scholarly journals Optimization of the maintenance planning of a multi-component system

2018 ◽  
Vol 200 ◽  
pp. 00011
Author(s):  
Issam Mallouk ◽  
Badr Abou El Majd ◽  
Yves Sallez
Keyword(s):  
High Reliability ◽  
Maintenance Planning ◽  
Multi Objective Optimization ◽  
Maintenance Policy ◽  
Swarm Optimization ◽  
Multiobjective Particle Swarm Optimization ◽  
Maintenance Policies ◽  
The Cost ◽  
The Mathematical Model ◽  
Multi Component System

The vehicle’s maintenance costs, uptime and security are the most important goals for owners and transport companies, but these goals are conflictual and the major cause for delays is related to the maintenance policies. The main objective of transporters is to respond properly to their customer’s demands. In order to deal with this competitiveness, transport companies are working to improve the management of their fleets by focusing in particular on vehicle maintenance, which impact the vehicles uptime, and generate the most important cost. In addition, a vehicle maintenance policy aims to avoid failures and keep the vehicle up and safe. This objective is reached by ensuring a high reliability; otherwise, an unexpected failure of a component can cause vehicle down and can affect the entire sub-system while generating costs. In this paper, we propose a new maintenance policy based on multi-objective optimization. This problem is solved using the Speed-Constrained Multiobjective Particle Swarm Optimization (SMPSO) for an instance of 18 components and 20 vehicles. First, we give an overview of the existing techniques used for vehicle’s maintenance policy, then we present the mathematical model that describes the cost of maintenance and the level of safety. Numerical experiments are presented to demonstrate the efficiency of our approach.

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.

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.

A STOCHASTIC MODEL FOR HYBRID MAINTENANCE POLICIES EVALUATION AND OPTIMIZATION

2001 ◽  
Vol 08 (03) ◽  
pp. 233-248 ◽  
Author(s):  
BRUNO CASTANIER ◽  
ANTOINE GRALL ◽  
CHRISTOPHE BÉRENGUER
Keyword(s):  
Stochastic Process ◽  
Stochastic Model ◽  
Average Cost ◽  
Numerical Experiments ◽  
System State ◽  
Maintenance Policy ◽  
Long Run ◽  
Running Cost ◽  
Maintenance Policies ◽  
The Cost

We propose a hybrid maintenance policy which combines periodic (age-based or time-based) regulation-based inspections with aperiodic condition-based inspection/replacements for a stochastically and gradually deteriorating system. The stationary laws of the deterioration state of the maintained system are derived in order to evaluate the long-run average running cost on an infinite span generated by the proposed combined policy. A computable expression of the average cost is established using the regenerative or semi-regenerative properties of the stochastic process describing the maintained system state. The behavior of the proposed maintenance is illustrated through numerical experiments and it is shown that the cost incurred by the optimized combined policy is lower than the cost generated by the regulation-based maintenance alone.

MAINTENANCE POLICIES FOR A TWO-UNITS SYSTEM: A COMPARATIVE STUDY

2002 ◽  
Vol 09 (02) ◽  
pp. 127-149 ◽  
Author(s):  
ANNE BARROS ◽  
ANTOINE GRALL ◽  
CHRISTOPHE BÉRENGUER
Keyword(s):  
Numerical Experiments ◽  
Maintenance Cost ◽  
Iteration Algorithm ◽  
Maintenance Policy ◽  
Weak Point ◽  
System A ◽  
Policy Iteration Algorithm ◽  
Maintenance Policies ◽  
The Cost ◽  
Maintenance Plan

This paper considers the age-based maintenance of a two-identical components system with economic dependences. Two existing approaches are presented and compared. One is a maintenance policy of (N,n)-type. It is very close to the optimal policy among all possible policies but difficult to optimize: Policy Iteration Algorithm is needed. The aim of the paper is to investigate if there are cases for which a simpler policy than those of (N,n)-type can be sufficient in terms of maintenance cost. A second approach proposed in literature (derived from the time-based block replacement one) is simpler but not sufficient in any situations. Some numerical experiments and an analysis of the stochastic behavior of the two-identical components system allows us to propose a third policy (Policy P). This third maintenance plan is simplified from the second one. It compensates for its weak point which is to be very expensive when the cost of replacement for one component is close to the cost of replacement for both components. Moreover it is possible to generalize this third policy from a two-identical components system to a n-identical components system. The performances analysis of the policy is based on numerical experiments.

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).

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

Case Study—Failure Analysis of a Multiplexer

2016 ◽  
Author(s):  
Michael Woo ◽  
Marcos Campos ◽  
Luigi Aranda
Keyword(s):  
Failure Analysis ◽  
High Reliability ◽  
Component Failure ◽  
Root Cause ◽  
Knowing That ◽  
Cause Of Failure ◽  
The Cost

Abstract A component failure has the potential to significantly impact the cost, manufacturing schedule, and/or the perceived reliability of a system, especially if the root cause of the failure is not known. A failure analysis is often key to mitigating the effects of a componentlevel failure to a customer or a system; minimizing schedule slips, minimizing related accrued costs to the customer, and allowing for the completion of the system with confidence that the reliability of the product had not been compromised. This case study will show how a detailed and systemic failure analysis was able to determine the exact cause of failure of a multiplexer in a high-reliability system, which allowed the manufacturer to confidently proceed with production knowing that the failure was not a systemic issue, but rather that it was a random “one time” event.

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