Iman Ajripour - 7th International Conference on Management Studies (ICMS-2021,) June, 05 - Eurokd
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7th International Conference on Management Studies
(ICMS-2021,) June, 05
Iman Ajripour
www.EUROKD.com
Author’s Photos
ICMS‐2021 2
•
Author’s short biographies
Iman Ajripour is a Ph.D. candidate of management
science at the University of Miskolc‐Hungary. He is
currently working on Multi‐Criteria Decision Making
Techniques and Strategic Planning. He has 6 years of
experience as an expert in project planning,
production planning, and strategic planning in two
big companies. He has published more than 10
national and international conference and journal
papers. He has also published the book “Expert
Choice Software Guide”. He has been a reviewer in
the Internation Journal of Applied Research In
Industrial Engineering.
ICMS‐2021 3
Introduction
• One of the main aspects of manufacturing factories is accessibility to
required spare parts. To increase efficiency and decrease the time of
machines' failure in manufacturing factories, the required spare parts
should be available in the factory's warehouse. One of the main challenges
of warehouse strategic management in manufacturing companies is
determining the optimal inventory level of each spare part. To manage
and control inventories in a factory’s warehouse, categorizing inventory
items is recommended.
• One of the most common methods which has been applied for
categorizing spare parts in a warehouse is ABC. To classify inventory items
several criteria like lead time, cost of lacking parts, sensitivity, price,
consumption rate, etc. are important but ABC only considers one criterion
“monetary value of annual consumption”.
• Applying Multi‐Criteria Decision Making (MCDM) could be an appropriate
solution to classify spare parts based on different criteria.
• The main goal of this study is to strategically manage some spare parts in
a factory’s warehouse by integrating AHP, TOPSIS, and BWM.
ICMS‐2021 4
The Literature Review
• A review of past literature has shown that there are extensive
studies to strategically manage a warehouse inventories, some of
which are theoretical, some practical, and case studies.
• One of the simple and primary methods to manage factories
warehouse and classify inventories is the ABC method, which is
based on only one criterion, the monetary value of the annual
consumption of spare parts. Reid (1987) used the traditional ABC
method to classify several items in a hospital.
• Duchessi et al. (1988) presented a two‐criteria (inventory cost and
sensitivity) model to classifying spare parts.
• A new multi‐criteria approach was introduced by Braglia, et al.
(2004) to define the best spare parts inventory management
strategy.
• Liu (2006) categorized items by applying data envelopment
analysis.
ICMS‐2021 5
The Literature Review
• Ferreira et al. (2018) proposed a multi‐criteria decision structure for
management of maintenance spare parts. Criticality of equipment,
demand forecast, logistic characteristics were considered as the main
indicators. Fuzzy AHP is applied.
• Inventories critically evaluated and prioritized by Antosz and Ratnayake
(2019). AHP technique was applied to classify inventories.
• To improve the ABC classification Bhattacharya et al. (2007) designed an
integrated model that includes a distance‐based multi‐criteria consensus
framework based on TOPSIS method.
• Bhattacharya et al. (2007) introduced a way of categorizing inventory
items employing TOPSIS technique and compared the model with other
ABC categorization technique.
• Shahin and Gholami (2014) used multi‐criteria and TOPSIS to manage a
warehouse by classification of inventories in an Iranian petrochemical
factory.
• Kaabi et al.(2015) applied TOPSIS and continuous VNS for multi‐criteria
inventory classification.
ICMS‐2021 6The Literature Review
• Kaabi et al.(2018) proposed hybrid classification models based on
both Genetic Algorithm (Metaheuristics) and two MCDM methods
(Weighted Sum (WS) and TOPSIS to carry out the ABC inventory
classification.
• Shannon’s entropy, TOPSIS, and goal programming are respectively
used to determine the weight of criteria which are effective in the
inventory items categorization, calculations of each item value, and
its classification based on Pareto’s principle (Kheybari et al., 2019).
• Although Best Worth Method (BWM) is applied in different fields
of study (e.g. Celik & Gul, 2021; Alkharabsheh et al., 2019; Moslem
et al., 2019; Palanisamy et al., 2020; Wang et al., 2020; Torkayesh et
al., 2021; Mei & Chen, 2021; Pamučar et al., 2021). None of the
previous research used the method in the field of inventory
classification and strategic management of warehouses.
ICMS‐2021 7The Study
• The main purpose of this study is to manage warehouse
inventories in an Iranian petrochemical plant. Due to the huge
amount of inventories, firstly, some of the gas turbine's spare parts
are selected to be managed and classified. Since the spare parts are
not equal in terms of importance, there is no need that all of them
to be kept in the factory warehouse. It is possible to distinguish the
low‐importance spare parts from the important ones by
categorizing and applying different strategies.
• The secondary goals are 1‐ specifying some strategies to manage
warehouse inventories. 2‐ Determining the benefits of spare parts
multi‐criteria categorization in comparison to the single‐criterion
classification. 3‐ Merging the results of AHP and TOPSIS by
applying a new conflation method.
ICMS‐2021 8Research Question(s)
• How could a factory strategically manage spare
parts in its warehouse?
• What would be the strategies to manage the
factory's warehouse inventories?
• What would be the advantages of the
classification of spare parts with a single criterion
in comparison to the multi‐criteria
categorization?
• How could we merge the final results of MCDM
techniques?
ICMS‐2021 9Methodology
ICMS‐2021 10Methodology
• To gain the weights of criteria, the Best Worst Method (BWM), Jafar
Rezaei (2015) is applied in my study. This technique assesses
alternatives based on the classification of decision criteria. BWM is
based on a relatively systematic comparison of decision criteria.
After finalizing the criteria for the decision, the best and the worst
criterion should be determined. A comparison between best‐to‐
others and the others‐to‐worst should be done. Finally, the weights
of criteria will be computed by solving a linear programming model.
The 5‐point scale of 1 to 5, 1 being equivalent, and 5 being an
strongly more important is recommended for comparison.
• In comparison to AHP, there is no need to compare all the criteria
with each other, so less data for comparison is needed. This method
makes more reliable results.
ICMS‐2021 11Methodology
• To solve complex decision making problems, Saaty (1980)
introduced Analytic Hierarchy Process (AHP). It is based on pairwise
comparisons and allows decision‐makers to take into account
different scenarios. This method systematically formulates the main
objectives, identifies specific criteria, sub‐criteria, and alternatives.
It calculates the weights of criteria and alternatives. Finally, AHP
prioritizes alternatives and finds the optimum solution.
• TOPSIS (Hwang and Yoon, 1981) is a widely used method that ranks
alternatives based on criteria. Alternatives are evaluated based on
proximity to positive and negative ideal points Then alternatives
are ranked according to their similarity to the ideal point. The more
similar an alternative to the ideal point, the higher its ranking. The
advantages of using this method are simplicity and producing
solution compatible with prioritization.
ICMS‐2021 12Results
Criteria Number = 4 Criterion 1 Criterion 2 Criterion 3 Criterion 4
The meaning of the numbers 1‐5:
1: Equal importance Names of Criteria Cost Lead Time Consumption Critical
2: Somewhat between Equal and Moderate
3: Moderately more important than Best to Others Cost Lead Time Consumption Critical
4: Somewhat between Moderate and Strong
Critical 3 5 3 1
5: Strongly more important than
Others to the Worst Lead Time Weights
0.60
Cost 3 0.50
0.40
Lead Time 1 0.30
Consumption 1 0.20
0.10
Critical 5 0.00
Cost Lead Time Consumption Critical
Weights
0.20 0.09 0.17 0.54
ICMS‐2021 13Results
= = S=
AHP TOPSIS Final ABCMC ABCS
smax smin S
Spare Part No. Score Spare Part No. Score Ranks classification classification
38 0.1640 38 0.8754 0.3832 0.0135 0.198 2 A C
29 0.1090 29 0.8907 0.3966 0.0059 0.201 1 A C
28 0.0521 28 0.4922 0.1212 0.0014 0.061 12 C A
27 0.0575 27 0.7954 0.3164 0.0017 0.159 3 B C
25 0.0610 25 0.6987 Integrate AHP 0.2441 0.0019 0.123 5 B B
24 0.0598 24 0.5049 and TOPSIS 0.1275 0.0018 0.065 11 C B
21 0.0794 21 0.6589 0.2171 0.0032 0.110 6 B C
16 0.0838 16 0.6538 0.2137 0.0035 0.109 7 B C
13 0.0643 13 0.7379 0.2723 0.0021 0.137 4 B B
11 0.0648 11 0.6130 0.1879 0.0021 0.095 8 C A
10 0.0650 10 0.5623 0.1581 0.0021 0.080 9 C B
8 0.1392 8 0.4995 0.1247 0.0097 0.067 10 C B
Considering the Pareto principle, the spare parts are classified into three groups: A, B,
and C. According to Pareto, 20% of the highest score spare parts are categorized in the A
category, the next 40% in the B category, and 40% with the lowest score classified in
the C category. The final classification of spare parts with multi criteria are shown in
above table.
ICMS‐2021 14Results
Based on Antosz and Ratnayake (2016) and experts'
opinions, inventory control strategies are determined
for each category.
Category Strategy
I. (Spare parts stock is mandatory. Maximum control and precision over warehouse
A inventory ‐ a high priority in purchasing the spare part ‐ 5 times average consumption
over lead time must be available in warehouse)
II. (Spare parts stock is recommended ‐ Second priority in purchasing ‐ 3 times
B
average consumption over lead time must be available in the warehouse)
III. (Revise in spare parts stock‐ Preferably purchase spare parts when they are needed
‐ If lack of spare parts causes production, safety, and environmental implications, 2
C
times average consumption over lead time must be available in the warehouse).
Otherwise, it is not essential to keep the spare parts in the warehouse.
ICMS‐2021 15Results
Minimum
Inventory Required
Adjust
Spare Part ABCMS and storage Available parts to be Income / ABCS
Score Price(USD) Inventory
No. classification control inventory kept in Expense classification
level
strategy warehouse +
1
٣٨ 0.198 A I 15.63 6 3 3 $46.89 C
٢٩ 0.201 A I 103.13 2 3 ‐1 ‐$103.13 C
٢٨ 0.061 C III 112.5 1 3 ‐2 ‐$225.00 A
٢٧ 0.159 B II 121.88 1 3 ‐2 ‐$243.76 C
٢٥ 0.123 B II 156.25 2 1 1 $156.25 B
٢٤ 0.065 C III 175 1 1 0 $0.00 B
٢١ 0.110 B II 231.25 2 2 0 $0.00 C
١٦ 0.109 B II 343.75 2 2 0 $0.00 C
١٣ 0.137 B II 903.13 2 2 0 $0.00 B
١١ 0.095 C III 953.13 2 1 1 $953.13 A
١٠ 0.080 C III 1341.25 1 1 0 $0.00 B
٨ 0.067 C III 1854.69 1 1 0 $0.00 B
The values in column eight (the number needed to be bought/sold to adjust inventory
levels) are obtained from the difference between the values of the sixth column and the
seventh column. For example, for spare part 38, the current inventory is 6. Since spare part
38 is classified in A category, the strategy I will be chosen as a control strategy of this
inventory. 5 times average consumption over lead time must be available in warehouse.
The minim required parts that should be kept in the warehouse is gained by ((Consumption
rate* lead time) /365) * 5)+1.
ICMS‐2021 16Discussion
Applying integrated multi‐criteria decision‐making techniques could
help managers to manage inventories in factories warehouse
strategically. BWM‐AHP‐TOPSIS is the hybrid method that I used to
classify the selected inventories (12 spare parts) in my case study.
Based on the final integrated rank of alternatives and considering the
Pareto rule, 2 spare parts with the highest score categorized in group
A, the next 5 spare parts with descended score are classified in group
B and finally, the 5 remains are grouped in category C.
The safety, environmental, and manufacturing implications of the lack
of spare parts are determined. Lack of spare parts with a high critical
score causes effective implications in the factory’s performance while a
lack of spare parts with a low critical score does not have a significant
implication in the company’s performance.
ICMS‐2021 17Discussion
After implementing strategies, it is found that some of the spare
parts have surplus inventories and some of them are deficient.
To increase the level of the inventories that a company has a
shortage of, some spare parts must be bought. Besides, some
other spare parts could be sold to decrease the level of the
surplus inventories.
The multiple‐criteria approach treats many of the “critical” parts
as a high priority, which protects the company against adverse
effects. On the other hand, since the single‐criterion approach
does not take the possible consequences of a lack of spare parts
into consideration, it places a low priority on parts when lacking
can lead to serious consequences.
ICMS‐2021 18Discussion
To merge final results provided by different MCDM techniques,
one can use the Borda, Copeland, Average of rank,… . Here a
new approach “Maximum‐Minimum Square Mean” ,Ajripour et
al. (2019), is applied to combine the final results of AHP and
TOPSIS.
The limitation of this study is as follows. It was time‐consuming
to categorize all the inventories in the factories' warehouse, so
only some limited spare parts were classified. If one wants to
generalize the results to another company’s spare parts, he/she
should be cautious.
ICMS‐2021 19Implications
Managing inventories in a factories' warehouse is an
important issue that managers are encounter. As the
simplest method, some factories have used the ABC
method to classify and manage inventories but it may not
provide the best solution. Employing multi‐criteria for
the classification of inventories would help managers to
manage and control the warehouse appropriately.
In this study, the selected inventories classified based on
multi‐criteria (Cost, Lead time, Consumption, and
critical). The three first criteria extracted from the
literature review and critical (production, safety,
environment)criterion is proposed in my study.
ICMS‐2021 20Implications
Using BWM for gaining the criteria weights while
one tends to classify inventories in a warehouse is
an important implication in my study.
In previous literature, applying the hybrid method
BWM‐AHP‐TOPSIS for categorizing inventories has
never been studies especially in Iranian case
studies.
The results in practice have shown that the method
could be a reliable one.
ICMS‐2021 21Suggestions for Further Research
Based on the results, it is recommended that this
study will be done for all the inventories in the
factories' warehouse within a specified time. Also,
classify alternatives based on other criteria such as
reliability, reparability, cost of missing, number of
suppliers, etc. is strongly recommended. The
revised AHP or fuzzy AHP/fuzzy TOPSIS or other
techniques like SAW, ELECTRE, PROMETHEE could
be applied to prioritize alternatives. Research can
be done by one or all of the above methods and the
best results can be achieved by the integration of all
methods.
ICMS‐2021 22Bright Future is Yours
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