Maintenance Strategy Selection Research Articles

Maintenance strategy selection using AHP and ANP algorithms: a case study

PurposeThe purpose of this paper is to demonstrate the use of two general purpose decision‐making techniques in selecting the most appropriate maintenance strategy for organizations with critical production requirements.Design/methodology/approachThe Analytical Hierarchical Process (AHP) and the Analytical Network Process (ANP) are used for the selection of the most appropriate maintenance strategy in a local newspaper printing facility in Turkey.FindingsThe two methods were shown to be effective in choosing a strategy for maintaining the printing machines. The two methods resulted in almost the same results. Both methods take into account the specific requirements of the organization through its own available expertise.Practical implicationsThe techniques demonstrated in this paper can be used by all types of organizations for selecting and adopting maintenance strategies that have higher impact on maintenance performance and hence overall business productivity. The two methods are explained in a step‐by‐step approach for easier adaptation by practitioners in all types of organizations.Originality/valueThe value of the paper is in applying AHP and ANP decision‐making methodologies in maintenance strategy selection. These two methods are not very common in the area of maintenance, and hence add to the pool of techniques utilized in selecting maintenance strategies.

Reliability-Centered Maintenance for Wind Turbines Based on Statistical Analysis and Practical Experience

The concept of reliability-centered maintenance (RCM) is applied to the two wind-turbine models Vestas V44-600 kW and V90-2MW. The executing RCM workgroup includes an owner and operator of the analyzed wind turbines, a maintenance service provider, a provider of condition-monitoring services, and wind-turbine component supplier as well as researchers at academia. Combining the results of failure statistics and assessment of expert judgement, the analysis is focused on the most critical subsystems with respect to failure frequencies and consequences: the gearbox, the generator, the electrical system, and the hydraulic system. This study provides the most relevant functional failures, reveals their causes and underlying mechanisms, and identifies remedial measures to prevent either the failure itself or critical secondary damage. This study forms the basis for the development of quantitative models for maintenance strategy selection and optimization, but may also provide a feedback of field experience for further improvement of wind-turbine design.

Application of Hybrid VIKOR Model in Selection of Maintenance Strategy

This paper focuses on the use of Fuzzy Analytic Hierarchy Process (FAHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian (VIKOR) to select an optimum maintenance strategy for a textile industry. In the proposed methodology, first the weight of each criterion is calculated by using improved AHP with fuzzy set theory to overcome the problems of unbalanced scale of judgments, uncertainty and imprecision in the pair-wise comparison process and then the VIKOR method is applied to compensate the imprecise ranking of the AHP in the selection of maintenance strategy. The real case study is conducted for a textile industry to illustrate the utilization of the proposed model for the maintenance strategy selection problem. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to make sure that the result of the proposed model can be acceptable. A sensitivity analysis is also conducted to show the validity of the proposed model. The paper gives an insight into multi criteria decision-making (MCDM) techniques to select an optimum maintenance strategy for a process industry using a case study.Request access from your librarian to read this article's full text.

An improved MCDM method for maintenance approach selection: A case study of auto industry

Article history: Received July 25, 2011 Received in Revised form September, 10, 2011 Accepted 12 September 2011 Available online 18 September 2011 In the current competitive environment, managers have been making attempts to convert organizations under their supervision into competitive and responsive through creating capability of timely delivery of quality products and services. In line with this, maintenance as a system plays an important role in achieving these goals. The maintenance strategy selection is a kind of multiple criteria decision-making (MCDM) problem, which requires considering a large number of complex factors as multiple evaluation criteria. A robust MCDM method should consider the interactions among criteria. The analytic network process (ANP) is a relatively new MCDM method, which can deal with all kinds of interactions systematically. Moreover, the Decision Making Trial and Evaluation Laboratory (DEMATEL) not only can convert the relations between cause and effect of criteria into a visual structural model, but also can be used as a way to handle the inner dependences within a set of criteria. Hence, this paper proposes an effective solution based on a combined ANP and DEMATEL approach to help vehicle companies that need to evaluate and select maintenance strategies. © 2012 Growing Science Ltd. All rights reserved.

Maintenance Strategy Evaluation Using ANP and Goal Programming

An optimal maintenance strategy mix is necessary for increasing availability and reliability levels of production facilities without significantly increasing operational costs. The selection of maintenance strategies is a typical Multiple Criteria Decision-Making (MCDM) problem with conflicting goals. Consideration of interdependence among the criteria and alternative policies for maintenance strategy provides valuable cost savings and greater benefits for any hybrid flow systems. For any decision maker, it is convenient to prioritize the criteria of MCDM problems and goals of goal programming problems in fuzzy terms. This paper presents an integrated approach for maintenance policy selection, using fuzzy Analytic Network Process (ANP) within a Goal Programming, based on fuzzy preemptive priority where goal hierarchies are specified in different levels of fuzzy importance. To overcome the criticism of inconsistency, unbalanced scale of judgments and uncertainty in the pair-wise comparison process, criteria weights are determined using modified fuzzy LLSM method.

Rolling stock maintenance strategy selection, spares parts’ estimation, and replacements’ interval calculation

The purpose of this paper is to permit an approach for: (1) selecting a maintenance strategy for rolling stock and (2) obtaining possible spare parts’ quantities and replacement intervals for the components of rolling stock. The methodology adopts an analytic network process (ANP) technique for the strategy evaluation, because ANP considers the important interactions among evaluation factors. The ANP’s result decides upon a proper rolling stock maintenance strategy formed by various combinations of preventive maintenance (PM) and corrective maintenance (CM). The ratio PM/CM, obtained by ANP, can help to predict spare parts’ quantities of the components of rolling stock. The empirical result also indicates that preventive maintenance should be much more valued than corrective maintenance. In addition, safety is considered the most crucial factor for the selection of a rolling stock maintenance strategy. The fruit of this study serves as a reference for railway system operators when evaluating their rolling stock maintenance strategy and also when estimating their spare parts’ quantities and replacement intervals for specific components of the rolling stock.

Extension of the ELECTRE method based on interval-valued fuzzy sets

Decision-making is the process of finding the best option among the feasible alternatives. In classical multiple criteria decision-making (MCDM) methods, the ratings and the weights of the criteria are known precisely. However, if decision makers cannot reach an agreement on the method of defining linguistic variables based on the fuzzy sets, the interval-valued fuzzy set theory can provide a more accurate modeling. In this paper, the interval-valued fuzzy ELECTRE method is presented aiming at solving MCDM problems in which the weights of criteria are unequal, using interval-valued fuzzy set concepts. For the purpose of proving the validity of the proposed model, we present a numerical example and build a practical maintenance strategy selection problem.

Selection of maintenance policy for textile industry using hybrid multi‐criteria decision making approach

PurposeThe purpose of this paper is to focus on the use of analytic hierarchy process (AHP) under fuzzy environment and technique for order preference by similarity to ideal solution (TOPSIS) to select an optimum maintenance strategy for a textile industry.Design/methodology/approachFirst by using improved AHP with fuzzy set theory, the weight of each criterion is calculated to overcome the criticism of unbalanced scale of judgments, uncertainty, and imprecision in the pair‐wise comparison process. Then this paper introduces a model that integrates improved fuzzy AHP with TOPSIS algorithm to support maintenance strategy selection decisions.FindingsAn efficient pair‐wise comparison process and ranking of alternatives can be achieved for maintenance strategy selection through the integration of AHP with fuzzy set theory and TOPSIS.Originality/valueThe paper points out a new insight of multi‐criteria decision making techniques to select optimum maintenance policy for a process industry with the use of a case study.

Extension of VIKOR method based on interval-valued fuzzy sets

Decision making is the process of finding the best option among the feasible alternatives. In classical multiple-criteria decision-making (MCDM) methods, the ratings and the weights of the criteria are known precisely. However, if decision makers cannot reach an agreement on the method of defining linguistic variables based on the fuzzy sets, the interval-valued fuzzy set theory can provide a more accurate modeling. In this paper, the interval-valued fuzzy VIKOR method is presented, aiming at solving MCDM problems in which the weights of criteria are unequal, using interval-valued fuzzy set concepts. For application and verification, this study presents a numerical example and builds a practical maintenance strategy selection problem to verify our proposed method. Moreover, a comparison is made between the interval-valued fuzzy VIKOR and other adapted MCDM interval-valued fuzzy number-based.

A Combined Approach for Maintenance Strategy Selection

A Combined Approach for Maintenance Strategy Selection

Multi‐criteria decision‐making approach to evaluate optimum maintenance strategy in textile industry

Purpose – The purpose of this paper is to focus on the use of analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to select an optimum maintenance strategy for a textile industry.Design/methodology/approach – The relative importance of multiple evaluation criteria and the extension of the TOPSIS are prioritized using AHP. The TOPSIS method is applied to compensate for the imprecise ranking of the AHP in the selection of a maintenance policy mix.Findings – An efficient ranking of alternatives can be achieved for maintenance strategy selection through the combination of AHP and TOPSIS.Originality/value – The paper highlights a new insight into multi‐criteria decision‐making techniques to select an optimum maintenance policy for a process industry with the use of a case study.

Cost-effective selection and multi-period scheduling of pavement maintenance and rehabilitation strategies

An optimization methodology is developed for determining the most cost-effective maintenance and rehabilitation (M&R) activities for each pavement section in a highway pavement network, along an extended planning horizon. A multi-dimensional 0–1 knapsack problem with M&R strategy-selection and precedence-feasibility constraints is formulated to maximize the total dollar value of benefits associated with the selected pavement improvement activities. The solution approach is a hybrid dynamic programming and branch-and-bound procedure. The imbedded-state approach is used to reduce multi-dimensional dynamic programming to a one-dimensional problem. Bounds at each stage are determined by using Lagrangian optimization to solve a relaxed problem by means of a sub-gradient optimization method. Tests for the proposed solution methodology are conducted using typical data obtained from the Texas Department of Transportation.

Maintenance Strategy Selection: a comparison between Fuzzy Logic and Analytic Hierarchy Process

Continued pressure on companies to reduce costs and improve customer satisfaction has resulted in increasingly detailed examinations of maintenance practices and strategies. At the same time, the role of maintenance nowadays is shifting from the traditional necessary evil to a business chance. However, even if research in this area is on the rise nowadays, little work has been done in order to provide a model for the selection of the suitable maintenance strategy for each piece of equipment. This paper shows a comparison between two techniques, Analytic Hierarchy Process and Fuzzy Logic, as Multi Criteria Decision Methods useful for selecting the most suitable maintenance strategy. The two models have been applied to a real case study carried out in an Italian manufacturing firm.

The model for selection of a maintenance strategy for municipal buildings

This paper considers a problem of the evaluation of different strategies for the proper maintenance of municipal buildings, including public and private property, with the emphasis on rapidly changing environmental conditions. One of the important aspects of problem in the area of building maintenance in many countries is the lack of sound long-term strategies aimed at adapting buildings to constantly changing requirements. This aspect is particularly acute in the municipal buildings sector. The main findings of paper are the theoretical model for rational maintenance strategy selection and the system of criteria for comparison of building maintenance strategies are suggested.

Fuzzy set solutions for optimal maintenance strategy selection

Selecting optimal maintenance strategy under fuzzy environment is not a trivial task. This paper presents an illustration of multi-criteria maintenance strategy selection under fuzzy environment. Three most common maintenance strategies and eight maintenance decision criteria have been considered and most appropriate/ optimal strategy selection process is demonstrated using three different techniques/ methods. Fuzzy linguistic terms have been used to rate and weigh the maintenance decision criteria. Linguistic terms/ variables are represented by triangular fuzzy sets/ number and fuzzy set operations have been carried out using α– cut method. The basic technique used is rating and ranking method using fuzzy set theory wherein ratings of alternatives/ strategies is determined first and then ranking is carried out to decide the optimal strategy. Other methods i.e. ranking fuzzy sets using cardinal utilities and by maximizing and minimizing sets are also established to confirm our choice of optimal maintenance strategy.

A structured approach for the assessment of system availability and reliability using Monte Carlo simulation

PurposeThis paper proposes a method to model and assess the availability and reliability of a system when numerous factors such as system complexity, wide range of failure modes, environment, and sustainability may influence system behaviour.Design/methodology/approachThe approach for reliability/availability study is using continuous time stochastic simulation (Monte Carlo simulation) and is based on seven steps for covering logical phases from system description to simulation result discussion. The feasibility and benefits of this approach are shown in a case study on cogeneration plant.FindingsOwing to the factors influencing the system behaviour, the opportunity to carry out system availability/reliability assessment through analytical models will be many times very restrictive. Thus a general approach to this problem is proposed based on Monte Carlo (stochastic) simulation. The simulation of the system's life process will be carried out in the computer, and estimates will be made for the desired measures of performance. The simulation will then be treated as a series of real experiments, and statistical inference will then be used to estimate confidence intervals for the performance metrics.Practical implicationsIndividuals, companies as well as society in general are becoming more and more dependent on increasingly complex technical systems. Moreover, failure of these complex systems often causes a major loss of service with potentially serious consequences (i.e. critical risk). Thus their dependability with its facets such as reliability, availability, safety has become an important issue. For example, the ability of reliability/availability assessment of such systems is invaluable in industrial domains. Indeed reliability/availability assessment is used for various purposes such as maintenance strategy selection, maintenance planning, production planning, risk and cost evaluations. To face with this complexity, the existing analytical models are not well adapted to carry out system modelling and assessment due mainly to assumptions that are difficult to validate. This paper looks into this issue by proposing a generic approach based on Monte Carlo (stochastic) simulation.Originality/valueThe Monte Carlo simulation method allows one to consider various relevant aspects of systems operation that cannot be easily captured by analytical models. The utilisation of this method is growing for the assessment of overall plants availability and the monetary value of plant operation.

Utility of spatially variable damage performance indicators for improved safety and maintenance decisions of deteriorating infrastructure

Corrosion of concrete and structural steel is a primary cause of deterioration of built infrastructure. This deterioration can cause reduced load capacity and on-going and costly maintenance and repair. Typically, this corrosion can be seen on structures to be spatially variable. Few studies have considered the effect of spatial variability of corrosion on structural performance and its effect on structural reliability. Random fields may be used to consider the temporal and spatial deterioration effects on structural performance, and performance indicators may include probability of extent of damage or structural reliability. In the present article, four case studies showing the benefits of using spatially variable damage performance indicators are discussed, for structural steel and reinforced concrete structures. It will be shown how spatially variable damage performance indicators will allow for more informed decision-making about the level of safety and the selection of optimal maintenance and repair strategies.

Value-driven maintenance planning for a production plant

Maintenance involves maintaining and securing the equipment and systems in, or restoring them to, a state in which they can perform the required functions. The challenge for maintenance planning is to identify appropriate objects and tasks for preventive maintenance and ensure that there are adequate resources for the repair actions. In this paper we will present a maintenance planning approach, called value-driven maintenance planning (VDMP), to emphasise the fact that the objectives of the plant are the reference points for specifying functional requirements for the equipment locations and equipment. The three basic phases of the VDMP planning approach are: (i) the definition of the fundamental, strategic and maintenance (means) objectives of the production plant, (ii) the classification of equipment locations (including one or several equipment items) into maintenance classes, each associated with a functional requirement specification, and (iii) the selection of maintenance strategies and maintenance tasks (including timing) for equipment assigned to the equipment locations. Feedback of the operational experience is crucial for the application of the maintenance planning approach. As a consequence, the approach is developed to support the continuous improvement of the cost effectiveness of maintenance rather than planning of the initial maintenance programme of a new plant. Analysis techniques are presented and challenges of application are discussed. The application of the VDMP approach to a gasification plant in Finland is also presented.

Privatization of Low-Volume-Road Maintenance Management

In 2001, the Malaysian government privatized the maintenance of its federal road network. The network was divided into four maintenance regions. The southern region consists of about 4,000 km of roads; of that, about 1,800 km is under the Federal Land Development Authority (FELDA) scheme. Under the privatization contract, the concessionaire is required to carry out periodic, routine, and emergency maintenance of all roads within the FELDA scheme. The implementation of the privatized maintenance management program for the low-volume road network is discussed. The current management program includes road condition data collection, maintenance strategy and pavement materials selection, and use of innovative pavement maintenance technology. Data collection is carried out by using a high-speed road data collection survey vehicle; structural assessment is made by using the falling weight deflectometer, coring and dynamic cone penetrometer, and a conventional visual condition survey. An inventory system was also developed. Components of this privatized maintenance contract are discussed in detail.

The Selection of a Suitable Maintenance Strategy for Wind Turbines

Common maintenance strategies applied to wind turbines include ‘Time-Based’ which involves carrying out maintenance tasks at predetermined regular-intervals and ‘Failure-Based’ which entails using a wind turbine until it fails. However, the consequence of failure of critical components limits the adequacy of these strategies to support the current commercial drivers of the wind industry. Reliability-Centred Maintenance (RCM) is a technique used mostly to select appropriate maintenance strategies for physical assets. In this paper, a hybrid of an RCM approach and Asset Life-Cycle Analysis technique is applied to Horizontal-Axis Wind Turbines to identify possible failure modes, causes and the resultant effects on system operation. The failure consequences of critical components are evaluated and expressed in financial terms. Suitable Condition-Based Maintenance activities are identified and assessed over the life-cycle of wind turbines to maximise the return on investment in wind farms.