Data

1. Chandrahas, et al., International Journal of Advanced Engineering Research and Studies E-ISSN2249–8974
Int. J. Adv. Engg. Res. Studies/IV/II/Jan.-March,2015/256-258
Proceedings of BITCON-2015 Innovations For National Development
National Conference on : Innovations In Mechanical Engineering For Sustainable Development
Research Paper
MAINTENANCE STRATEGY AND DECISION MAKING –
AHP METHOD
Chandrahas1
, Santosh Kumar Mishra2
and Deepak Mahapatra2
Address for Correspondence
1
Student, 2
Faculty at Bhilai Institute of Technology, Durg (CG) India
ABSTRACT:
Maintenance strategy plays a very important role in all kind of manufacturing industries. Each maintenance strategy has their
characteristics, importance and drawbacks. Performance of a machine depends on the type of maintenance strategies
employed on it. Machines used in industries need proper maintenance because failure of machine may cause the production
loss. Maintenance strategy may vary from one machine to another machine because of the various conflicting factors like
safety, cost, customer satisfaction etc. Factors affecting machines performance need to identify and control. Use of
inappropriate maintenance strategy may increase the maintenance cost. Increase in maintenance cost will increase the
production cost. Selection of a maintenance strategy to a particular machine or group of machines is a problem of decision
making and it is always a challenging task for maintenance Manager/Engineer. By using the decision making tools like
AHP, this problem can be solved. Use of AHP method also facilitates to calculate the weight of factors through which
decision maker can analyze the difference between actual condition and required condition. Present research work shows
that the problem of selecting an optimum maintenance strategy to a machine can be overcome by using decision making tool
(AHP).
KEYWORDS: Analytical Hierarchy Process, Decision Making, Maintenance Strategy.
1. INTRODUCTION:
According to Jureen Thor et al. (2013), Maintenance
has emerged since the construction of physical
structures such as ships and machines. In general,
maintenance is defined as the combination of all
technical and administrative actions, including
supervision and action indented to retain the machine
or restore it to a state in which it can perform a
required function. Effective maintenance ultimately
aims to determine suitable action’s that can keep
machine performance at acceptable level and extend
the life cycle of the machine. Different types of
maintenance alternatives have been proposed to
achieve the ultimate goal. However, a maintenance
policy implemented in a similar machine but in
different manufacturing environments may not
produce similar results because of various operating
factors such as humidity, temperature and work load.
In addition, decision making in maintenance
selection is often accompanied by diverse constraints
and economic perspectives. Examples of these
constraints include operator safety issues,
government regulation, resource limitation and
budget, consequently the selection of a suitable
maintenance policy becomes a crucial decision
making process to obtain high levels of success for
the firm beneficiaries in manufacturing industry.
2. REVIEW OF RESEARCH WORKS ON
MAINTENANCE STRATEGY SELECTION -
In last few decades there were lots of research work
had been done all over the world on maintenance
strategy selections. Few of them are introduced in
this research work. M. Bevilacqua et al. (March
2000), the research work is all about the selection of
maintenance strategy in a plant which is still in
construction phase. Possible alternatives are
considered preventive, condition based, corrective
and opportunistic maintenance. There are
approximate 200 facilities for which best
maintenance policy have to select. The machines are
clustered in three homogeneous groups after a
criticality analysis based on internal procedures of
the oil refinery. With AHP technique, several aspects,
which characterize each of the above mentioned
maintenance strategies, are arranged in hierarchic
structure and evaluated using only a series of pair
wise judgments. Massinio Bertolin et al. (2005)
presents a Lexicographic goal programming (LGP)
approach to define the best strategies for the
maintenance of critical centrifugal pumps in an oil
refinery for each pump failure mode , the model
allows to take into account the maintenance policy
Borden in terms of inspection or repair and in terms
of the manpower involved , linking them to
efficiency risk as peats quantified as in FMECA
methodology through the use of the classic parameter
occurrence , severity and detestability , evaluated
through an adequate application of AHP technique.
Ling Wang et al. (2007) analyzed deal with the
uncertain judgment of decision makers, a fuzzy
modification of the AHP method is applied as an
evaluation tool where uncertain and imprecise
judgments of decision makers are translated into
fuzzy numbers. In order to avoid fuzzy priority
calculation and fuzzy ranking procedures in the
traditional fuzzy AHP methods, a new fuzzy
prioritization method is proposed. This fuzzy
prioritization method can derive crisp priorities from
a consistent or inconsistent fuzzy judgment matrix by
solving an optimization problem with non linear
constraints. Maria Scocorro et al. (2008) proposes
the use of a multi- criteria technique, namely the
analysis hierarchy process, as a potential decision
making method for use in management maintenance
processes. In this case the problem corneous the
selection of a parts clearing system for diesel engine
maintenance. A hierarchical structure is built for the
prequalification of the criteria and the alternatives
within the system. By applying the analytical
hierarchy process, the criteria can be prioritized and
the alternatives can be organized in descending order
so that the best parts clearing system may be selected.
Ming- feng yang et al. 2008. In this paper an AHP
approach is used evaluating food quality management
of Bakery Sector. In this approach triangular numbers
were introduced into the conventional AHP in order
to improve the degree of judgments of decision
maker(s). Using of AHP approach to evaluating food
quality Management of Bakery sector alternative
results in the following two major advantages

2. Chandrahas, et al., International Journal of Advanced Engineering Research and Studies E-ISSN2249–8974
Int. J. Adv. Engg. Res. Studies/IV/II/Jan.-March,2015/256-258
(i)Numbers are preferable to extend the range of crisp
comparison matrix of the conversion matrix of the
convection AHP method. (ii)Adoption of numbers
can allow decision makers to have freedom of
estimation regarding the food quality management of
Bakery sector selection. Mansoore Momani et al.
(2011) studied the selection of maintenance strategies
in Electro Fan Company. It is studied that the
evaluation of maintenance strategies for each piece of
equipment is a multiple criteria decision making
(MCDM) problem. To deal with the uncertain
judgment of decision makers are translated into fuzzy
numbers. A specific example of selection of
maintenance strategies in this company with the
application of proposed fuzzy TOPSIS method is
given, showing that the preventive maintenance
strategy is the most suitable for equipment. Jureen
Thor et al. July 2013 reviewed and compared
analytic hierarchy process, elimination and compared
analytic reality, simple additive weighting and
technique for order preference by similarity to ideal
solution. The comparisons were based on the aspects
of consistency problem structure, concept, core
process and accuracy of final results.
3. FIELD OF MCDM (AHP) METHOD:
In our day to day life from morning market to
business market we need to make decisions with
some genuine logics and sense. The purpose is to get
better outputs and results. Now a day’s decision
making tools are getting rapidly popular in various
fields like Maintenance strategy selection, Supply
chain management, Agriculture, Medical Science,
Food industry, Education, Automobile industry,
Project selection etc.
4. COMPARATIVE STUDY OF
MAINTENANCE STRATEGIES:
When there is need to identify the various
alternatives to take in consideration for the selection
of best maintenance strategy, it is always helpful to
compare the alternatives by important factors like
philosophy, reliability level, percentage in use,
advantages, disadvantages etc. It simplifies the
understanding between various points and conditions.
Table no.1 Comparative study of maintenance strategies
S.N. Factors Corrective Maintenance Preventive Maintenance Condition Based Maintenance
1. Nature  Run-to-failure  Time based maintenance  Predictive maintenance,
monitor as per assets condition
2. Basic
Philosophy
 Allow machinery to run to
failure
 Repair or replace damaged
equipment when obvious
problem occur.
 Schedule maintenance
activities at pre-determined
time intervals.
 Repair or replace damaged
equipment before obvious
problem occur.
 Schedule maintenance activities
when mechanical or operational
conditions warrant.
 Repair or replace damaged
equipment before obvious
problem occur.
3. On the basis of
Reliability
 Small parts and
equipment.
 Non-critical equipment
 Equipment unlikely to fail.
 Redundant systems
 Equipment subjected to wear.
 Consumer-able equipment
 Equipment with known
failure pattern.
 Manufacturer
recommendations
 Equipment with random failure
patterns.
 Critical equipment
 Equipment not subjected to
wear.
 System which failure may be
induced by incorrect preventive
maintenance.
4. Advantages  Low cost
 Less staff
 Cost effective in many
capital intensive processes.
 Flexibility allows for the
adjustment of maintenance
periodically.
 Increased component life
cycle.
 Energy savings
 Reduced equipment or
process failure.
 Estimated 12-18% cost
savings over CM.
 Increased component
operational life/availability.
 Decrease in equipment or
process downtime.
 Decrease in costs for parts and
labors.
 Better product quality
 Improved worker and
environmental safety.
 Energy savings.
 Improved worker morale.
 Estimated 8-12% cost savings
over PM.
5. Disadvantages  Increased cost due to
unplanned downtime of
equipment.
 Increased labor cost,
especially if overtime
needed.
 Cost involved with repair
or replacement of
equipment.
 Possible secondary or
process damage from
equipment failure.
 Catastrophic failure still
likely to occur.
 Labor intensive
 Includes performance of
unneeded maintenance.
 Potential for incidental
damage to components in
conducting unneeded
maintenance.
 Increased investment in
diagnostic equipment.
 Increased investment in staff
training.
 Savings potential not readily
seen by management.
6. Maintenance
Strategy used
in industry.
 55% Reactive
maintenance used in
industry.
 31% preventive maintenance
used in industry.
 12% predictive maintenance
used in industry.
7. Equation Breakdown cost = labor +
downtime
Preventive Maintenance cost
= labor + downtime due to
(PM) cost planned shutdown
Condition Based Maintenance
Cost = labor + downtime due to
(CBM) cost planned shutdown
8. Example  Lubricate motors when
they become noisy or
vibrations occur.
 Lubricate pumps every 2000
in hours.
 Conduct scans on pumps and
panels to determine if and when
work is required.

3. Chandrahas, et al., International Journal of Advanced Engineering Research and Studies E-ISSN2249–8974
Int. J. Adv. Engg. Res. Studies/IV/II/Jan.-March,2015/256-258
5. SELECTION OF CRITERIA AND SUB-
CRITERIA
Selection of criteria is also a very important factor in
the process of selecting the best maintenance
strategy. Criteria’s which highly influence the
performance of machine or to achieve the goal of
company, need to be analyzed very carefully. Multi-
Criteria Decision Making tools facilitate to rank these
criteria’s with respect to the others. Most general
criteria and sub criteria for manufacturing industries.
According to Ling Wang (2007), the important
criteria’s and sub-criteria’s are classified in table
form.
Table no.2 Classifying Criteria and Sub-Criteria
Criteria Sub- Criteria
Cost (A)
Cost of poor maintenance practices (A1)
Cost of using spare parts (A2)
Staff training cost (A3)
Safety (B)
Environmental effects (B1)
Personnel safety (B2)
Value –Added(C)
Role of professional specialist (C1)
Spare parts quality and availability (C2)
Customer satisfaction (C3)
Equipment and Technology(D) Fault Identification (D1)
Feasibility (D2)
Table no.3 Comparisons between Criteria’s
6. STRATEGY OF DATA COLLECTION
Data collection is a very important task in the
selection of maintenance strategy by using the
MCDM Methods. Appropriate well planned data
sheet must take all the required information from the
expert when ask for any decision. Inappropriate way
of data collection may lead to fail the purpose of
analysis. When a question is asked to an expert there
must be no any confusion related to understanding
meaning of question. Logic must be arises in the
mind of the decision maker at the time of answering.
A sample paper of questionnaire is added in this
research paper (table no. 3). Data collected from
sample questionnaire are required to put in matrix
form and then after it can be calculated by AHP
process. Tools like MATLAB etc can be used for
matrix calculation for large size of data calculation.
7. CONCLUSIONS:
This research paper aims to show how a typical
problem of maintenance strategy selection can be
simplified by using a decision making tools. Using
the advantages and facilities of MCDM methods
helps to control the factor which influences to
achieve the goal of company. In this paper review of
various researches suggest that large scope of
applicability of MCDM methods. Comparative study
of alternatives can help to understand the condition of
problem and also at the time of decision making i.e.
to fulfill questionnaire part for data collection.
Selection of any criteria is also a challenging task but
it can be well estimated by review of various research
studies at different conditions in different companies.
It can be concluded at the end of this research paper
that for the general problem of maintenance strategy
selection above steps can be taken in the account and
along with this sensitivity analysis can also be
implemented so that influence in output can be
measured by changing the criteria weight.
REFERENCES:
1. Al-Najjar, B. and I. Alsyouf, 2003, selecting the most
efficient maintenance approach using fuzzy multiple
criteria decision making. International J. Production
Economics, pp: 84.
2. Alsyouf Imad 2009, Maintenance practices in Swedish
Industries: survey results, department of mechanical
engineering , school of technology and design, Vaxjo
University, SE-35195, vaxjo Sweden.
3. Artiba, Abdhakim; riane, dr. Fauad(2005), Maintenance
strategy and reliability optimization Bradford, GBR;
Emerald Group publication ltd, 2005,p6
4. Asma M. A. Bahurmoz (2006) The Analytic Hierarchy
Process: A Methodology for Win- Win Management
JKAU: Econ. & Adm., Vol. 20 No. 1, pp: 3-16 (2006
A.D./1427 A.H.)
5. Jurrenthor, siewhong ding, shahrulkamarddin (2013),
comparison of multi-criteria decision making methods
from the maintenance alternative selection perspective ,
International journal of Engineering and Science,
ISSN(e)-2319-1813, ISSN(p)-2319- 1805
6. Mansour Momeni, Mohammad Reza Fathi, Mohammad
Karimi Zarchi and Sirous Azzizollahi (2011), A Fuzzy
TOPSIS-Based Approach to Maintenance Strategy
Selection: A Case Study, Middle-East Journal of
Scientific Research 8(3):699-706, 2011
7. Mark Velasquez1 and Patrick T. Hester2(2013) An
Analysis of Multi-Criteria Decision Making Methods,
International Journal of Operations Research Vol. 10,
No. 2, 56066 (2013)
8. Massimo Bertolini, Maurizio Bevilacqua(2005), A
combined goal programming – AHP approach to
maintenance selection problem, Reliability Engineering
and System Safety 91 (2005) 839-848
9. M. Bevilacqua, M. Braglia(2000), The analytic
hierarchy process applied to maintenance strategy
selection, Reliability Engineering and System Safety 70
(2000) 71–83
10. Ling Wang, Jian Chu, Jun Wu, 2007, Selection of
optimum maintenance strategies based on a fuzzy
analytic hierarchy process, Int. j. Production
Economics 107(2007) 151-163-50
Note: This Paper/Article is scrutinised and reviewed by
Scientific Committee, BITCON-2015, BIT, Durg, CG, India
Factor Factor Weight
Factor
More important than Equal Less important than
Cost 9 7 5 3 1 3 5 7 9 Safety
Cost 9 7 5 3 1 3 5 7 9 Add- Value
Cost 9 7 5 3 1 3 5 7 9 Equipment and Technology
Safety 9 7 5 3 1 3 5 7 9 Add-value
Safety 9 7 5 3 1 3 5 7 9 Equipment and Technology
Add-
Value
9 7 5 3 1 3 5 7 9 Equipment and Technology