A preventive maintenance of circular consecutive-k-out-of-n: F systems

2017 ◽  
Vol 34 (6) ◽  
pp. 752-769 ◽  
Author(s):  
Alfonsus Julanto Endharta ◽  
Won Young Yun
Keyword(s):  
Preventive Maintenance ◽  
Continuous Monitoring ◽  
Maintenance Policy ◽  
Expected Cost ◽  
Content Type ◽  
Cost Rate ◽  
Minimal Cut ◽  
Cost Parameters ◽  
The Cost ◽  
Preventive Maintenance Policy

Purpose The purpose of this paper is to develop a preventive maintenance policy with continuous monitoring for a circular consecutive-k-out-of-n: F systems. A preventive maintenance policy is developed based on the system critical condition which is related to the number of working components in the minimal cut sets of the system. If there is at least one minimal cut set which consists of only one working component, the system is maintained preventively (PM) after a certain time interval and the failed components are replaced with the new ones to prevent the system failures. If the system fails prior to the preventive maintenance, the system is correctively maintained (CM) immediately by replacing the failed components. Design/methodology/approach The mathematical function of the expected cost rate for the proposed maintenance policy is derived. The costs of PM, CM, and replacement per component are considered. The optimal maintenance parameter, which is the PM interval, is obtained by enumeration, and the numerical studies are shown with various system and cost parameters. The performance of the proposed policy is evaluated by comparing its expected cost rate to those of the no-PM and age-PM policies. The percentage of cost increase from the no-PM and age-PM policies to the proposed PM policy is calculated and this value can represents how important the continuous monitoring in this policy. Findings The proposed policy outperforms other policies. When the cost of CM is high and the cost of PM is low, the proposed PM policy is more suitable. Research limitations/implications The system consists of identical components and the component failure times follow an exponential distribution. Continuous monitoring is considered, which means that the component states can be known at any time. Three cost parameters, cost of PM, CM, and replacement per component, are considered. Originality/value This paper shows a maintenance problem for circular consecutive-k-out-of-n: F systems. Many studies on this system type focused on the reliability estimation or system design problem. Previous study with this policy (Endharta and Yun, 2015) has been developed for linear systems, although the study used a simulation approach to estimate the expected cost rate. Also, Endharta et al. (2016) considered a similar method for the different types of system, which is linear consecutive-k-out-of-n: F system.

OPTIMAL PERIODIC PREVENTIVE MAINTENANCE SCHEDULES WITH IMPROVEMENT FACTORS DEPENDING ON NUMBER OF PREVENTIVE MAINTENANCES

2007 ◽  
Vol 24 (01) ◽  
pp. 111-124 ◽  
Author(s):  
JAE-HAK LIM ◽  
DONG HO PARK
Keyword(s):  
Preventive Maintenance ◽  
Hazard Rate ◽  
Optimal Schedule ◽  
Maintenance Policy ◽  
Expected Cost ◽  
Cost Rate ◽  
Mathematical Formulas ◽  
Periodic Preventive Maintenance ◽  
Maintenance Schedules ◽  
Preventive Maintenance Policy

This paper considers a periodic preventive maintenance policy under which each preventive maintenance (PM) reduces the hazard rate of the repairable system, while keeping the pattern of hazard rate unchanged. For this model, the hazard rate at a given time t is affected by the improvement factor which depends on the number of PMs conducted until t. In addition to the periodic preventive maintenance, the system undergoes the minimal repair at each failure between the preventive maintenances. We derive mathematical formulas to evaluate the expected cost rate per unit time by computing the expected number of failures depending on the hazard rate of the underlying life distribution of the system. Assuming that the system is replaced by a new one at the N-th preventive maintenance, the optimal values of N and the preventive maintenance period, which minimize the expected cost rate, are solved and thus the best schedules for the periodic preventive maintenance policy are established. Explicit solutions for the optimal schedule for the periodic preventive maintenance are presented when the failure times follow the Weibull distribution.

On preventive maintenance policies: a selection framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Imad Alsyouf ◽  
Sadeque Hamdan ◽  
Mohammad Shamsuzzaman ◽  
Salah Haridy ◽  
Iyad Alawaysheh
Keyword(s):  
Preventive Maintenance ◽  
Fuzzy Ahp ◽  
Critical Component ◽  
Multi Objective Optimization ◽  
Maintenance Policy ◽  
Coolant Pump ◽  
Content Type ◽  
Multi Objective ◽  
Maintenance Policies ◽  
Preventive Maintenance Policy

PurposeThis paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.Design/methodology/approachThe critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.FindingsFor a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.Research limitations/implicationsOnly three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.Practical implicationsThe proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.Originality/valueThis research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.

Condition-Based Maintenance

2016 ◽  
pp. 292-320
Author(s):  
Hao Peng
Keyword(s):  
Preventive Maintenance ◽  
Condition Based Maintenance ◽  
General Idea ◽  
Optimization Models ◽  
Sensor Technology ◽  
Maintenance Policy ◽  
Expected Cost ◽  
Measurement Devices ◽  
Preventive Maintenance Policy ◽  
Random Failures

Condition-Based Maintenance (CBM) is one type of preventive maintenance policy. CBM has attracted lots of attentions of both academia and industry due to the development of advanced sensor technology and measurement devices. The proper implementation of CBM can reduce the frequency of random failures and the expected cost of maintenance during the lifecycle of a system. In this chapter, a brief overview of different maintenance strategies is first provided for the readers who are not familiar with maintenance optimization models. Then several elementary models about CBM will be introduced to help the readers get a general idea of the optimization models in this field.

scholarly journals The Optimal Warranty and Preventive Maintenance Policy for the Four-State System

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Ahmed F. Attia ◽  
Eman D. Abou Elela ◽  
Hany A. Hosham
Keyword(s):  
Steady State ◽  
Markov Process ◽  
Preventive Maintenance ◽  
State System ◽  
Maintenance Policy ◽  
Failure Times ◽  
Multistate System ◽  
Maintenance Policies ◽  
The Cost ◽  
Preventive Maintenance Policy

A complete view for the multistate system considering the four-state system is here introduced. The exponential distribution for failure times and repair times is considered. The steady state availability is established via the Markov process. Different warranty and preventive maintenance policies are introduced, and also the cost of these policies for the manufacturer and the buyer is evaluated.

Opportunistic perfect preventive maintenance policy in presence of masked data

2021 ◽  
pp. 1748006X2110589
Author(s):  
Hasan Misaii ◽  
Firoozeh Haghighi ◽  
Mitra Fouladirad
Keyword(s):  
Preventive Maintenance ◽  
Optimization Problem ◽  
Maintenance Optimization ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Inspection Interval ◽  
Long Run ◽  
Cause Of Failure ◽  
Preventive Maintenance Policy ◽  
Multi Component System

In this paper, the maintenance optimization problem of multi-component system is considered. It is assumed that the exact cause of system failure might be masked. That is, the exact cause of failure is unknown, and we only know that it belongs to a set called mask set. Both opportunistic perfect preventive maintenance (OPPM) and perfect corrective maintenance are considered. Threshold of OPPM and inter-inspection interval are considered as decision parameters which are optimized using long-run cost rate criteria. The applicability of the proposed maintenance policy is investigated using an illustrative example.

Joint design of control chart, production and maintenance policy for unreliable manufacturing systems

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nadia Bahria ◽  
Imen Harbaoui Dridi ◽  
Anis Chelbi ◽  
Hanen Bouchriha
Keyword(s):  
Quality Control ◽  
Control Chart ◽  
Preventive Maintenance ◽  
Buffer Stock ◽  
Maintenance Policy ◽  
Content Type ◽  
Stock Size ◽  
Periodic Preventive Maintenance ◽  
Preventive Maintenance Policy

PurposeThe purpose of this study is to develop a joint production, maintenance and quality control strategy involving a periodic preventive maintenance policy.Design/methodology/approachThe proposed integrated policy is defined and modeled mathematically.FindingsThe paper focuses on finding simultaneously the optimal values of the preventive maintenance period, the buffer stock size, the sample size, the sampling interval and the control chart limits, such that the expected total cost per time unit is minimized.Practical implicationsThe paper attempts to integrate in a single model the three main aspects of any manufacturing system: production, maintenance and quality. The considered system consists of one machine subject to a degradation process that directly affects the quality of products. The process and product quality control is carried out using an “x-bar” control chart. In the proposed model, a preventive maintenance action is performed every α inspections of product quality in order to reduce the shift rate to the “out-of-control” state. A corrective maintenance action is undertaken once the control limits are exceeded. In order to palliate perturbations caused by the stopping of the machine to undergo maintenance actions, a buffer stock is built up to ensure the continuous supply of the subsequent machine. The main goal of this work is to develop a model that captures the underlying link between the preventive maintenance policy, the buffer stock size and the parameters of an “x-bar” control chart used to control the quality of the product. Numerical experiments and a study of the effects of the input parameters variation on the obtained results are performed.Originality/valueThe existing models that simultaneously consider maintenance, inventory and control charts consist of a condition-based maintenance (CBM) policy. Periodic preventive maintenance (PM) has not been considered in such models. The proposed integrated model is original, in that it links production through buffer stocks, quality through a control chart and maintenance through periodic preventive maintenance (different practical settings and modeling approach than when CBM is used). Hence, this paper addresses practical situations where, for economic or technical reasons, only systematic periodic preventive maintenance is possible.

scholarly journals The post-warranty random maintenance policies for the product with random working cycles

2021 ◽  
Vol 23 (4) ◽  
pp. 726-735
Author(s):  
Lijun Shang ◽  
Haibin Wang ◽  
Cang Wu ◽  
Zhiqiang Cai
Keyword(s):  
Preventive Maintenance ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Working Cycle ◽  
Maintenance Policies ◽  
Reliability Performance ◽  
The Cost

Advanced sensors and measuring technologies make it possible to monitor the product working cycle. This means the manufacturer’s warranty to ensure reliability performance can be designed by monitoring the product working cycle and the consumer’s post-warranty maintenance to sustain the post-warranty reliability can be modeled by tracking the product working cycle. However, the related works appear seldom in existing literature. In this article, we incorporate random working cycle into warranty and propose a novel warranty ensuring reliability performance of the product with random working cycles. By extending the proposed warranty to the post-warranty maintenance, besides we investigate the postwarranty random maintenance policies sustaining the post-warranty reliability, i.e., replacement last (first) with preventive maintenance (PM). The cost rate is constructed for each post-warranty random maintenance policy. Finally, sensitivity of proposed warranty and investigated polices is analyzed. We discover that replacement last (first) with PM is superior to replacement last (first).

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