper the authors provide a more comprehensive approach that considers simultaneously RBD, the burn-in and warranty periods, along with the maintenance policy to be adopted. The authors also consider the context of products whose component failures cannot be rectified through repair actions. They can only be fixed by replacement.

Maintenance policy selection model – a case study in the palm oil industry

2014 ◽  
Vol 25 (3) ◽  
pp. 415-435 ◽  
Author(s):  
Siew-Hong Ding ◽  
Shahrul Kamaruddin ◽  
Ishak Abdul Azid
Keyword(s):  
Palm Oil ◽  
Selection Process ◽  
Oil Industry ◽  
Second Phase ◽  
Maintenance Policy ◽  
Content Type ◽  
Policy Selection ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy

Purpose – An optimal maintenance policy is key to the improvement of the availability and reliability of a system at an acceptable level without a significant increase in investment. However, the selection process is a complicated task because it requires in-depth knowledge on maintenance policies and on the technical requirements of maintenance. The difficulties and complexity of the selection process arise from the combination of conflicting maintenance constraints such as available spares, size of workforce, and maintenance skills. The paper aims to discuss these issues. Design/methodology/approach – The proposed maintenance policy selection (MPS) model is separated into three major phases. The first phase identifies the critical system (CS) based on failure frequency. The failure mechanism in the CS is then analyzed by using a failure mode and effect analysis in the second phase. In the third phase, a multi-criteria decision making method, called the technique for order of preference by similarity to ideal solution, is adopted to identify an optimal maintenance policy that can minimize the failures. Findings – Through a case study, preventive maintenance was selected as the optimal maintenance policy for the reduction of system failures. The results obtained from the case study not only provide evidence of the feasibility and practicability of the developed model, but also test the acceptability and rationale of the developed model from the industry perspective. Valuable knowledge and experience from employees were extracted and utilized through the proposed model to rank the optimal maintenance policy based on the capability to reduce failure. Originality/value – The practicality of the MPS model is justified through an implementation in the palm oil industry. The application of the MPS model can also be extended to other manufacturing industries.

Opportunistic maintenance (OM) as a new advancement in maintenance approaches

2014 ◽  
Vol 20 (2) ◽  
pp. 98-121 ◽  
Author(s):  
Hasnida Ab-Samat ◽  
Shahrul Kamaruddin
Keyword(s):  
Current Trend ◽  
Replacement Policy ◽  
Practical Significance ◽  
Clear Understanding ◽  
Maintenance Policy ◽  
Opportunistic Maintenance ◽  
Content Type ◽  
Research Areas ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy

Purpose – This paper reviews the literature on opportunistic maintenance (OM) as new advance maintenance approach and policy. The purpose of this paper is to conceptually identify common principle and thereby provide absolute definition, concept and characteristics of this policy. Design/methodology/approach – A conceptual analysis was conducted on various literatures to clarify a number of principle and concepts as a method for understanding information on OM. The analysis involves the process of separating the compound terms used in the literatures into a few parts, analyse them and then recombining them to have more clear understanding of the policy. Findings – The paper discussed the maintenance approach, genealogy, principle, concept and applications of OM both in numerical analysis and real industry. OM policy is developed based on combination of age replacement policy and block replacement policy and in practical; OM is applied as the combination of corrective maintenance which is applied when any failure occurred, with preventive maintenance (PM) – a planned and scheduled maintenance approach to prevent failure to happen. Any machine shutdown or stoppages due to failure is the “opportunity” to conduct PM even though it is not as planned. The characterization of OM was provided in order to present its theoretical novelty for researchers and practical significance for industries. Practical implications – To date, there is no publication that reviews the OM in-depth and provides clear understanding on the topic. Therefore, this paper aims to show lineage of OM and the current trend in researches. This discussion will pave the way of new research areas on this optimal maintenance policy. Clear definition and principle of OM provided in this paper will trigger interest in its practicality as well as aid industries to understand and conduct OM in operation plant. Originality/value – This paper discussed the available literature about OM in various perspectives and scopes for further understanding of the topic by maintenance management professionals and researchers. Therefore, OM can be widely studied and applied in real industry as it is an effective and optimal maintenance policy.

scholarly journals A study on an optimal replacement policy for a deteriorating system under partial product process

10.26524/cm65 ◽  
2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Govindaraju P ◽  
Rajendiran R
Keyword(s):  
Explicit Expression ◽  
Average Cost ◽  
Replacement Policy ◽  
Partial Product ◽  
Maintenance Policy ◽  
Optimal Replacement ◽  
Optimal Replacement Policy ◽  
Optimal Maintenance ◽  
Random Shocks ◽  
Optimal Maintenance Policy

In this paper, we consider an optimal maintenance policy for a reparable deteriorating system subject to random shocks. For a reparable deteriorating system, the repair time by a partial product process and the failure mechanism by a generalized δshock process. Develop an explicit expression of the ling run average cost per unit time under N policy is studied.

Imperfect maintenance model for estimating aircraft fleet availability

2017 ◽  
Vol 89 (2) ◽  
pp. 338-346 ◽  
Author(s):  
Aleksandar Knezevic ◽  
Ljubisa Vasov ◽  
Slavisa Vlacic ◽  
Cedomir Kostic
Keyword(s):  
Intermediate Level ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Content Type ◽  
Reliability Parameters ◽  
Optimal Maintenance ◽  
Maintenance Policies ◽  
Optimal Maintenance Policy ◽  
Maintenance Model

Purpose The purpose of this paper is to define conditions under which improved availability of fleet of G-4 jet trainers is obtained, and optimization of intermediate-level maintenance through imperfect maintenance model application. This research has been conducted based on available knowledge, and experience gained by performing intermediate-level maintenance of Serbian Air Force aircrafts. Design/methodology/approach Analysis of the data collected from daily maintenance reports, and the analysis of maintenance technology and organization, was performed. Based on research results, a reliability study was performed. Implementation of imperfect maintenance with its models of maintenance policies (especially a quasi-renewal process and its treating of reliability and optimal maintenance) was proposed to define new maintenance parameters so that the greater level of availability could be achieved. Findings The proposed methodology can potentially be applied as a simple tool to estimate the present maintenance parameters and to quickly point out some deficiencies in the analyzed maintenance organization. Validation of this process was done by conducting a reliability case study of G-4 jet trainer fleet, and numerical computations of optimal maintenance policy. Research limitations/implications The methodology of the availability estimation when reliability parameters were not tracked by the maintenance organization, and optimization of intermediate-level maintenance, has so far been applied on G-4 jet trainers. Moreover, it can be potentially applied to other aircraft types. Originality/value Availability estimation and proposed optimization of intermediate maintenance is based on a survey of data for three years of aircraft fleet maintenance. It enables greater operational readiness (due to a military rationale) with possible cost reduction as a consequence but not as a goal.

Progressive maintenance policy for multiple repairable systems with imperfect maintenance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Garima Sharma ◽  
Rajiv Nandan Rai
Keyword(s):  
Power Plants ◽  
Maintenance Cost ◽  
Mean Residual Life ◽  
Time Interval ◽  
Imperfect Maintenance ◽  
Repairable Systems ◽  
Maintenance Policy ◽  
Data Set ◽  
Content Type ◽  
Maintenance Policies

PurposeDegradation of repairable components may not be similar after each maintenance activity; thus, the classic (traditional-time based) maintenance policies, which consider preventive maintenance (PM), age-based maintenance and overhauls to be done at fixed time interval, may fail to monitor the exact condition of the component. Thus, a progressive maintenance policy (PMP) may be more appropriate for the industries that deal with large, complex and critical repairable systems (RS) such as aerospace industries, nuclear power plants, etc.Design/methodology/approachA progressive maintenance policy is developed, in which hard life, PM scheduled time and overhaul period of the system are revised after each service activity by adjusting PM interval and mean residual life (MRL) such that the risk of failure is not increased.FindingsA comparative study is then carried out between the classic PM policy and developed PMP, and the improvement in availability, mean time between failures and reduction in maintenance cost is registered.Originality/valueThe proposed PMP takes care of the equipment degradation more efficiently than any other existing maintenance policies and is also flexible in its application as the policy can be continuously amended as per the failure profile of the equipment. Similar maintenance policies assuming lifetime distributions are available in the literature, but to ascertain that the proposed PMP is more suitable and applicable to the industries, this paper uses Kijima-based imperfect maintenance models. The proposed PMP is demonstrated through a real-time data set example.

OPTIMAL MAINTENANCE POLICY TO SUPPORT THE OPERATION OF MANUFACTURING WITH MINIMAL AND DELAYED REPAIR

2009 ◽  
Vol 16 (03) ◽  
pp. 235-247 ◽  
Author(s):  
GWO-LIANG LIAO ◽  
BOR-LING SHAW
Keyword(s):  
Imperfect Maintenance ◽  
Minimal Repair ◽  
Maintenance Policy ◽  
Delayed Repair ◽  
Proposed Model ◽  
Special Cases ◽  
Optimal Period ◽  
Optimal Maintenance ◽  
Periodic Preventive Maintenance ◽  
Optimal Maintenance Policy

This work presents a periodic preventive maintenance (PM) model for a repairable system that undergoes minimal repair or delayed repair at each failure to keep a plant operating. Two PM types are performed, i.e. imperfect PM and perfect PM. The likelihood that PM is perfect depends on the number of imperfect maintenance activities have been performed since the last renewal cycle. Mathematical formulae for expected cost per unit time are developed. The optimal period for periodic PM, which minimizes cost, is identified. Various special cases are considered, including the maintenance learning effect. A numerical example demonstrates the effectiveness of the proposed model.

scholarly journals A model for a dynamic preventive maintenance policy

2000 ◽  
Vol 13 (4) ◽  
pp. 321-346 ◽  
Author(s):  
Christiane Cocozza-Thivent
Keyword(s):  
Simulated Annealing ◽  
Stochastic Model ◽  
Preventive Maintenance ◽  
Average Cost ◽  
Simulated Annealing Algorithm ◽  
Maintenance Policy ◽  
Optimal Maintenance ◽  
Annealing Algorithm ◽  
Optimal Maintenance Policy ◽  
Preventive Maintenance Policy

This paper exhibits a stochastic model which describes the evolution of a material submitted to inspections. When an inspection takes place, a decision depending on the observed state of the material is taken. If the material is in “not too bad” state, no service is rendered, only the date of the next inspection is chosen. If the material is in a “bad” working state, a service takes place. Roughly speaking, the failure rates of the material are constant, the inspection and repair rates are general. We define the average cost function corresponding to the utilization of this material and we show how it can be computed. Then we determine the inspection rates which give the optimal maintenance policy using a simulated annealing algorithm. We observe experimentally that the best durations between inspections are deterministic ones.

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