SELECTION OF MATERIAL HANDLING SYSTEM USING MULTI CRITERIA DECISION TECHNIQUES AT IMPERIAL PORCELAIN PRIVATE LIMITED

A
Presentation
on the topic

SELECTION OF MATERIAL HANDLING SYSTEM USING
MULTI CRITERIA DECISION TECHNIQUES AT
IMPERIAL PORCELAIN PRIVATE LIMITED

Presented By:
Ankur Mahajan
NITTTR, Chandigarh
Email:ankurmahajan786@gmail.com

Contents
 Introduction
 Company’s Profile
 Literature Review
 Problem Formulation
 Methodology
 Result & Discussions
 Conclusions & Scope for Future Work
 References

2

Introduction
Material handling systems:-
 Material handling systems consist of discrete or continuous
resources to move entities from one location to another.
Material movement occurs everywhere in a factory or
warehouse—before, during, and after processing.
 Although the cost associated with the material movement does
not add value in the manufacturing process, sometimes half of
the company's expenditure incurred in material handling.
Therefore, each effort to keep the material handling activities at
a minimum is appreciable.
 Due to the increasing demand for a high variety of products
and shorter response times in today's manufacturing
industry, there is a need for highly flexible and efficient
material handling systems.
 Basic design of a material handling system comprises of
machine layout, product routings, and material flow control. 3

TEN PRINCIPLES OF MATERIAL HANDLING
Planning
Standardization
Work
Ergonomics
Unit Load
Space Utilization
System
Automation
Environment
Life Cycle
4

TYPES OF MATERIAL HANDLING SYSTEMS

 Conveyors (belt conveyors, bucket conveyors, etc.)
 Cranes (jib crane, bridge crane, etc.)
 Palletizers
 Industrial trucks (fork lift)
 Excavators, bull-dozers
 AGV
 Robots
 Automated Storage and Retrieval System

5

TYPES OF CONVEYORS

Flat belt conveyor Trough belt conveyor
6

Chain driven roller conveyor Screw conveyor

7

Roller Bed Belt conveyor

8

Company Profile
 Imperial Porcelain Private Limited is one of the pioneer
ceramic industry in the western Rajasthan located in Bikaner to
produce porcelain insulators.
 The basic raw material is Quartz which is abundantly available
at Bikaner.
 With government’s impetus on electrification in India, the
company diversified its entire production to Low Tension &
High Tension insulators for attaining higher value addition.
 The industry was established in the year 1991 with capacity of
6-8 tonnes /day.
 The company is small scale and having manpower 150.
 The major clients are RVUNL, NTPC, NHPL etc
9

Products
 1.1 KV transformer  33 KV Pin Insulator
Bushing  LT Pin Insulator
 12-17.5 KV Transformer  11 KV post Insulator
Bushing  11 KV 45 KN Disc
 36 KV Transformer Insulator
Bushing  11 KV 70&90 KN Disc
 11 KV Pin Insulator Insulator
 22 KV Pin Insulator  LT shackle insulator

11

Literature Review(Concluding Remarks)
 For problem in different field of engineering viz. selection of
best equipment, process, logistic, vendor, product etc. a number
of alternatives are usually available for selecting the best
possible solution some quantifying methods are required.
 From the literature survey it has been found that a number of
Multi Criteria Decision Method are available which can help in
making a optimal selection.
 Some of the Multi Criteria Decision Method technique reported
in the literature are Analytical Hierarchy Process, Analytical
Network Process, Technique for Order Preference by Similarity
to Ideal Solution, Preference Ranking Organization Method for
Enrichment of Evaluation, Social choice theory method:
preferential or non preferential etc.
13

Contd..
 Out of these techniques AHP, ANP, TOPSIS has been applied
for solving various engineering problem and has been found to
be effective
 These three techniques i.e. AHP, ANP and TOPSIS establish
the priorities in the same way by using pair wise comparisons
and judgment.
 The AHP reduces a multidimensional problem into a one
dimensional problem. AHP structures a decision problem into a
hierarchal structure with a goal, decision criteria and
alternatives.
 The basic structure of ANP is an influence network of clusters
and nodes contained within the clusters.

14

Contd..

 TOPSIS is a practical and useful technique for ranking and
selection of a number of externally determined alternatives
through distant measures.
 However there is no indicator available for selecting a suitable
technique for a given problem. Therefore it is proposed to
apply these three techniques for selecting the material handling
system for Imperial Porcelain Private Limited, Bikaner.

15

Problem Identification
 For the last 2 years, observation of the management of the
company was that the production of the organization is low and
cracks were appearing in the insulators during drying and
baking.
 The percentage of defects were observed in the range of 13%
to 17%.
 After analyzing the whole manufacturing process it was found
that three processes namely pugging, shaping and copying play
an important role for preparing the required and specified
preliminary sizing and shaping of the final product.
 These processes are providing the required properties of
electrical and mechanical for final product.

16

Contd..
 The extra removed material which is removed during shaping
and copying process dumped around the machines.
 This material is later on reused in the pugging machine mixed
with fresh raw material.
 The extra material is fed back into the pug mill manually at
irregular intervals.
 During this process the material gets dry and its properties
become different from the fresh raw material and therefore the
basic properties of the mixture on the pug mill are changed.
 Due to intermittent feeding process some material becomes
completely dry.

17

Contd..
 Thus it was observed that the main reason for large percentage
of cracks is the material recovered from the shaping and
copying machines which is mixed with the fresh raw material.
 By the time this material is transported manually to the pugmill
for recycling it loses moisture and it contains chunks due to the
operation carried out during shaping and copying.
 It was therefore proposed to the management that the material
from the shaping and copying be transported back to blunger
instead of pugmill for proper mixing.
 Further a suitable material handling system be installed so that
irregular transportation can be avoided which was causing
moisture loss and reduced productivity.

18

Contd..
 The management wanted to select the most suitable material
handling system which would increase productivity with least
investment.
 Since a number of alternative are available in material handling
system.
 It was decided to select a system which meet maximum
possible criteria of the process. Therefore in the present work,
different MCDM techniques will be used for the optimum
selection of material handling system, by using AHP, ANP and
TOPSIS techniques in context of different criteria
defined/specified by the company.

19

Contd..
Identification of criteria
The first step is to go for detailed study of existing
process, products and layout of the organization. The
selection of material handling system depends upon
different criteria. In this step the criteria applicable to the
existing problem will be identified.
Criterion/Factors
Factor I : Characteristic of product (Gas, Liquid & Solid)
Factor II : Conveying speed (Low, Medium, High)
Factor III : Cost (Installation, Maintenance & Operation)
Factor IV : Movement (Distance and frequency of moves)
Factor V : Load Flexibility (Light, Medium & Heavy)
Factor VI : Physical shape of the product (Long & Flat)
Factor VII : Property of the product (Wet, Sticky, Hot)
Factor VIII : Volume to be moved
21

contd..
Listing of alternatives
A number of alternatives are available in material handling systems
such as conveyors, overhead cranes, trucks, AGV’s etc. further
options are there in each of these systems. The criteria identified in
the previous steps will be used for choosing a giving type of material
handling system using MCDM techniques. The different material
handling systems are as follows
C-1 : Chain Driven Roller Conveyor
C-2 : Flat belt Conveyor
C-3 : Roller bed belt conveyor
C-4 : Screw Conveyor
C-5 : Troughed Belt Conveyor
It is the major concern of the company to install an appropriate
material handling system in view of its specific nature of the flow of
material and cost.
22

contd..
Application of MCDM Techniques
There are number of MCDM techniques available. Out of
these techniques AHP, ANP and TOPSIS are proposed for
selecting the material handling system for the given
problem. The three technique will be applied one by one
for ranking the different alternatives based upon the
selected criteria.

23

Methodology for Analytical Hierarchy Process
 Step 1: Cost Factor Component of the Equipments

Chain
Roller bed Troughed
Equipment driven Flat belt Screw
S. No belt belt
s roller conveyor conveyor
conveyor conveyor
curve
Cost of
1 165000 120000 159000 256000 138000
Acquisition
Cost of
2 30000 20000 25000 35000 30000
installation
Cost of
3 12000 12000 15000 18000 16000
Operation
Cost of
4 Maintenan 26000 20000 27000 18000 23000
ce

5 Total Cost 233000 172000 226000 327000 207000

24

Step 2: Developing the Decision Tree

25

Step 3: Objective Factor Measure (OFM)
Objective Factor Measure (OFM) values are determined
for each of the alternatives of equipment. The formula is
given below:
OFMi = [OFCi x Σ(1/OFCi)]-1
Where OFCi = Objective Factor Component for i = 1,
2… n number of alternatives of equipment.

(1/OFCi) = (1/OFC1+1/OFC2+1/OFC3+1/OFC4+1/OFC5)
= (1/233000 + 1/172000 + 1/226000 + 1/327000 + 1/207000)

Σ(1/OFCi) = 2.242*10-5
26

Chain Driven
Flat Belt Roller Bed Screw Troughed Belt
S. No. Equipments Roller
Conveyor Belt Conveyor Conveyor Conveyor
Conveyor

Cost of
1 165000 120000 159000 256000 138000
Acquisition

Cost of
2 30000 20000 25000 35000 30000
installation

Cost of
3 12000 12000 15000 18000 16000
Operation

Cost of
4 26000 20000 27000 18000 23000
Maintenance

5 Total Cost 233000 172000 226000 327000 207000

6 OFM 0.1914 0.2593 0.1973 0.1364 0.2154

27

Step 4: Decision Matrix
I II III IV V VI VII VIII

I 1 4 2 1/5 1/2 1/2 2 1/2

II 1/4 1 1/2 1/8 1/4 1/7 1/2 1/6

III 1/2 2 1 1/8 1/4 1/5 2 1/4

IV 5 8 8 1 2 2 7 4

V 2 4 4 1/2 1 1/2 4 2

VI 2 7 5 1/2 2 1 6 2

VII 1/2 2 1/2 1/7 1/4 1/6 1 1/4

VIII 2 6 2 1/4 1/2 1/2 4 1

29

Step 5: Pairwise Comparison Matrices
1.Pair-wise comparison matrix for Characteristic of product

C1 C2 C3 C4 C5

C1 1 1/5 2 2 1/6

C2 5 1 6 8 2

C3 1/2 1/6 1 3 1/6

C4 1/2 1/8 1/3 1 1/6

C5 6 1/2 6 6 1

30

2. Pair-wise comparison matrix for Conveying speed
3. Pair-wise comparison matrix for Cost
4. Pair-wise comparison matrix for Distance Movement
5. Pair-wise comparison matrix for Load Flexibility
6. Pair-wise comparison matrix for Physical Shape of The
Product
7. Pair-wise comparison matrix for Property of the Product
8. Pair-wise comparison matrix for Volume to be Moved

31

Step 6: Determination of the priority vectors (P.V.)


I 1 4 2 1/5 1/2 1/2 2 1/2

II 1/4 1 1/2 1/8 1/4 1/7 1/2 1/6

III 1/2 2 1 1/8 1/4 1/5 2 1/2

IV 5 8 8 1 2 2 7 4

V 2 4 4 1/2 1 1/2 4 2

VI 2 7 5 1/2 2 1 6 2

VII 1/2 2 1/2 1/7 1/4 1/6 1 1/4

VIII 2 6 2 1/4 1/2 1/2 4 1

TOTAL 13.250 34.000 23.000 2.842 6.750 5.009 26.500 10.416

32

Normalize Matrix for decision matrix
I II III IV V VI VII VIII PV

I 0.0755 0.1176 0.0870 0.0704 0.0741 0.0998 0.0755 0.0480 0.0810

II 0.0189 0.0294 0.0217 0.0440 0.0370 0.0285 0.0189 0.0160 0.0268

III 0.0377 0.0588 0.0435 0.0440 0.0370 0.0399 0.0755 0.0480 0.0481

IV 0.3774 0.2353 0.3478 0.3518 0.2963 0.3992 0.2642 0.3840 0.3320

V 0.1509 0.1176 0.1739 0.1759 0.1481 0.0998 0.1509 0.1920 0.1512

VI 0.1509 0.2059 0.2174 0.1759 0.2963 0.1996 0.2264 0.1920 0.2081

VII 0.0377 0.0588 0.0217 0.0503 0.0370 0.0333 0.0377 0.0240 0.0376

VIII 0.1509 0.1765 0.0870 0.0879 0.0741 0.0998 0.1509 0.0960 0.1154

TOTAL 1 1 1 1 1 1 1 1 1

33

Graphical representation of decision matrix
PV values for Decision Matrix
0.35
CHARACTERISTIC OF
PRODUCT
0.30 CONVEYING SPEED

0.25 COST
PV Average

0.20 DISTANCE MOVEMENT

0.15 LOAD FLEXIBILITY

PHYSICAL SHAPE OF THE
0.10
PRODUCT
PROPERTY OF THE
0.05 PRODUCT
QUANTITY TO BE MOVED
0.00
Critrion

34

PV Value for Characteristic of Product

35

PV Value for Conveying Speed

36

PV Valve for Cost

37

PV Valve for Distance Movement

38

PV Valve for Load Flexibility

39

PV Valve for Physical Shape of the Product

40

PV Valve for Property of the Product

41

PV Valve for Volume to be moved

42

Step 7: Consistency Index (C.I.) for each of the Matrices
 The Consistency Index (C.I.) for each of the matrix is
calculated using following formula:
 C.I. = (λmax – n) / (n-1)
 Where n = number of elements of each of the matrices.
 Here λmax = Principle Eigen value
 λmax can be calculated by summation of the multification
of sum of each column with the corresponding PV value
for each of the matrix.
Step 8: Random Consistency index (R.I.)
n 5 8
R.I. 1.11 1.41

43

Step 9: Consistency Ratio (C.R.)
The consistency Ratio for each of the matrix is calculated by
the ratio of Consistency index and Random Index.
C.R. = C.I. / R.I.
C.R. for decision matrix: = 0.02994901
C.R. for Characteristic of product: = 0.0733575
C.R. for Conveying speed: = 0.0858189
C.R. for Cost: = 0.0798872
C.R. for Distance Movement: = 0.0501446
C.R. for Load Flexibility: = 0.0900662
C.R. for Physical shape of the product: = 0.011578
C.R. for Property of the product: = 0.070508
C.R. for Volume to be moved:= 0.0864858

44

Step 10: Subjection Factor Measure Valve for Alternatives

SFMi can be calculated by multiplying each of the PV
values of decision matrix to each of the PV values of each
alternatives of equipment for each factor. The product is
then summed up for each alternative.
SFM1 = 0.1893
SFM2 = 0.266
SFM3 = 0.1883
SFM4 = 0.1248
SFM5 = 0.2300

45

CRITERIA

I II III IV V VI VII VIII SFM

0.0810 0.0268 0.0481 0.3320 0.1512 0.2081 0.0376 0.1154

C1 0.0911 0.1178 0.0671 0.0580 0.1485 0.4027 0.2856 0.3408 0.1893

C2 0.4499 0.1829 0.5268 0.4733 0.0656 0.0799 0.0744 0.1254 0.2676

C3 0.0770 0.0685 0.1197 0.0780 0.1949 0.3875 0.1309 0.2915 0.1883

C4 0.0441 0.0569 0.0529 0.0402 0.4799 0.0474 0.4445 0.0409 0.1248

C5 0.3379 0.5739 0.2334 0.3505 0.1111 0.0825 0.0646 0.2015 0.2300

46

Step 11: Material Handling Equipment Measure
Valve for Alternatives
MEMi = [(α x OFMi) + (1 - α) x SFMi ]
Equipment MEM valve Rank

CHAIN DRIVEN ROLLER CONVEYOR 0.1907328 3

FLAT BELT CONVEYOR 0.2620521 1

ROLLER BED BELT CONVEYOR 0.1943825 4

SCREW CONVEYOR 0.1325751 5

TROUGHED BELT CONVEYOR 0.2202575 2

The best alternative on the basis of the highest value of the
MEM is Flat belt Conveyor.
48

The result shows that the Flat belt conveyor is best as per the
criteria selected for Imperial Porcelain Private Limited
49

Methodology for Analytical Network Process
The ANP is a more general form of the AHP used in multi
criteria decision analysis.

AHP structures a decision problem into hierarchy with a
goal, decision criteria and alternatives while the basic structure
of ANP is an influence network of clusters and nodes contained
within the clusters.

ANP is a multi-criteria decision analysis method that takes
simultaneously, several criteria, both qualitative and
quantitative into consideration, allowing dependence and
making numerical tradeoffs to arrive at a synthetic conclusion
indicating the best solution of a set of possible alternatives.

50

Step 1: Network Structure

51

Step2: Pairwise Comparison Matrices
1. Comparison Matrices of Alternative –Alternative with respect
to Criteria

2. Comparison Matrix Alternative –Alternative with respect to
Alternative

3. Comparison Matrix Criteria-Criteria with respect to Criteria

4. Comparison Matrix of Criteria-Criteria with respect to
Alternative

52

Comparison Matrix of Criteria-Criteria with respect
to Alternative
Comparison with respect to Chain Drive Roller Conveyor Node in "Criteria" Cluster

I 1 1/6 1/4 1/3 1/6 1/2 2 1/2

II 6 1 1/2 1/2 1/4 2 5 3

III 4 2 1 1/2 1/3 4 4 2

IV 3 2 2 1 1/2 3 4 3

V 6 4 3 2 1 4 7 4

VI 2 1/2 1/4 1/3 1/4 1 2 1/3

VII ½ 1/5 1/4 1/4 1/7 1/2 1 1/4

VIII 2 1/3 1/2 1/3 1/4 3 4 1

Total 24.5000 10.2000 7.7500 5.2500 2.8929 18.0000 29.0000 14.0833

53

I II III IV V VI VII VIII PV

I 0.0408 0.0163 0.0323 0.0635 0.0576 0.0278 0.0690 0.0355 0.0429

II 0.2449 0.0980 0.0645 0.0952 0.0864 0.1111 0.1724 0.2130 0.1357

III 0.1633 0.1961 0.1290 0.0952 0.1152 0.2222 0.1379 0.1420 0.1501

IV 0.1225 0.1961 0.2581 0.1905 0.1728 0.1667 0.1379 0.2130 0.1822

V 0.2449 0.3922 0.3871 0.3810 0.3457 0.2222 0.2414 0.2840 0.3123

VI 0.0816 0.0490 0.0323 0.0635 0.0864 0.0556 0.0690 0.0237 0.0576

VII 0.0204 0.0196 0.0323 0.0476 0.0494 0.0278 0.0345 0.0178 0.0312

VIII 0.0816 0.0327 0.0645 0.0635 0.0864 0.1667 0.1379 0.0710 0.0880

Total 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

54

Step 4: Consistency Index (C.I.) For each of the Matrices.

C.I. = (λmax – n) / (n-1)
• C.I. = (8.638228533 - 8)/ (8-1) = 0.091175505
• C.I. = (8.667012993 - 8)/ (8-1) = 0.09528757
• C.I. = (8.693005629 - 8)/ (8-1) = 0.099000804
• C.I. = (8.609240185 - 8)/ (8-1) = 0.087034311
• C.I. = (8.681107493 - 8)/ (8-1) = 0.09730107

55

n 5 8
R.I. 1.11 1.41

C.R. = C.I./ R.I.
C.R. for Chain drive roller conveyor = 0.06512536
C.R. for Flat belt conveyor = 0.06806255
C.R. for Roller bed belt conveyor = 0.07071486
C.R. for Screw conveyor = 0.062167365
C.R. for Troughed belt conveyor = 0.069500765
56

The Unweighted Supermatrix
Alternative Criteria

C1 C2 C3 C4 C5 I II III IV V VI VII VIII

C1 0.0883 0.0897 0.1159 0.1098 0.1004 0.0911 0.1178 0.0671 0.0580 0.1485 0.4027 0.2856 0.3408

C2 0.4607 0.4949 0.3947 0.4579 0.2920 0.4499 0.1829 0.5268 0.4733 0.0656 0.0799 0.0744 0.1254
Altern
C3 0.0805 0.0617 0.0926 0.0843 0.0758 0.0770 0.0685 0.1197 0.0780 0.1949 0.3875 0.1309 0.2915
ative
C4 0.0397 0.0396 0.0398 0.0421 0.0412 0.0441 0.0569 0.0529 0.0402 0.4799 0.0474 0.4445 0.0409

C5 0.3308 0.3140 0.3569 0.3060 0.4906 0.3379 0.5739 0.2334 0.3505 0.1111 0.0825 0.0646 0.2015

I 0.0428 0.0487 0.0420 0.0382 0.0374 0.0810 0.0219 0.0218 0.0322 0.0269 0.0255 0.3023 0.1471

II 0.1357 0.0251 0.1444 0.0244 0.0719 0.0268 0.0934 0.1175 0.0332 0.1393 0.2725 0.0247 0.0436

III 0.1501 0.1062 0.0756 0.3309 0.1315 0.0481 0.2145 0.3215 0.0645 0.1203 0.1197 0.0890 0.1006

IV 0.1822 0.0993 0.1884 0.1604 0.3462 0.3320 0.1470 0.1284 0.3055 0.0923 0.1732 0.0436 0.2888
Criteri
a
V 0.3123 0.2437 0.3270 0.0941 0.2016 0.1512 0.0785 0.0349 0.1821 0.2935 0.0343 0.0690 0.0965

VI 0.0576 0.0747 0.0803 0.2400 0.0751 0.2081 0.0758 0.1481 0.1479 0.0289 0.2212 0.1232 0.2027

VII 0.0312 0.0414 0.0633 0.0814 0.0242 0.0376 0.0360 0.0586 0.0272 0.0480 0.0527 0.1670 0.0294

VIII 0.0880 0.3610 0.0789 0.0306 0.1120 0.1154 0.3330 0.1692 0.2075 0.2508 0.1009 0.1811 0.0913

57

Step 8: The Cluster Matrix

Alternatives Criteria

Alternatives 1.0000 1.0000

Criteria 1.0000 1.0000

Total 2.0000 2.0000

Alternatives Criteria PV Average

Alternative
0.5 0.5 0.500
s

Criteria 0.5 0.5 0.500

Total 1 1 1.000

58

Step 8: Weighted Supermatrix


C1 0.0441 0.0449 0.0580 0.0549 0.0502 0.0455 0.0589 0.0336 0.0290 0.0743 0.2013 0.1428 0.1704

C2 0.2304 0.2475 0.1974 0.2289 0.1460 0.2249 0.0915 0.2634 0.2367 0.0328 0.0400 0.0372 0.0627
Altern
C3 0.0403 0.0309 0.0463 0.0422 0.0379 0.0385 0.0342 0.0598 0.0390 0.0975 0.1937 0.0654 0.1457
ative
C4 0.0198 0.0198 0.0199 0.0210 0.0206 0.0221 0.0284 0.0265 0.0201 0.2399 0.0237 0.2223 0.0204

C5 0.1654 0.1570 0.1784 0.1530 0.2453 0.1690 0.2870 0.1167 0.1752 0.0556 0.0413 0.0323 0.1007

I 0.0214 0.0243 0.0210 0.0191 0.0187 0.0405 0.0110 0.0109 0.0161 0.0134 0.0127 0.1511 0.0735

II 0.0679 0.0125 0.0722 0.0122 0.0360 0.0134 0.0467 0.0587 0.0166 0.0696 0.1363 0.0124 0.0218

III 0.0751 0.0531 0.0378 0.1655 0.0657 0.0240 0.1073 0.1608 0.0322 0.0601 0.0598 0.0445 0.0503

IV 0.0911 0.0496 0.0942 0.0802 0.1731 0.1660 0.0735 0.0642 0.1527 0.0462 0.0866 0.0218 0.1444
Criter
ia
V 0.1562 0.1219 0.1635 0.0471 0.1008 0.0756 0.0392 0.0174 0.0910 0.1468 0.0172 0.0345 0.0482

VI 0.0288 0.0374 0.0401 0.1200 0.0376 0.1040 0.0379 0.0741 0.0740 0.0145 0.1106 0.0616 0.1014

VII 0.0156 0.0207 0.0317 0.0407 0.0121 0.0188 0.0180 0.0293 0.0136 0.0240 0.0264 0.0835 0.0147

VIII 0.0440 0.1805 0.0395 0.0153 0.0560 0.0577 0.1665 0.0846 0.1037 0.1254 0.0505 0.0906 0.0456
59

Step 9: Limit Supermatrix


C1 0.0692 0.0692 0.0692 0.0692 0.0692 0.0692 0.0692 0.0692 0.0692 0.0692 0.0692 0.0692 0.0692

C2 0.1685 0.1685 0.1685 0.1685 0.1685 0.1685 0.1685 0.1685 0.1685 0.1685 0.1685 0.1685 0.1685
Altern
C3 0.0635 0.0635 0.0635 0.0635 0.0635 0.0635 0.0635 0.0635 0.0635 0.0635 0.0635 0.0635 0.0635
ative
C4 0.0461 0.0461 0.0461 0.0461 0.0461 0.0461 0.0461 0.0461 0.0461 0.0461 0.0461 0.0461 0.0461

C5 0.1527 0.1527 0.1527 0.1527 0.1527 0.1527 0.1527 0.1527 0.1527 0.1527 0.1527 0.1527 0.1527

I 0.0259 0.0259 0.0259 0.0259 0.0259 0.0259 0.0259 0.0259 0.0259 0.0259 0.0259 0.0259 0.0259

II 0.0413 0.0413 0.0413 0.0413 0.0413 0.0413 0.0413 0.0413 0.0413 0.0413 0.0413 0.0413 0.0413

III 0.0677 0.0677 0.0677 0.0677 0.0677 0.0677 0.0677 0.0677 0.0677 0.0677 0.0677 0.0677 0.0677

Criteri IV 0.1020 0.1020 0.1020 0.1020 0.1020 0.1020 0.1020 0.1020 0.1020 0.1020 0.1020 0.1020 0.1020

a V 0.0942 0.0942 0.0942 0.0942 0.0942 0.0942 0.0942 0.0942 0.0942 0.0942 0.0942 0.0942 0.0942

VI 0.0562 0.0562 0.0562 0.0562 0.0562 0.0562 0.0562 0.0562 0.0562 0.0562 0.0562 0.0562 0.0562

VII 0.0211 0.0211 0.0211 0.0211 0.0211 0.0211 0.0211 0.0211 0.0211 0.0211 0.0211 0.0211 0.0211

VIII 0.0914 0.0914 0.0914 0.0914 0.0914 0.0914 0.0914 0.0914 0.0914 0.0914 0.0914 0.0914 0.0914

60

The result shows that the Flat belt conveyor is best as per the criteria selected
for Imperial Porcelain Pvt. Limited and followed by Troughed belt conveyor
61

Methodology For Technique For Order Preference By
Similarity to Ideal Solution (TOPSIS)

 TOPSIS is based on the idea that the chosen alternative
should have the shortest distance from the Positive Ideal
Solution (PIS) and on the other side the farthest distance of
the Negative Ideal Solution (NIS).
 The Positive Ideal Solution maximizes the benefit criteria
and minimizes the cost criteria, whereas the Negative Ideal
Solution maximizes the cost criteria and minimizes the
benefit criteria. In the process of TOPSIS, the priority
valves are same as in AHP.

62

Steps for TOPSIS
Step 1: Decision Matrix:
Step 2: Pairwise Comparison Matrices:
1) Pair-wise comparison matrix for Characteristic of product
2) Pair-wise comparison matrix for Conveying speed
3) Pair-wise comparison matrix for Cost
4) Pair-wise comparison matrix for Distance Movement
5) Pair-wise comparison matrix for Load Flexibility
6) Pair-wise comparison matrix for Physical Shape of The Product
7) Pair-wise comparison matrix for Property of the Product
8) Pair-wise comparison matrix for Volume to be Moved
Step 4: Consistency Index (C.I.) For Each of the Matrices.
63

Step 7: Construct a Normalize matrix:
The vector normalization is used for computing rij, which is given as

CRITERIA


WEIGH
0.0810 0.0268 0.0481 0.3320 0.1512 0.2081 0.0376 0.1154
TS

C1 0.1579 0.1899 0.1129 0.0970 0.2681 0.7034 0.5163 0.6696
ALTER
NATIV C2 0.7799 0.2950 0.8859 0.7912 0.1183 0.1396 0.1344 0.2464

ES C3 0.1335 0.1104 0.2012 0.1303 0.3518 0.6769 0.2366 0.5726

C4 0.0765 0.0917 0.0890 0.0672 0.8661 0.0828 0.8036 0.0803

C5 0.5858 0.9254 0.3924 0.5858 0.2006 0.1442 0.1169 0.3958
64

Step 8: Weighted Normalized Decision Matrix
For constructing the weighted normalized decision matrix multiply each column of
the normalized decision matrix by its associated weight. The weighted normalized
value Vij is calculated as:
Vij = Wj*rij
CRITERIA


WEIG
0.0810 0.0268 0.0481 0.3320 0.1512 0.2081 0.0376 0.1154
HTS
C1 0.0128 0.0051 0.0054 0.0322 0.0405 0.1463 0.0194 0.0773
ALTER
C2 0.0632 0.0079 0.0426 0.2627 0.0179 0.0290 0.0051 0.0284
NATIV
ES C3 0.0108 0.0030 0.0097 0.0433 0.0532 0.1408 0.0089 0.0661

C4 0.0062 0.0025 0.0043 0.0223 0.1309 0.0172 0.0302 0.0093

C5 0.0474 0.0248 0.0189 0.1945 0.0303 0.0300 0.0044 0.0457
65

Step 9: Determine the positive ideal and negative
ideal solution
Positive ideal solution:
A* ={ V1*, . . . ., Vn*}, where
= {0.0061926, 0.00245856, 0.004278, 0.02230477,
0.0178841, 0.017232, 0.0043905, 0.009266231}
Negative ideal solution:
A' = { V1’, . . . ., Vn’}, where
Vj’, = { if jε J ; if j ε J’ }
= {0.0061926, 0.00245856, 0.004278, 0.02230477,
0.0178841, 0.017232, 0.0043905, 0.009266231}

66

Step 10: Separation measure for the positive ideal
alternative

CRITERIA

SUM S*

C1 0.0025 0.0004 0.0014 0.0531 0.0082 0.0000 0.0001 0.0001 0.0659 0.2566

C2 0.0000 0.0003 0.0000 0.0000 0.0128 0.0125 0.0006 0.0014 0.0276 0.1662
ALTE
RN--
C3 0.0027 0.0005 0.0011 0.0481 0.0060 0.0000 0.0005 0.0000 0.0589 0.2428
ATIV
ES
C4 0.0032 0.0005 0.0015 0.0578 0.0000 0.0153 0.0000 0.0032 0.0815 0.2855

C5 0.0002 0.0000 0.0006 0.0046 0.0101 0.0123 0.0007 0.0004 0.0289 0.1701

67

Separation measure for the Negative ideal alternative

CRITERIA

SUM S’

C1 0.0000 0.0000 0.0000 0.0001 0.0005 0.0167 0.0002 0.0046 0.022 0.148

C2 0.0032 0.0000 0.0015 0.0578 0.0000 0.0001 0.0000 0.0004 0.063 0.251
ALTE
RN--
C3 0.0000 0.0000 0.0000 0.0004 0.0012 0.0153 0.0000 0.0032 0.020 0.142
ATIVE
S
C4 0.0000 0.0000 0.0000 0.0000 0.0128 0.0000 0.0007 0.0000 0.013 0.115

C5 0.0017 0.0005 0.0002 0.0296 0.0002 0.0002 0.0000 0.0013 0.033 0.183

68

Step 11: Calculation for relative closeness

Calculation for relative closeness coefficient to rank the
alternatives. The closeness coefficient is the distance to the
positive ideal solution (S*) and negative ideal solution (S-)
simultaneously by taking the relative closeness to the positive
ideal solution. The closeness coefficient () for each alternative
is calculated as follow

69

Relative Closeness of the Alternatives

The result shows that the Flat belt conveyor is best as per the criteria
selected for Imperial Porcelain Pvt. Limited and followed by Troughed belt
conveyor
70

RESULTS AND DISCUSSION
Result obtained using Multi Criteria Decision techniques
1. AHP Result for selection of Alternative

Alternatives Result(MEM) Rank
Chain driven roller conveyor 0.1907328 3

Flat belt conveyor 0.2620521 1

Roller bed belt conveyor 0.1943825 4

Screw conveyor 0.1325751 5

Troughed belt conveyor 0.2202575 2

The ranking obtained based upon Material Handling Equipment
Measure show that flat belt conveyor is the most suitable system for
present work followed by Troughed belt conveyor, Chain driven
roller conveyor, Roller bed belt conveyor and Screw conveyor.

71

2. ANP Result for selection of Alternative

Alternatives Result Rank






The ranking obtained based upon Limit super matrix show that
flat belt conveyor is the most suitable system for present work
followed by Troughed belt conveyor, Chain driven roller
conveyor, Roller bed belt conveyor and Screw conveyor.
72

3. TOPSIS Result for selection of Alternative

Alternatives Result Rank






The ranking obtained based upon relative closeness to the ideal
solution show that flat belt conveyor is the most suitable
system for present work followed by Troughed belt conveyor,
Roller bed belt conveyor, Chain driven roller conveyor and
Screw conveyor.
73

4. Comparative Result of MCDM Techniques

The chart shows that the flat belt conveyor was ranked first. The ranking of troughed belt
conveyor and screw conveyor are second and fifth by all the three techniques. Chain driven
roller conveyor and roller bed belt conveyor are preferred over belt driven in case of heavier
loads. Therefore both of them can be used interchangeably when the material to be
transported is heavy. Accordingly they have been ranked in the range of three to four.
74

Discussion on Rankings of Material handling Systems

Results obtained by using MCDM Techniques are discussed with
reference to the criterion/factors of the problem
Factor I : Characteristic of product (Gas, Liquid & Solid)
Factor II : Conveying speed (Low, Medium, High)
Factor III : Cost (Installation, Maintenance & Operation)
Factor IV : Movement (Distance and frequency of moves)
Factor V : Load Flexibility (Light, Medium & Heavy)
Factor VI : Physical shape of the product (Long & Flat)
Factor VII : Property of the product (Wet, Sticky, Hot)
Factor VIII : Volume to be moved

75

Cost analysis of flat belt conveyor installation at
Imperial Porcelain Pvt. Limited
 The flat belt conveyor was ranked first by AHP, ANP and TOPSIS techniques in
selection of material handling system for the present problem.
 The cost price of flat belt conveyor suitable for the present problem is one lac
seventy five thousand approximately and the operational cost is Rs fifteen
thousand per month approximately.
 Therefore the total cost for installing and operating the conveyor system in the
first year will be Rs. Three lac fifty five thousand to the company.
 But installation of the conveyor system the requirement of labour will be reduce
to six from the present numbers i.e. ten.
 The present labour cost is Rs. Three hundred per person per day.
 With the reduction of labour requirement the company will be saving Rs.
300x4x30 =36000/- per month. Thus there will be a annual saving of Rs.
36000x12 = 4,32,000/- in the first year.
 Thus the company will will be able to recover the cost price in the very first
year along with substantial savings which will further increase in the subsequent
year. 76

Discussion…..
 After installation the conveyor system, there is indirect benefit
of decrement in the defective pieces that occur due to the
transportation of extra material from shaping and copying
machine to the blunger is intermittent and at irregular intervals
and the material dried. The basic properties of the extra material
on the pug mill get changed. After installation of conveyor
system for providing continuous movement of chunks from
copying and shaping to blunger which will enhance the overall
productivity of the system.
 Keeping in view the different factors which affect the selection
of material handling system at Imperial Porcelain Pvt. Limited,
Bikaner and the cost analysis, it is stated that the Flat belt
conveyor selected using the different Multi Criteria Decision
Method techniques is the optimal selection.

77

CONCLUSIONS AND SCOPE FOR FUTURE WORK
Conclusion
 For selection of suitable material handling system, the dominant
factors considered were characteristic of product, conveying speed,
cost, distance movement, load flexibility, physical shape of the
product, property of the product and volume to be moved.
 Multi Criteria Decision Method techniques viz. AHP,ANP and
TOPSIS were used for selection of suitable material handling system.
 The results show that the flat belt conveyor was ranked first by
AHP,ANP and TOPSIS techniques for selection of material handling
system for the present problem. The ranking of troughed belt
conveyor and screw conveyor are second and fifth by all the three
techniques. Chain driven roller conveyor and roller bed belt
conveyor are preferred over belt driven in case of heavier loads.
Therefore both of them can be used interchangeably when the
material to be transported is heavy. Accordingly they have been
ranked in the range of three to four.

78

Conclusion ….
 The results obtained from AHP,ANP and TOPSIS techniques
were correlated with factors affecting the process and it was
found that the results providing by all the Multi Criteria
Decision Method techniques were optimal. Thus it may be
concluded that Multi Criteria Decision method techniques are
an effective tool for this type of problem.
 The cost analysis of the material handling system shows that
installing the said conveyor system would result in economic
benefit for the company.
 The indirect benefit is reduction in the percentage of defective
pieces due to continuously supply of extra material to blunger
so that the properties of extra material is not changed.

79

Limitation of Multi Criteria Decision Method Technique
1. The result obtained were forwarded to the management of the
company. The benefits of implementing the selected material
handling system can be measured only after the company
management decides to implement the system.
2. The single set of input data for the Multi Criteria Decision Method
Technique was obtained in the form of rankings scale for different
options in the questionnaire from the company management and
technical experts. Obtaining different sets of input from different
people and using aggregation technique for converging may have
resulted in the different result.
3. The procedure uses weighing the importance of a decision maker
on the basis of his experience and knowledge in the field. Although
the method is widely used but may introduce biasing based on
decision maker’s preferences.
80

Scope for Future Work
 The measure evaluated as weighted average of objective and
subjective factor measure while computing MEM, life of the
equipment and present value of the money has not been considered
explicitly. As different alternatives have different life span, it should
be included in the analysis. Further money in absolute terms cannot be
compared and it needs to be analyzed in relation to time factor.
 In the MCDM analysis, decision-makers are asked to express their
opinions on comparative importance of various criteria in exact
numerical values. However, in practice, the decision is very subjective
and it is usually expressed in linguistic terms rather than exact
numerical values. These linguistic variable scales, such as "very
important'', "important", "equal", "less important'', can then be
converted into fuzzy numbers, since it becomes more meaningful to
quantify a subjective measurement into a range rather than in an exact
value. Therefore, further work is suggested to explore the application
of fuzzy theory in developing this decision system.
81

Some aggregation technique may be used to improve
the data collection and the preliminary results of the
system.
Some other Multi Criteria Decision methods may be
used for the problem viz. Preference Ranking
Organization Method Enrichment of Evaluation
(PROMETHEE), Social Choice Theory Method:
Preferential or Non Preferential, Compromise
Programming, Borda technique, Elimination and
Choice Expressing Reality(ELECTRE) etc.

82

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SELECTION OF MATERIAL HANDLING SYSTEM USING MULTI CRITERIA DECISION TECHNIQUES AT IMPERIAL PORCELAIN PRIVATE LIMITED

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