Maintenance Strategy Selection
Maintenance strategy selection has been studied extensively where various decision making
approaches were proposed based on multiple criteria. This paper presents a review of the multi-
criteria decision making approaches used in maintenance strategy selection and attempts to address
which approaches were prevalently applied and which evaluating criteria were paid more attention.
This work also provides evidence that the multi-criteria approach facilitate better decision making in
maintenance strategy selection.
1. Introduction
Maintenance has been defined as the combination of technical and associated administrative
actions in tended to retain an item or system in, or restore it to, a state in which it can perform
its required function (ISO 14224: 2004). A proper maintenance needs technical skills,
techniques, methods to properly utilize the assets like factories, power plants, vehicles,
equipment’s and machines. The key objective of maintenance is to ensure system function
(availability, efficiency and product quality), system life (asset management), and system
safety with low energy consumption. Poorly maintained machines or equipment’s may lead
to random breakdowns causing unavailability for production or service. This generally results
into lower utilization and hence the lower productivity. Therefore, maintenance is directly
linked to the competitiveness and profitability of an organization. Several maintenance
approaches (strategies) have been implemented by practitioners or suggested by
intellectuals. Maintenance strategy is a systematic approach to upkeep the facilities and
equipment and it may vary from facility to facility. It involves identification, researching and
execution of many repairs, replace and inspect decisions (Kelly, 1997) and is concerned with
formulating the best life plan for each unit of the plant, in coordination with production and
other functions concerned. It describes what events (e.g. failure, passing of time, condition)
trigger what type of maintenance action (inspection, repair, or replacement). Selecting the
best maintenance strategy depends on several factors such as the goals of maintenance, the
nature of the facility or the equipment to be maintained, work flow patterns (process focus,
product focus), and the work environment. Most widely used maintenance strategy include
Reliability Centered Maintenance (RCM), Total Productive Maintenance (TPM), Business
Centered Maintenance (BCM), terotechnology, capital asset management, and integrated
logistic support (ILS).
2. Review of Maintenance Strategies
Basically there are two maintenance approaches namely Corrective maintenance (CM) and
Preventive maintenance (PM). Corrective Maintenance is used after failure of equipment is
occurred and Preventive (or predictive) Maintenance is carried away before the failure of
equipment. Most widely adopted maintenance strategies like run to failure, time based preventive
maintenance, condition based maintenance, predictive maintenance, Total productive
maintenance, reliability centered maintenance are briefly reviewed next.
Corrective Maintenance
It is also referred as, failure based maintenance, breakdown maintenance or run to failure
strategy. It is the original maintenance strategy appeared in industry). In this strategy an item is
allowed to fail before maintenance is implemented. This is appropriate when the consequence of
failure are small (Example, light bulb) It can be used where the failure of equipment do not have
a greater impact on availability or service for productive use of an organization. However, such
failure based maintenance often may cause serious damage of related facilities, personnel and
environment. In this strategy, the task of the repair/ maintenance team is to restore the facility to
a state in which it can perform the required function as early as possible
Predictive Maintenance
It is a planned maintenance approach where failure or break down of facilities is avoided.
Basically, this approach tries to forecast or predict the wear and tear or life of equipment by using
different approaches and accordingly recommends a corrective action. Fault prediction facilitate
maintenance engineers the possibility to plan for the maintenance. In general, the amount of
equipment failure can be reduced if the preventive maintenance strategies are correctly selected,
especially the condition-based/predictive maintenance. Most commonly referred strategies in the
literature are time based PM and CBM
Time-based Preventive Maintenance: In this approach maintenance is scheduled in advance to
prevent failure. It focuses on preventing failures through replacing components at particular time.
It assumes that the machine component life is predictable, and maintenance is based on hours of
run or calendar time elapsed. This is suitable for repeatable degradation modes, e.g wear process
or constant rate corrosion. In this strategy replacement or repair at a fixed time after the
installation of facility is carried out which is generally independent of its condition. The time period
used to construct a maintenance schedule can be either calendar time or component running
time. Component is replaced at a fixed time, or at failure whichever occurs first. In spite of
preventive approach some failure may occur because of uncertainty of the failure distribution
which is occasionally shorter than the maintenance interval. Recently a maintenance management
decision model to revise PM interval by considering current machine state for non-repairable
components has been reported (R. Ahmed, 2011).
Condition-based maintenance (CBM): In this strategy maintenance decision is made depending
on the measured data. Vibration monitoring, lubricating analysis and ultrasonic testing are the
commonly used approaches to collect the data. Based on the data analysis whenever the
monitoring level value exceeds the normal the component is either repaired or replaced. This
strategy is mostly applied for rotating and reciprocating machines like turbines, centrifugal pumps,
compressors, etc. The use of CBM may lead to appreciable reductions in production cost & capital
investment and increments in the quality rate, profits, and market share. But limitations in data
coverage and quality reduce the effectiveness and accuracy of the condition-based maintenance
strategy (Al-Najjar and Alsyouf, 2003). Lawrence compared condition-based PM with the
traditional statistical-reliability (S-R-based PM approach and found that condition based PM gives
better results (Lawrence et al., 1995).
Other two commonly referred maintenance approaches for improving the productivity of an
organization are Total Productive maintenance (TPM) and Reliability centered maintenance
(RCM). These are briefly given next.
Total Productive Maintenance (TPM)
The prime objective of total productive maintenance are to maximize equipment effectiveness
and productivity Nakajima, S. (1988), and eliminate all machine losses, create a sense of ownership
in equipment operators through a program of training and involvement, promote continuous
improvement through small group activities involving production, engineering, and maintenance
personnel. Each enterprise has its own unique definition and vision for TPM (John Campbell 1995).
But in most cases there are common elements and themes. These are Asset strategy,
Empowerment, Resources Planning and scheduling, Systems and Procedures, Measurement,
Continuous improvement Teams, Processes.
Reliability Centered Maintenance (RCM)
It is a methodology that determines what must be done to ensure that the asset continues
fulfilling its intended functions in its present operating context defined by Moubray (2000). RCM
was initiated in the U.S airline industry in the eatrly 1960s in response to rapidly increasing
maintenance costs, poor availability, and concern over the effectiveness of traditional time-based
preventive maintenance. RCM based program takes into account business requirements and
objectives so that the required productivity goal can be achieved. The success of this approach
depends on the availability of failure data, analysis methods, and operating experience to achieve
its target. RCM has implementation difficulties due to unavailability of plant failure data. RCM
does not make full provision for the use of Condition Monitoring techniques (Al-Najjar 1997).
Recently, life cycle risk map (LCRM) has been proposed as a maintenance (for transmission
equipment) strategy for for individual equipment (Arisa Takehara 2008). In this approach, author
has developed a map that plots the transition of aging risk of equipment over its lifetime, under a
specific maintenance strategy considering cost and demonstrated that LCRM is useful for deriving
the optimal overhaul strategy (timing and cost of overhaul over the whole life of the equipment
under study).
3. Selection/Application of Maintenance Strategy
Various multi-criteria decision making approaches have been proposed for maintenance
strategy selection such as Analytic Hierarchy Process (AHP), fuzzy set theory, Genetic
Algorithm (GA), mathematical programming,
factor analysis, simple multi-attribute rating technique (SMART). AHP has been used as a
multi-criteria tool by most of the authors, either independently or in the combination with
other approach. Multi-criteria approach consists of finite set of alternatives among which a
decision maker has to select or rank; a finite set of criteria weighted according to their
importance. In addition, a decision matrix consists of evaluation of each alterative with
respect to each criterion using a suitable measure. The evolution ratings are then, aggregated
taking into account the weights of the criteria, to get a global evaluation of each alternative
and a total ranking of the alternatives. AHP the most widely referred multi-criteria approaches
is briefly described next followed by the review of literature. AHP is a multi-criteria decision-
making method developed by Saaty (Saaty, 1982). AHP aims at quantifying relative weights
for a given set of criteria on a ratio scale. Two features of AHP differentiate it from other
decision-making approaches. One, it provides a comprehensive structure to combine the
intuitive rational and irrational values during the decision making process. The other is its
ability to judge the consistency in the decision-making process. A number of applications of
AHP have been published in the literature indicating its widespread use in industry and
government organizations, for product development, planning, facility location, resource
allocation, market selection and portfolio selection (Vargas, 1990). It is also possible to
incorporate sensitivity analysis into the AHP model to answer different `what-if' questions: for
example, what happens if the importance of one criterion is doubled or if one more supplier
joins the evaluation process. Bevilacqua used AHP for selecting the best maintenance strategy
for an important Italian oil refinery (an Integrated Gasification and Combined Cycle plant).
Five possible alternatives are considered: preventive, predictive, condition-based, corrective
and opportunistic maintenance (M. Bevilacqua, 2000). Al-Najjara also used a combination of
AHP and fuzzy to predict most cost effective maintenance strategy approach, however, the
author has not considered the importance criterion of maintenance time (Al-najjara, 2003).
AHP with Fuzzy Logic control has been proposed to provide fixed rules and flexible strategies
to support the decision maker in addressing the issue of how assets should be maintained.
That is, whether to run to failure, to upgrade operator skills, to maintain on a fixed time basis,
or to design out the causes of failures, based on the prioritized focus (A.W. Libib, 2004). Author
further proposed a FuzzyDMG approach to determine what type and when a maintenance
strategy has to be implemented to facilitate the responsiveness of a manufacturing system to
the changing environment (A.W. Libib, 2008). Different maintenance strategies - corrective,
time-based, condition-based, and predictive - for different equipment have been evaluated
by using a fuzzy-AHP method (Ling Wang, 2007). Similarly, Shyjith proposed a combination of
AHP and TOPSIS to select suitable maintenance policy for a textile spinning mill ring frame unit
(K. Shyjit, 2008). Recently, Anhua Peng and Zhiming Wang compared fuzzy approach with
TOPSIS (Technique for Order Preference by Similarities to Ideal Solution) and commented that
fuzzy approach is better suited to address the ambiguity and uncertainty part of the decision
making (Anhua Peng and Zhiming Wang, 2011). A combination of AHP, TOPSIS, and VIKOR
methodologies was used to select the most effective maintenance strategy for non-safety
category of failures in aircraft systems (Alirza Ahmadi, 2011). Similarly, Sunil Dutta proposed
a fuzzy logic and AHP multi-criteria approach to select maintenance strategy for transmission
system of military vehicle (Sunil Dutta, 2011) and Bertolini presented a combined AHP &
lexicographic goal programming (GP) approach to select the best policies for the maintenance
of critical centrifugal pumps in an oil refinery (Bertolini and Bevilacqua, 2006). In another
approach, author decided the best maintenance strategy by utilizing the combination of two
techniques of factor analysis and AHP. Firstly authors tied to recognize key factors from
amongst effective factors and then making a hierarchy structure and evaluation of strategies
(M.S. Zaeri, 2007). In addition to the AHP, other tools are also reported in evaluating and
selecting the maintenance strategy. For example, the use of Genetic Algorithm for different
situations has been proposed to address the least-cost part replacement problem (Dragan A.
Savic, 1995), and a case study of a power station coal transportation system (Yu Liu, 2010).
Azizollah used fuzzy delphi method for selecting best maintenance strategy (Azizollah Jafari,
2008). Similarly, attempts being made to address the maintenance policy selection by using
simulation approach. It has been used by the researchers to compare, evaluate or validate
maintenance policies (Burton, J.S, 1989, Boschian, V, 2009). Satoshi used simulation approach
that enabled robots to undergo preventive maintenance at optimal intervals and corrective
maintenance each time they fail. Through simulation experiments, author demonstrated the
effectiveness of the optimal maintenance strategy is investigated (Satoshi Hoshino 2011).
Hennequin proposed a combination of simulation with fuzzy logic to optimize defective
preventive maintenance and remedial steps necessary to carried out on single equipment
(Hennequin, 2009). Burhanuddin proposed a structured Decision Support System for
maintenance management by benchmarking contractors in failure-based maintenance by
using AHP. The approach was demonstrated by an example from the food processing factories
in Malaysia (M. A. Burhanuddin, 2011). Three dimensions namely maintenance technique,
maintenance orgnization and maintenance reach has been used in decision making to select
an optimal maintenance strategy and the same is explained with a case study for wind turbine
industry (Stefan Gassner (2003). Pierre used wait until system down, constant monitoring and
corrective maintenance, purely preventive maintenance and combination of corrective and
preventive maintenance strategies based on the lowest Life cycle Cost by using Markov
modeling approach (Pierre Dersin, 2008).
4. Conclusion
Maintenance strategy selection has been studied extensively in the literature. In this work an
attempt has been made to review the most widely used maintenance strategies as well as the
tool. It has been found that authors used various approaches to demonstrate the approach
suitable in a particular paradigm. Most of the authors exhibited their approach with the help
of a real life example. The efforts clearly show that the systematic approach towards the
maintenance of equipment’s and facilities is gaining more and more importance in achieving
the competitive advantage. From the review we can state that multi-criteria approach in
selecting or decision making helps decision maker in better decision making and getting better
insight into the problem situation. Corrective maintenance, Preventive maintenance and
Condition based maintenance are the most commonly used approach towards the effective
maintenance management. AHP, a multi-criteria tool that helps in combining quantitative and
qualitative criteria, find out relative weights and also to understand the consistency on part
of decision maker is the most referred approach in evaluating and selecting the maintenance
strategies
