Ahp

SUPPLIER SELECTION USING ANALYTIC HIERARCHY PROCESS

QUALITY SYSTEM DESIGN PROJECT

Submitted By

HARIHARAN.S -- 2009286005

in partial fulfillment for the award of the degree of

MASTER OF ENGINEERING

in

QUALITY ENGINEERING & MANAGEMENT

DEPARTMENT OF INDUSTRIAL ENGINEERING

COLLEGE OF ENGINEERING, GUINDY

ANNA UNIVERSITY

CHENNAI-600025

MAY-2011

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BONAFIDE CERTIFICATE

Certified that this project report (QUALITY SYSTEM DESIGN PROJECT) titled

“SUPPLIER SELECTION USING ANALYTIC HIERARCHY PROCESS” is the bonafide

work of HARIHARAN.S (2009286005) who carried out the project work under my

supervision. Certified further that to the best of my knowledge. The work reported here in

does not form part of any other thesis or dissertation on the basis of which a degree or award

was conferred on an earlier occasion for any other candidate.

Dr.P.SHAHABUDEEN Dr.M.RAJMOHAN

Head of Department, Supervisor,

Professor, Assistant professor,

Department of Industrial Engineering, Department of Industrial Engineering,

College of Engineering, College of Engineering,

Guindy, Guindy,

Anna University, Anna University,

Chennai-600025. Chennai-600025.

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ACKNOWLEDGEMENT

I am extremely thankful to my project guide Dr.M.Rajmohan, Department of

Industrial Engineering for imitating keen interest and giving valuable guidance at every stage

of this project.

It is my great pleasure to express my sincere gratitude and thanks to my head of the

department Dr. P.Shahabudeen, for his valuable guidance and help.

I wish to express my sincere thanks to the company guide Mr.C.G.Visvanathan who

is my external guide for his kind support and guidance to complete my project.

I am also thankful to all the faculty members of the Department of Industrial

Engineering for their kind and valuable cooperation during the course of the project.

I would also like to thank my parents, friends and well wishers who encourage me to

complete this project successfully.

Date: Signature of the Candidate

(Hariharan.S)

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ABSTRACT

Supplier selection is one of the most critical activities of purchasing management in

supply chain. Supplier selection is a complex problem involving qualitative and quantitative

multi-criteria.

In this work, an AHP-based supplier selection model is formulated and then applied

to a real case study for a steel manufacturing company. The use of the proposed model

indicates that it can be applied to improve and assist decision making to resolve the supplier

selection problem in choosing the optimal supplier combination.

The work represents the systematic identification of the important criteria for supplier

selection process. In addition, the results exhibit the application of development of a multi-

criteria decision model for evaluation and selection of suppliers with proposed AHP model,

which by scoring the performance of suppliers is able to reduce the time taken to select a

vendor

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Table of Contents

Chapter No Title Page No

1 Introduction 1

1.1 Supply chain Management 2

1.1.1 Evolving Concept SCM 2

1.1.2 What is SCM 3

1.1.3 SCM objective 3

1.2 Supplier Selection 4

1.2.1 Need for Supplier Selection 6

1.2.2 Supplier Selection Criteria 7

2 MCDM Methods 8

2.1 Various MCDM Methods 8

2.2 Weighted Sum model 9

2.3 Weighted Product model 9

2.4 Multi Attribute Global Inference of Quality 10

3 Analytic Hierarchy Process 12

3.1 AHP introduction 12

3.2 Model development 14

3.3 Advantage of AHP 15

4 Model Development 16

4.1 Company Details 16

4.2 Define criteria for supplier selection 17

4.3 Define sub criteria and sub sub-criteria for supplier selection 17

4.4 Structure the hierarchical model 18

4.5 Prioritize the order of criteria or sub criteria 25

4.6 Measure supplier performance 28

4.7 Identify supplier priority and selection 30

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Chapter No Title Page No

5 Conclusion 31

5.1 Conclusion 31

5.2 Inference Drawn 32

5.3 Future Scope 34

6 Reference 35

Annexure 36

List of Figure

Figure No Title Page No

3.1 AHP Model 15

4.1 AHP Supplier selection model 20

4.2 AHP Supplier selection model with individual weight 24

5.1 Main Criteria Ranking 32

5.2 Sub Criteria Ranking 32

5.3 Supplier Ranking 33

List of Tables

Table No Title Page No

4.1 Level of relative important 18

4.2 Pair wise comparison matrix 19

4.3 Pair wise comparison matrix with relative priority 21

4.4 Composite priority weight of sub criteria 23

4.5 Ranking of sub criteria 25

4.6 Ranking of main criteria 26

4.7 Criteria relative priority with respect to supplier 27

4.8 Priority weights of each alternative 28

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CHAPTER 1

INTRODUCTION

Introduction

In today’s world of globalization many apparel retailers are building strong supply

chains to gain advantage over their competitors by offering the best value to their customers.

The supply-chain management (SCM) has become very critical to manage risk, dynamism,

and complexities of global sourcing. A totally integrated supply chain is required for the

company to get gain the maximum benefits.

One major aspect of the SCM is to select the right sources of supply in the global

business environment that can support corporate’s strategy. Contrary to the conventional

adversarial relationships, effective SCM in the new competition suggests seeking close

relationships in the long term with less number of partners.

Considering the rapidly changing market conditions and customer seeking the best

value, long-term relationships with the vendors became very critical in the apparel industry.

Therefore the apparel retailers are looking for the vendors who can provide the best cost in

the fastest way. Such a relationship is regarded as partnership since it includes activities such

as information sharing, joint product design, or sharing storage spaces.

The purpose of this paper is to emphasize the importance the vendor-selection

problem and its relation to the supply-chain strategy. It presents a model, based on the

analytical hierarchy process (AHP), that an apparel company can use to select its suppliers,

and create a strategy for supplier relationship management (SRM). The framework of the

performance measurement is based on quantitative and qualitative measurements.

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1.1 Supply Chain:

A supply chain is a network of facilities and distribution options that performs the

functions of procurement of materials, transformation of these materials into intermediate

and finished products, and the distribution of these finished products to customers. Supply

chains exist in both service and manufacturing organizations, although the complexity of the

chain may vary greatly from industry to industry and firm to firm.

Traditionally, marketing, distribution, planning, manufacturing, and the purchasing

organizations along the supply chain operated independently. These organizations have their

own objectives and these are often conflicting. Marketing's objective of high customer

service and maximum sales conflict with manufacturing and distribution goals. Many

manufacturing operations are designed to maximize throughput and lower costs with little

consideration for the impact on inventory levels and distribution capabilities. Purchasing

contracts are often negotiated with very little information beyond historical buying patterns.

The result of these factors is that there is not a single, integrated plan for the organization---

there were as many plans as businesses. Clearly, there is a need for a mechanism through

which these different functions can be integrated together. Supply chain management is a

strategy through which such integration can be achieved.

1.1.1 An Evolving Concept:

Supply Chain Management (SCM) has emerged as one of the principal areas on

which leading edge companies are focusing to increase market share, profitability,

competitive advantage and shareholder value. While the term "Supply Chain Management" is

widely used, there is not general agreement as to the definition and scope of the SCM

concept. In fact, during the last several decades, the term itself has evolved from

"Distribution" to "Logistics" to "Supply Chain Management."

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1.1.2 What is SCM?

Definitions from well-respected references have varied during the past decade. For

example, Supply Chain Yearbook 2000 described SCM as, "A chain of processes that

facilitates business activities between trading partners, from the purchase of raw goods and

materials for manufacturing to delivery of a finished product to an end user."

APICS-The Performance Advantage, offered this definition in January 1999: "The

global network used to deliver products and services from raw materials to end customers

through an engineered flow of information, physical distribution and cash."

This is a little change from the 1997 definition, Logistics Management offered,

describing SCM as, "The delivery of enhanced customer and economic value through

synchronized management of the flow of physical goods and associated information from

sourcing to consumption."

The definition evolution continues as European Logistics Association, in 1995

suggested SCM was, "The organization, planning, control and execution of the goods flow

from development and purchasing through production and distribution to the final customer

in order to satisfy the requirements of the market at minimum cost and minimum capital use.

1.1.3 Supply Chain Objective:

The objective of the supply chain is to support the flow of goods and materials from

the original supplier through multiple production and logistics operations to the ultimate

consumer. Supply chain management is the planning and control of this flow to speed time to

market, reduce inventory levels, lower overall costs, and, ultimately, enhance customer

service and satisfaction

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The time has come when companies can no longer afford to look at their operations in

a vacuum. What they now need is the ability to collect comprehensive, accurate, and timely

information over the entire supply chain. By analyzing this information, they can better

understand how changing conditions affect their businesses. Making informed business

decisions this way helps organizations accomplish their business goals while also helping

them use information for competitive advantage.

1.2 Supplier Selection:

Supplier selection and evaluation have become one of the major topics in production

and operations management literature, especially in advanced manufacturing technologies

and environment (Motwani et al., 1999). The main objective of supplier selection process is

to reduce purchase risk, maximize overall value to the purchaser, and develop closeness and

long-term relationships between buyers and suppliers, which is effective in helping the

company to achieve “Just-In-Time” (JIT) production (Li et al., 1997). Additionally, with the

increase in use of Total Quality Management (TQM) and Just-In-Time (JIT) concepts by a

wide range of firms, the supplier selection question has become extremely important

(Petroni, 2000). Choosing the right method for supplier selection effectively leads to a

reduction in purchase risk and increases the number of JIT suppliers and TQM production.

Selecting the suitable supplier is always a difficult task for buyers. Suppliers have

varied strengths and weaknesses, which require careful assessment by the purchasers before

ranking, can be given to them.

The vendor selection process would be simple if only one criterion was used in the

decision making process. However in many situations, purchasers have to take account of a

range of criteria in making their decisions.

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If several criteria are used then it is necessary to determine how far each criterion

influences the decision making process, whether all are to be equally weighted or whether the

influence varies accordingly to the type of criteria.

The model development for steel manufacturing company for selection of vendors

has to be done not only to ensure benefits to the purchaser customers but also to order raw

materials on account of the following reasons:

(1) Huge variety of finished products, and thus great need for raw materials. (2) The large

number of projects in process.

(3) The huge fluctuations in price for raw materials such as: mild steel sheets, stainless steel

and UB steel.

(4) The large number of suppliers providing varieties in qualitative and quantitative criteria.

Supplier selection problem is a group Multiple Criteria Decision-Making (MCDM)

out of which quantities criteria has been considered for supplier selection in the previous and

existing decision models so far. In Multiple Criteria Decision-Making (MCDM), a problem is

affected by several conflicting factors in supplying selection, for which a purchasing

manager must analyze the trade off among the several criteria. MCDM techniques support

the decision-makers (DMs) in evaluating a set of alternatives. Depending upon the

purchasing situations, criteria have varying importance and there is a need to weigh them.

For Multiple Criteria Decision-Making (MCDM) problem of steel manufacturing

company a unique and suitable method is needed to facilitate the supplier selection and

consequently provide the company with a proper and economical system for ordering raw

materials.

The analytic hierarchy process (AHP) has found widespread application in decision

making problems, involving multiple criteria in systems of many levels. This method has the

ability to structure complex, multi-person, multi attribute, and multi-period problem

hierarchically.

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Considering the existing problems in the company initiating from incorrect supplier

selection, owing to the human mistakes in judging the raw materials, or paying too much

attention to one factor only, such as price, cost and other similar and unexpected problems,

the AHP model is highly recommended to handle the supplier selection.

1.2.1 Need for supplier selection:

Global competitive environment continues to force many companies to make strategic

changes in managing their business. Numerous manufacturers have been downsizing,

concentrating on their core competencies, moving away from vertical integration, and

outsourcing more extensively (Goffin, Szwejczewski & New, 2007; Leenders, Nollet, &

Ellram, 2004). According to Leenders et al. (2004), in this process, the need to gain a

competitive edge on the supply side has increased substantially. Particularly for companies

which spend a high percentage of their sales revenue on parts and material supplies, and

whose material costs represent a larger portion of total costs savings from supplies are of

particular importance.

Krajeweski (2006) reported for instance, that the percentage of sales revenues spent

on materials varies from more than 80 percent in the petroleum refining industry to 25

percent in the pharmaceutical industry. Most firms have spent 45 to 65 percent of sales

revenues on materials. Moreover the emphasis on quality and timely delivery in today's

globally competitive marketplace adds a new level of complexity to outsourcing and supplier

selection decisions.

Many companies have attempted to streamline the number of suppliers from which

they purchase. Goffin and his colleagues (2007) found that in a variety of industries in the

United Kingdom between 1990 and 2006, the number of suppliers decreased as much as 36

percent. Collectively, these developments make the supplier selection decisions more critical.

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Weber and his colleagues argue that given the complexity and economic importance

of vendor selection it is somewhat surprising how little attention has been paid in the

literature to the application or quantitative methods to vendor selection. Such techniques

would enable purchasers to select the vendors who best satisfy the requirements necessary to

implement management strategy (Weber, Current and Bestow, 2005, p. 16). A survey by

those authors indicated that companies show a growing interest in multiple criteria methods

when selecting suppliers (Weber, et al., 2005).

1.2.2 Supplier selection criteria:

One major aspect of the purchasing function is supplier selection criteria. The

analysis of criteria for selection and measuring the performance of suppliers has been the

focus of attention for many scientists and purchasing practitioners since 1960's. In the mid

1960's, researchers were developing performance criteria upon which potential suppliers

could be evaluated. Dickson (1966) firstly performed an extensive study to determine,

identify and analyze what criteria were used in the selection of a firm as a supplier. Dickson

asked the respondents to assess the importance of each criterion on a five point scale of:

extreme, considerable, average, slight, and of no importance.

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CHAPTER 2

MCDM Methods

Multi-Criteria Decision Analysis (MCDA) or Multi-Criteria Decision

Making (MCDM)

MCDM is a discipline aimed at supporting decision makers faced with making

numerous and sometimes conflicting evaluations. MCDA aims at highlighting these conflicts

and deriving a way to come to a compromise in a transparent process.

2.1 Various MCDM Methods:

There are many MCDA / MCDM methods in use today. However, often different

methods may yield different results for exactly the same problem. In other words, when

exactly the same problem data are used with different MCDA / MCDM methods, such

methods may recommend different solutions even for very simple problems.

Some of the MCDA methods are:

Weighted sum model (WSM)

Weighted product model (WPM)

Multi-Attribute Global Inference of Quality (MAGIQ)

Analytic hierarchy process (AHP)

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http://en.wikipedia.org/wiki/Analytic_hierarchy_process

http://en.wikipedia.org/wiki/Multi-Attribute_Global_Inference_of_Quality

http://en.wikipedia.org/wiki/Weighted_product_model

http://en.wikipedia.org/wiki/Weighted_sum_model

2.2 Weighted sum model (WSM)

The weighted sum model is the best known and simplest multi-criteria decision

analysis / multi-criteria decision making method for evaluating a number of alternatives in

terms of a number of decision criteria. It is very important to state here that it is applicable

only when all the data are expressed in exactly the same unit.

In general, suppose that a given MCDA problem is defined on m alternatives and n decision

criteria. Furthermore, let us assume that all the criteria are benefit criteria, that is, the higher

the values are, the better it is. Next suppose that wj denotes the relative weight of importance

of the criterion Cj and aij is the performance value of alternative Ai when it is evaluated in

terms of criterion Cj.

Then, the total (i.e., when all the criteria are considered simultaneously) importance

of alternative Ai, denoted as AiWSM-score, is defined as follows:

2.3 Weighted product model (WPM)

The weighted product model is a popular multi-criteria decision

analysis (MCDA) / multi-criteria decision making (MCDM) method. It is similar to

the weighted sum model (WSM). The main difference is that instead of addition in the main

mathematical operation now there is multiplication. As with all MCDA / MCDM methods,

given is a finite set of decision alternatives described in terms of a number of decision

criteria. Each decision alternative is compared with the others by multiplying a number of

ratios, one for each decision criterion. Each ratio is raised to the power equivalent to the

relative weight of the corresponding criterion.

15

http://en.wikipedia.org/wiki/Weighted_product_model

http://en.wikipedia.org/wiki/Weighted_sum_model

Suppose that a given MCDA problem is defined on m alternatives and n decision

criteria. Furthermore, let us assume that all the criteria are benefit criteria, that is, the higher

the values are, the better it is. Next suppose that wj denotes the relative weight of importance

of the criterion Cj and aij is the performance value of alternative Ai when it is evaluated in

terms of criterion Cj. Then, if one wishes to compare the two

alternatives AK and AL (where m ≥ K, L ≥ 1) then, the following product has to be calculated:

If the ratio P(AK/AL) is greater than or equal to the value 1, then it indicates that

alternative AK is more desirable than alternative AL (in the maximization case). If we are

interested in determining the best alternative, then the best alternative is the one that is better

than or at least equal to all other alternatives.

2.4 Multi-Attribute Global Inference of Quality (MAGIQ)

Multi-Attribute Global Inference of Quality (MAGIQ) is a multi-criteria decision

analysis technique. MAGIQ is based on a hierarchical decomposition of comparison

attributes and rating assignment using rank order centroids. The MAGIQ technique is used to

assign a single, overall measure of quality to each member of a set of systems where each

system has an arbitrary number of comparison attributes.

The MAQIC technique has features similar to the Analytic Hierarchy Process and the

Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) technique. The

MAGIQ technique was first published by James D. McCaffrey. The MAGIQ process begins

with an evaluator determining which system attributes are to be used as the basis for system

comparison.

16

http://en.wikipedia.org/wiki/Multi-Attribute_Global_Inference_of_Quality

http://en.wikipedia.org/wiki/MCDA

These attributes are ranked by importance to the particular problem domain, and the

ranks are converted to ratings using rank order centroids. Each system under analysis is

ranked against each comparison attribute and the ranks are transformed into rank order

centroids. The final overall quality metric for each system is the weighted (by comparison

attribute importance) sum of each attribute rating.

The references provide specific examples of the process. There is little direct research

on the theoretical soundness and effectiveness of the MAGIQ technique as a whole, however

the use of hierarchical decomposition and the use of rank order centroids in multi-criteria

decision analyses have been studied, with generally positive results. Anecdotal evidence

suggests that the MAGIQ technique is both practical and useful.

The Analytic Hierarchy Process (AHP) is another type which we used in our

project. This is explained in next chapter

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CHAPTER 3

Analytic Hierarchy Process (AHP)

3.1Analytic Hierarchy Process (AHP)

The Analytic Hierarchy Process (AHP) is a structured technique for dealing

with complex decisions. Rather than prescribing a "correct" decision, the AHP helps decision

makers find one that best suits their goal and their understanding of the problem—it is a

process of organizing decisions that people are already dealing with, but trying to do in their

heads.

Based on mathematics and psychology, the AHP was developed by Thomas in the

1970s and has been extensively studied and refined since then. It provides a comprehensive

and rational framework for structuring a decision problem, for representing and quantifying

its elements, for relating those elements to overall goals, and for evaluating alternative

solutions.

Analytic Hierarchy Process (AHP), since its invention, has been a tool at the hands of

decision makers and researchers, and it is one of the most widely used multiple criteria

decision-making tools. Many outstanding works have been published based on AHP. They

include applications of AHP in different fields such as planning, selecting best alternative,

resource allocations, resolving conflict, optimization, etc., as well as numerical extensions of

AHP. Among applications of AHP method for the field of selecting the best alternative, the

following publications are specified to supplier selection. Ghodsupour and O'Brion (1998)

studied the conflicts between two tangible and intangible factors, based on AHP method, i.e.

qualitative and quantitative, in order to choose the best suppliers.

Users of the AHP first decompose their decision problem into a hierarchy of more

easily comprehended sub-problems, each of which can be analyzed independently. The

elements of the hierarchy can relate to any aspect of the decision problem—tangible or

intangible, carefully measured or roughly estimated, well- or poorly-understood—anything at

all that applies to the decision at hand.

18

http://en.wikipedia.org/wiki/Hierarchy

http://en.wikipedia.org/wiki/Psychology

http://en.wikipedia.org/wiki/Mathematics

http://en.wikipedia.org/wiki/MCDA

Once the hierarchy is built, the decision makers systematically evaluate its various

elements by comparing them to one another two at a time, with respect to their impact on an

element above them in the hierarchy.

In making the comparisons, the decision makers can use concrete data about the

elements, or they can use their judgments about the elements' relative meaning and

importance. It is the essence of the AHP that human judgments, and not just the underlying

information, can be used in performing the evaluations.

The AHP converts these evaluations to numerical values that can be processed and

compared over the entire range of the problem. A numerical weight or priority is derived for

each element of the hierarchy, allowing diverse and often incommensurable elements to be

compared to one another in a rational and consistent way. This capability distinguishes the

AHP from other decision making techniques.

The selection of vendors in Scheme Company has to be done not only to ensure

benefits to the purchasers but also to develop the vendors. The multiple and conflicting

objectives, both getting good quality furniture companies improve their operations, imply

that the criteria to use in selecting vendors might be different than that for normal

commercial purchasing of goods. Given the need to identify the strengths and weakness of

vendors for the development purposes of the scheme, a vendor rating system is essential and

cannot be avoided.

The evaluation procedure took care of about 18 different criteria. These were

segregated into four groups namely: product development capability, manufacturing

capability, quality capability, and cost and delivery. The evaluation method of this model is

based on relative performance measure for each supplier for subjective (qualitative) criteria

which is obtained by quantifying the ratings expressed in quantitative terms. The supplier

who has the maximum score is selected.

Quality, Delivery, Cost, Transport, Quality Certification, Production Facility &

Capability, Technical Capability (Dimensions), Service, Trust, Attitude, Reliability,

Responsiveness, Supplier culture, Packing ability, Profitability, Financial Stability & Credit

Strength, Communication System, etc….,

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3.2 Model development

The objectives of this works are to develop AHP method for supplier selection. In

order to comply AHP supplier selection model a six steps approach was performed to insure

successful implementation as follows:

Step 1: Define criteria for supplier selection

Step 2: Define sub criteria and sub sub-criteria for supplier selection

Step 3: Structure the hierarchical model

Step 4: Prioritize the order of criteria or sub criteria

Step 5: Measure supplier performance

Step 6: Identify supplier priority and selection

Decision situations to which the AHP can be applied include:

Choice - The selection of one alternative from a given set of alternatives, usually

where there are multiple decision criteria involved.

Ranking - Putting a set of alternatives in order from most to least desirable

Prioritization - Determining the relative merit of members of a set of alternatives,

as opposed to selecting a single one or merely ranking them

Resource allocation - Apportioning resources among a set of alternatives

Benchmarking - Comparing the processes in one's own organization with those of

other best-of-breed organizations

Quality management - Dealing with the multidimensional aspects of quality and

quality improvement

Conflict resolution - Settling disputes between parties with apparently

incompatible goals or positions

The applications of AHP to complex decision situations have numbered in the

thousands, and have produced extensive results in problems involving planning, resource

allocation, priority setting, and selection among alternatives.

20

http://en.wikipedia.org/wiki/Resource_allocation


http://en.wikipedia.org/wiki/Planning

http://en.wikipedia.org/wiki/Decision_making

http://en.wikipedia.org/wiki/Conflict_resolution

http://en.wikipedia.org/wiki/Quality_management

http://en.wikipedia.org/wiki/Benchmarking


http://en.wikipedia.org/wiki/Ranking

Other areas have included forecasting, total quality management, business process re-

engineering, quality function deployment, and the Balanced Scorecard.

3.1 AHP Model

3.3 Advantages of the AHP Method

Some benefits of AHP method provided the follow explanation.

The strength of the AHP method lies in its ability to structure a complex, multi

person, multi attribute, and multi period problem hierarchically (Saaty, 1980).

It is simple to use and understand (Chan, 2003).

It necessitates the construction of a hierarchy of attributes, sub attributes, alternatives

and so on, which facilitates communication of the problem and recommend solutions

(Yusuff et al., 2001).

It provides a unique means of quantify judgmental consistency (Chan, 2003).

It does not greatly intuition, experience, and theoretical knowledge of the domain

expert as expert system (Yusuff et al., 2001).

It does not require preferential independent of its complement (i.e. the preference

order of consequences, for any pair of attributes does not depend on the levels at

which all other attributes are hold) as multi-attribute utility model (Chan, 2003).

21

http://en.wikipedia.org/wiki/Balanced_Scorecard

http://en.wikipedia.org/wiki/Quality_function_deployment

http://en.wikipedia.org/wiki/Business_Process_Improvement

http://en.wikipedia.org/wiki/Business_Process_Improvement

http://en.wikipedia.org/wiki/Total_quality_management

http://en.wikipedia.org/wiki/Forecasting

CHAPTER 4

MODEL DEVELOPMENT

4.1 COMPANY DETAILS ( BAY CONTAINER TERMINAL PVT LTD )

Bay Container Terminal Private Limited provides container terminal services all over

the world. The company’s services include container handling to/from vessel and rail, storage

of containers, internal terminal transport, cargo planning for the vessel, reefer monitoring,

transport to/from container freight station, handling of over dimensional and hazardous

containers, water supply, garbage removal, waste oil disposal, opening and closing of

hatches, lashing, daily gate/yard/rail in and out reports, medical and ambulance, berthing, de-

stuffing of LCL containers, and movement of bonded cargoes to inland container depots. It

also provides mainline, feeder, and coastal services. The company was founded in 1985 and

is based in Mumbai, India. It has customers all over the world. The main customer of them

was MEARSK

The main functions of company are to repair, service, handling & storage of various

containers. Four major types of containers that are taken care are

DRY containers

OPEN TOP containers

REFER containers

FLAT TRACK containers

Steels for containers were purchased from various suppliers like LAL

GANAPATHY, MATHAV, PRARIPURNAM, MAHAVEER, THIRUPATHY, and

J.K.STEELS.

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4.2 Step 1: Define criteria for supplier selection

After defining the criteria for selecting the supplier, the first structured interview was

designed based on the input received; an additional criterion were added such that the

respondents were asked to identify the importance of each criterion by using numbers from 1

to 9. In order to identify relevant criteria, the respondents were asked to rate each factor using

the four-point scale of "Not important (1 to 3)", "Some-what important (4 to 5)", Important (6

to 7)" and "Very important (8 to 9)".

Before start of the research, according to the AHP method, the structured interview

was filled out by a related specialist (the manager) to evaluate the criteria. Interviews were

conducted with three members of the Steel Company namely, the two project managers and a

purchasing manager represented in order by (R1), (R2) and (R3) respectively. In order to

select the most important criteria, it was intended to accept the criteria with average above 7.

Finally, the effective extremely important criteria such as quality, delivery, cost, trust,

technical ability were selected at level (2) in supplier selection model (The goals factor in

Level (1) for supplier selection model is to select the best overall supplier).

4.3 Step 2: Define sub criteria and sub sub-criteria for supplier selection

In this step, the definition of the sub criteria and sub sub-criteria has been done for

supplier selection based on the five important criteria selected as the results of previous step.

Design and modification of identified sub and sub-criteria, also respondents, selection of the

second structured interview, have been done similar to the first step.

23

By using the second structured interview, it becomes possible to find sub and sub

sub-criteria. On account of the problems involved in sending the questionnaires to the proper

authorities and getting their response, as well as to minimize the efforts, second structured

interviews were applied to cover two goals.

To find sub-criteria and sub sub-criteria.

To weight and compare pair-wise for all criteria, sub-criteria and sub sub criteria.

Verbal judgment or preference Numerical Rating

Extremely preferred

Very strongly preferred

Strongly preferred

Moderately preferred

Equally preferred

intermediate values between two adjacent

judgments ( when compromise is needed)

9

7

5

3

1

2, 4, 6, and 8

4.1 Level of relative important

4.4 Step 3: Structure the hierarchical model

This phase involves building the AHP hierarchy model and calculating the weights of

each levels of supplier selection model. The developed AHP model, based on the identified

criteria, sub criteria and sub sub-criteria, contains five levels: the goal, the criteria, sub-

criteria, sub-sub criteria and alternatives. (Figure 2) shows an illustrative 5-level hierarchy

for the supplier selection problem. The goal of our problem in selecting the supplier for the

steel manufacturing company is identified in the first level. The second level (criteria)

contains: quality, delivery, cost, trust, technical ability.

The third and fourth level of the hierarchy consist 18 sub criteria, which were

identified in previous section. The lowest level of the hierarchy contains of the alternatives,

namely the different supplier to be evaluated in order to select the best supplier. Six suppliers

were used to represent arbitrarily the ones that the firm wishes to evaluate.

24

To complete the model at this stage, the priority weight of each criterion in each level

was determined. A second structure, an interview consisting of all factors in each level of the

AHP model is used to collect the pair-wise comparison judgments from all evaluation team

members. This approach is found to be very useful in collecting data. This determination is

performed through using pair-wise comparisons. The function of the pair-wise comparisons

is by finding the relative importance of the criteria and sub criteria which is rated by the nine-

point scale proposed by Saaty (1980), as shown in Table , which indicates the level of

relative importance from equal, moderate, strong, very strong, to extreme level by 1, 3, 5, 7,

and 9, respectively. The intermediate values between two adjacent arguments were

represented by 2, 4, 6, and 8

Sample of pair-wise comparison matrix shows that the entry for the five row and the

five column gives the importance of that row's criterion relative to the column's criterion as

shown in Table.

Criteria Quality Delivery Cost Trust Technical

Quality 1 3 2 4 3

Delivery 0.33 1 0.5 2 3

Cost 0.5 2 1 3 3

Trust 0.25 0.5 0.33 1 0.33

Technical 0.33 0.33 0.33 3 1

4.2 Pair wise comparison matrix

25

After obtaining the pair-wise judgments as in the above Table, the next step is the

Computation of a vector of priorities or weighting of elements in the matrix. In terms of

matrix algebra, this consists of calculating the "principal vector" (Eigenvector) of the matrix

by adding the members of each column to find the total. In the next step, in order to

normalize each column to sum to 1.0 or 100%, divide the elements of that column by the

total of the column and sum them up. Finally, add the elements in each resulting row and

divide this sum by the number of elements in the row to get the average.

Criteria Quality Delivery Cost Trust Technical Relative

Priority

Quality 1 3 2 4 3 0.39

Delivery 0.33 1 0.5 2 3 0.17

Cost 0.5 2 1 3 3 0.25

Trust 0.25 0.5 0.33 1 0.33 0.07

Technical 0.33 0.33 0.33 3 1 0.12

Sum 2.41 6.83 4.16 13 10.33

4.3 Pair wise comparison matrix with relative priority

The consistency ratio (C.R.) for the comparison above is calculated to determine the

acceptance of the priority weighting. The consistency test is one of the essential features of

the AHP method which aims to eliminate the possible inconsistency revealed in the criteria

weights, through the computation of consistency level of each matrix.

The consistency ratio (CR) was used to determine and justify the inconsistency in the

pair-wise comparison made by the respondents. Based on Saaty's (1980) empirical

suggestion that a C.R. = 0.10 is acceptable, it is concluded that the foregoing pair-wise

comparisons to obtain attribute weights are reasonably consistent. If the CR value is lower

than the acceptable value, the weight results are valid and consistent. In contrast, if the CR

value is larger than the acceptable value, the matrix results are inconsistent and are exempted

for the further analysis.

27

Weighted sum vector:

WSV = 2.04

0.92

1.36

0.37

0.60

Quality = (2.04/ .39) = 5.231

Delivery = (0.92/ .17) = 5.412

Cost = (1.36/ .25) = 5.44

Trust = (.37/ .07) = 5.286

Technical = (0.60/ .12) = 5

λ max =(5.231+5.412+5.44+5.286+5)/ 5 = 5.2738

C.I = ((λ max – n)/(n-1)) (here n=4)

= ((5.2738-5)/(5-1)) = .0.068

CR = CI/RI (RI = 1.11 (for n= 5))

= .068/ 1.11 = .061 (CR< 0.1 OK).

Table below exhibits the local weights for each criterion in each level.

The global weights are calculated by multiplying the local weights with criteria, sub

criteria and sub sub-criteria. As an example the calculations of the global weights of trust

criteria are shown in following. The result of priority criteria's with local weights of each

level is shown in Table.

28

Composite Priority weights of Sub Criteria:

Main Criteria Local Weight Sub Criteria Local weight

Quality 0.39 Warranty 0.5

Top Management Commitment 0.29

Customer Focus 0.13

I.S.O 0.09

Cost 0.25 Net Price 0.43

Ordering Cost 0.28

Capital investment 0.21

Profitability 0.08

Delivery 0.17 On Time Delivery 0.35

Location 0.3

Delivery Lead Time 0.2

Service Flexibility 0.12

Packaging Ability 0.03

Technical Ability 0.12 Dimension 0.56

Capability Of Supplier 0.32

Communication System 0.12

Trust 0.07 Reliability 0.48

Impression 0.29

Attitude 0.18

Culture 0.05

Quality 0.39 Warranty 0.5

Top Management Commitment 0.29

Customer Focus 0.13

I.S.O 0.09

4.4 Composite Priority weights of Sub Criteria

29

4.5 Step 4: Prioritize the order of criteria or sub criteria

Having completed mathematical calculations, comparisons of criteria and allocating

weights for each criterion in each level is performed. As indicated in the previous section

(Priority weights for alternatives versus attribute and prediction priority), according to the

results of each criterion weights define important criteria arrangement and classified in each

level for selecting the supplier.

After calculating the global weights of each sub sub-criteria of level 4, the result is

rearranged in descending order of priority, as shown in Table.

Rank Critical Factors Global Weight

1 Warranty 0.195

2 Top Management Commitment 0.113

3 Net Price 0.108

4 Ordering Cost 0.07

5 Dimension 0.067

6 On time Delivery 0.06

7 Capital Investment 0.053

8 Customer Focus 0.051

9 Location 0.051

10 Capability of Supplier 0.038

11 I.S.O 0.035

12 Delivery Lead Time 0.034

13 Reliability 0.034

14 Profitability 0.02

15 Service Flexibility 0.02

16 Impression 0.02

17 Communication System 0.014

18 Attitude 0.012

19 Packaging Ability 0.005

20 Culture 0.003

4.5 Ranking of sub criteria

31

Ranking of Main Criteria :

R

ank Critical Factors Global Weight

1 Quality 0.39

2 Cost 0.25

3 Delivery 0.17

4 Technical Ability 0.12

5 Trust 0.07

4.6 Ranking of main criteria

4.6 Step 5: Measure supplier performance

The main reason for adopting this method is the evaluation of supplier for a particular

steel manufacturing company. After weighting the AHP model for determining priority

weight for alternatives and testing the model, the third structured interview was designed and

modifies. This interview collects the weightings of alternatives to identify the best supplier.

In this step, to determine the priority weight for alternatives, the competitive rivals that are

actually the suppliers who are supposed to be used for steel company were compared. After

finding the local weights of each alternative, the global weights of each alternative in each

level can be calculated. The global weights evaluation of each alternative can be obtained

through multiplying the global weights of sub sub criteria by the local weights of each

alternative. The results and priority weight for each alternative are shown in Table.

In the following tables C.F (Criteria Factors), L.W (Local Weights), G.W (Global Weights)

32

Criteria Relative Priority W.R.T supplier:

MAHA

VEER

PRARIP

URNAM

THIRU

PATHY

MAT

HAV

LAL GANA

PATHY

J.K.

STEELS

C.F L.W L.W L.W L.W L.W L.W

Warranty 0.26 0.39 0.04 0.1 0.17 0.03

T.M.C 0.29 0.05 0.17 0.38 0.04 0.07

Net Price 0.18 0.15 0.05 0.03 0.28 0.21

Ordering Cost 0.47 0.02 0.07 0.04 0.08 0.32

Dimension 0.47 0.05 0.18 0.09 0.12 0.1

On time Delivery 0.37 0.27 0.04 0.03 0.18 0.11

Capital

Investments 0.44 0.15 0.21 0.03 0.06 0.1

Customer Focus 0.11 0.04 0.47 0.29 0.03 0.06

Location 0.19 0.38 0.05 0.04 0.29 0.05

Capability of

Supplier 0.45 0.24 0.03 0.07 0.07 0.14

I.S.O 0.38 0.24 0.05 0.15 0.03 0.16

Delivery Lead

Time 0.38 0.22 0.04 0.03 0.2 0.13

Reliability 0.25 0.39 0.04 0.13 0.17 0.03

Profitability 0.59 0.11 0.04 0.11 0.04 0.11

Service

Flexibility 0.33 0.33 0.04 0.03 0.17 0.1

Impression 0.41 0.22 0.08 0.06 0.03 0.2

Communication

System 0.42 0.21 0.07 0.06 0.03 0.14

Attitude 0.44 0.14 0.23 0.03 0.07 0.09

Packaging Ability 0.3 0.12 0.3 0.1 0.05 0.4

Culture 0.16 0.21 0.9 0.9 0.3 0.42

4.7Criteria Relative Priority W.R.T supplier

33

Priority Weights of Each Alternative:

Critical FactorsMAHAVEER PRARIPURNAM THIRUPATHI MATHAV LAL

GANAPATHYJ.K.STEELS

G.W L.W G.W L.W G.W L.W G.W L.W G.W L.W G.W L.W G.WWarranty 0.195 0.26 0.0507 0.39 0.07605 0.04 0.0078 0.1 0.0195 0.17 0.03315 0.03 0.00585

Top Management Commitment 0.113 0.29 0.03277 0.05 0.00565 0.17 0.01921 0.38 0.04294 0.04 0.00452 0.07 0.00791

Net Price 0.108 0.18 0.01944 0.15 0.0162 0.05 0.0054 0.03 0.00324 0.28 0.03024 0.21 0.02268Ordering Cost 0.07 0.47 0.0329 0.02 0.0014 0.07 0.0049 0.04 0.0028 0.08 0.0056 0.32 0.0224

Dimension 0.067 0.47 0.03149 0.05 0.00335 0.18 0.01206 0.09 0.00603 0.12 0.00804 0.1 0.0067On time Delivery 0.06 0.37 0.0222 0.27 0.0162 0.04 0.0024 0.03 0.0018 0.18 0.0108 0.11 0.0066Capital

Investment 0.053 0.44 0.02332 0.15 0.00795 0.21 0.01113 0.03 0.00159 0.06 0.00318 0.1 0.0053Customer

Focus 0.051 0.11 0.00561 0.04 0.00204 0.47 0.02397 0.29 0.01479 0.03 0.00153 0.06 0.00306Location 0.051 0.19 0.00969 0.38 0.01938 0.05 0.00255 0.04 0.00204 0.29 0.01479 0.05 0.00255

Capability of Supplier 0.038 0.45 0.0171 0.24 0.00912 0.03 0.00114 0.07 0.00266 0.07 0.00266 0.14 0.00532

I.S.O 0.035 0.38 0.0133 0.24 0.0084 0.05 0.00175 0.15 0.00525 0.03 0.00105 0.16 0.0056Delivery Lead

Time 0.034 0.38 0.01292 0.22 0.00748 0.04 0.00136 0.03 0.00102 0.2 0.0068 0.13 0.00442Reliability 0.034 0.25 0.0085 0.39 0.01326 0.04 0.00136 0.13 0.00442 0.17 0.00578 0.03 0.00102

4.8.1 Priority Weights of Each Alternative

34

Priority Weights of Each Alternative:

Profitability 0.02 0.59 0.0118 0.11 0.0022 0.04 0.0008 0.11 0.0022 0.04 0.0008 0.11 0.0022Service

Flexibility 0.02 0.33 0.0066 0.33 0.0066 0.04 0.0008 0.03 0.0006 0.17 0.0034 0.1 0.002Impression 0.02 0.41 0.0082 0.22 0.0044 0.08 0.0016 0.06 0.0012 0.03 0.0006 0.2 0.004

Communication System 0.014 0.42 0.00588 0.21 0.00294 0.07 0.00098 0.06 0.00084 0.03 0.00042 0.14 0.00196Attitude 0.012 0.44 0.00528 0.14 0.00168 0.23 0.00276 0.03 0.00036 0.07 0.00084 0.09 0.00108

Packaging Ability 0.005 0.3 0.0015 0.12 0.0006 0.3 0.0015 0.1 0.0005 0.05 0.00025 0.4 0.002Culture 0.003 0.16 0.00048 0.21 0.00063 0.9 0.0027 0.9 0.0027 0.3 0.0009 0.42 0.00126TOTAL SCORE 0.31968 0.20553 0.10617 0.11648 0.13535 0.11391

4.8.2 Priority Weights of Each Alternative

35

4.7 Step 6: Identify supplier priority and selection

Based on the global priority, weights of each alternative can be evaluated and

summarized. The summaries of overall attributes are shown in above Table. It can be

noted that among the six given suppliers, supplier "MAHAVEER” has the highest

weight. Therefore, it must be selected as the best supplier to satisfy the goals and

objectives of the steel manufacturing company. Above table shows the final score of each

supplier s' results and ranking. As can be seen, supplier MAHAVEER s’ score of

(0.31968) is greater than the other five suppliers' scores such as supplier

PRARIPURNAM (0.20553), supplier LAL GANAPATHY (0.13535), supplier

MATHAV (0.11648), supplier J.K.STEELS (0.11391) and supplier THIRUPATHY

(0.10617).

36

CHAPTER 5

Conclusion

5.1 Conclusion:

The main contribution of the work was the identification of the important criteria

for supplier selection process. The criteria found were Warranty, followed by Top

Management Commitment and Net Price. This achievement covered the first objective of

the research.

The second contribution was a development of a multi-criteria decision model for

evaluation and selection which is used for supplier selection in steel company.

The model for supplier evaluation and selection were successfully developed by using

AHP method dedicated for steel manufacturing company. The four-level of AHP model

is assessing decision-makers to identify and evaluate the supplier selection. These

achievements covered the second objective of the research.

Finally, the model is applicable to supplier selection problem in steel

manufacturing company. In addition, the proposed AHP model is significantly effective

in decision making. With the use of AHP model software, the results can be transferred to

a spreadsheet for easy computations and it is easier to identify and evaluate suppliers to

arrive to a consensus decision. The works that have been carried out, can be reused to

identify any supplier ranking case, in order to evaluate and compare other new future

suppliers with the consideration both quantity and quality criteria in steel manufacturing

company.

37

5.2 Inference Drawn:

MAIN CRITERIA RANKING:

SUB CRITERIA RANKING:

38

SUPPLIER RANKING:

The ranking list of critical success factors can be seen that quality and cost factors

occupy the top-most ranking in the list, the top rank being the warranty (0.195), followed

by top management commitment (0.113) and net price (0.108). The delivery and

technical ability factors that are in the top ten ranking include on time delivery (0.06),

dimension (0.067), capital investment (0.053) and location (0.051).

It can be noted that among the six given suppliers, supplier "MAHAVEER” has

the highest weight. Therefore, it must be selected as the best supplier to satisfy the goals

and objectives of the steel manufacturing company.

39

5.3 Future Scope:

In order to have a more reliable result, it is suggested that in future group AHP or

Fuzzy AHP be applied to guide decision making toward a more constructive and

consolidated plan. To comply with this method, questionnaires are prepared which have

to be taught to the related and evolved members to enable them to fill them out correctly

and accurately to get optimum advantages and results. Therefore training classes for the

participant members, involved in decision making, are highly recommended in order to

upgrade their know-ledge in using the sophisticated technique of "AHP". Considering the

simplicity of this technique, the involved members can gain the basic and essential

context of this method along with being cognizant of the questionnaires. Afterwards, the

group will be able to analyze the given data, inputs. Although this method is utterly

beneficial and useful for paving the road for the group to make constructive decisions, it

has some handicaps and faults which can be alleviated and compensated through the

mathematical methods indulged in it.

40

CHAPTER 6

REFERENCE

BOOKS:

Saaty.T.L (2001) Decision making with dependence and feedback, RWS Publication.

Saaty.T.L (1990) The Analytic hierarchy Process, RWS Publication.

JOURNALS:

Farzad Tahriri, M. Rasid Osman, October 2008, “AHP approach for supplier evaluation”,

Vol 1(Journal of industrial engineering and management, 2008 (www.jiem.org))

WEBSITES:

http://nb.vse.c2/~jablon/

http://www.boku.ac.at/mi/

41

http://www.boku.ac.at/mi/

http://nb.vse.c2/~jablon/

http://www.jiem.org/

ANNEXURE

QUALITY Criteria:

Pair wise comparison Metrics:

Criteria ISO Warranty TMC Customer

Focus

Relative

Priority

ISO 1 0.2 0.33 0.5 0.09

Warranty 5 1 2 4 0.5

TMC 3 0.5 1 3 0.29

Customer

Focus

2 0.25 0.33 1 0.13

sum 11 1.95 3.66 8.5


WSV = 0.346

2.01

1.2

0.531

ISO = (0.346/ .09) = 3.84

Warranty = (2.01/ .5) = 4.02

TMC = (1.2/ .29) = 4.138

Customer Focus = (.531/ .13) = 4.085

λ max = (3.84+4.02+4.138+4.085)/ 4

= 4.021

C.I = ((λ max – n)/(n-1)) (here n=4)

= ((4.021-4)/(4-1))

= .007

RI = 0.9(for n= 4)

CR = CI/RI

= .007/ 0.9

= .007 (CR< 0.1 OK).

42

DELIVERY Criteria:


Criteria On Time

Delivery

Service

Flexibility

Delivery

L.T

Location Packaging

Ability

Relative

priority

On Time

Delivery

1 3 2 2 4 0.35

Service

Flexibility

0.33 1 0.5 0.33 5 0.12

Delivery

L. T

0.5 2 1 0.5 7 0.2

Location 0.5 3 2 1 9 0.3

Packaging

Ability

0.25 0.2 0.14 0.11 1 0.03

Sum 2.58 9.2 5.64 3.94 27


WSV = 1.83

0.58

0.98

1.51

0.20

Quality = (1.83/ .35) = 5.229

Delivery = (0.58/ .12) = 4.833

Cost = (0.98/ .2) = 4.9

Trust = (1.51/ .3) = 5.033

Technical = (0.20/ .03) = 6.667

λ max =(55.229+4.833+4.9+5.033+6.667)/ 5 = 5.3324

C.I = ((λ max – n)/ (n-1)) (here n=4)

= ((5.3324-5)/(5-1)) = .0831

RI = 1.11 (for n= 5)

CR = CI/RI = .0831/ 1.11

= .075 (CR< 0.1 OK).

43

COST Criteria:


Criteria Net Price Ordering

Cost

Capital

Investment

Profitability Relative

Priority

Net Price 1 2 5 2 0.43

Ordering

Cost

0.5 1 3 2 0.28

Capital

Investment

0.2 0.33 1 0.25 0.08

Profitability 0.5 0.5 4 1 0.21

Sum 2.2 3.83 13 5.25


WSV = 1.81

1.16

0.31

0.89

Net Price = (1.81/ .43) = 4.209

Ordering Cost = (1.16/ .28) = 4.143

Capital Investment = (.31/ .08) = 3.875

Profitability = (0.89/ .21) = 4.238

λ max =(4.209+4.143+3.875+4.238)/ 4 = 4.116

C.I = ((λ max – n)/(n-1)) (here n=4)

= ((4.116-4)/(4-1))

= 0.039

RI = 0.9(for n= 4)

CR = CI/RI

= 0.039/ 0.9

= 0.043 (CR< 0.1 OK).

44

TRUST Criteria:


Criteria Attitude Impression Reliability Culture Relative

Priority

Attitude 1 0.5 0.33 5 0.18

Impression 2 1 0.5 7 0.29

Reliability 3 2 1 9 0.48

Culture 0.2 0.14 0.11 1 0.05

Sum 6.2 3.64 1.94 23


WSV = 0.733

1.24

2.05

0.179

Attitude = (0.733/ .18) = 4.072

Impression = (1.24/ .29) = 4.276

Reliability = (2.05/ .48) = 4.271

Culture = (0.179/ .05) = 3.58

λ max =(4.072+4.276+4.271+3.58)/ 4 = 4.05

C.I = ((λ max – n)/(n-1)) (here n=4)

= ((4..05-4)/(4-1))

= 0.017

RI = 0.9(for n= 4)

CR = CI/RI

= 0.017/ 0.9

= 0.019 (CR< 0.1 OK).

45

TECHNICAL Criteria:


Criteria Capability of

Supplier

Dimension Communication

system

Relative

priority

Capability of

Supplier

1 0.5 3 0.32

Dimension 2 1 4 0.56

Communication

system

0.33 0.25 1 0.12

Sum 3.33 1.75 8


WSV = 0.96

1.68

0.37

Capability of Supplier = (0.96/.32) = 3

Dimension = (1.68/ .56) = 3

Communication system = (0.37/ .12) = 3.083

λ max =(3+3+3.083)/ = 3.013

C.I = ((λ max – n)/(n-1)) (here n=3)

= ((3.013-3)/(3-1))

= 0.007

RI = 0.58(for n= 3)

CR = CI/RI

= 0.017/ 0.58

= 0.012 (CR< 0.1 OK).

46

Supplier Based on QUALITY:


Criteria Mahaveer Paripurnam Thirupathi Mathav Lal

Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 3 2 5 7 2 .33

Paripurnam .33 1 .33 3 5 2 .16

Thirupathi .5 3 1 5 7 3 .28

Mathav .2 .33 .2 1 3 .25 .04

Lal Ganapathi .14 .2 .14 .33 1 .14 .03

J.K.Steels .5 .5 .33 4 7 1 .16

Sum 2.67 8.03 4 18.33 30 8.39


WSV = 2.1

0.95

1.82

0.34

0.18

0.87

Mahaveer = (2.1/.33) = 6.36

Paripurnam = (.95/.16) = 5.94

Thirupathi = (1.82/.28) = 6.5

Mathav = (.531/ .13) = 8.5

Lal Ganapathi = (0.18/.03) =6

J.K.Steels = (0.87/.16) =5.44

λ max =(6.36+5.94+6.5+8.5+6+5.44)/ 6 = 6.502

C.I = ((λ max – n)/(n-1)) (here n=6) = ((6.502-6)/(6-1)) = .1

RI = 1.24(for n= 6)

CR = CI/RI = .01/ 1.24 = ..08 (CR< 0.1 OK).

47

Supplier Based on DELIVERY:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 7 5 5 .5 5 .33

Paripurnam .14 1 .33 .5 .14 .33 .04

Thirupathi .2 3 1 3 .5 2 .13

Mathav .2 2 .33 1 .14 .33 .05

Lal Ganapathi 2 7 2 7 1 5 .37

J.K.Steels .2 3 .5 3 .2 1 .08

Sum 3.74 23 9.16 19.5 2.48 13.66


WSV = 2.1

0.23

0.81

0.32

2.32

0.56

Mahaveer = (2.1/.33) = 6.36

Paripurnam = (.23/.04) = 5.75

Thirupathi = (.81/ .13) = 6.23

Mathav = (.32/ .05) = 6.4

Lal Ganapathi = (2.32/.37) = 6.27

J.K.Steels = (.56/.08) = 7

λ max =(6.36+5.75+6.23+6.4+6.27+7)/ 6 = 6.335

C.I = ((λ max – n)/(n-1)) (here n=6) = ((6.335-6)/(6-1)) = .067

RI = 1.24(for n= 6)

CR = CI/RI = .067/ 1.24 = .05 (CR< 0.1 OK).

48

Supplier Based on COST:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 5 7 7 7 7 .52

Paripurnam .2 1 2 2 3 3 .16

Thirupathi .14 .5 1 .5 .5 .33 .05

Mathav .14 .5 2 1 .33 .33 .06

Lal Ganapathi .14 .33 2 3 1 3 .12

J.K.Steels .14 .33 3 3 .33 1 .09

Sum 1.76 7.66 17 16.5 12.16 14.66


WSV = 3.56

1.11

0.32

0.38

0.8

0.59

Mahaveer = (3.56/ .52) = 6.85

Paripurnam = (1.11/ .16) = 6.94

Thirupathi = (.32/ .05) = 6.4

Mathav = (.38/ .06) = 6.3

Lal Ganapathi = (0.8/.12) = 6.67

J.K.Steels = (0.59/.09) = 6.56

λ max =(6.85+6.94+6.4+6.3+6.67+6.56)/ 6 = 6.62

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.62-6)/(6-1))

= .123

RI = 1.24(for n= 6)

CR = CI/RI = .123/ 1.24 = .099 (CR< 0.1 OK).

49

Supplier Based on TRUST:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 .33 4 1 3 2 .18

Paripurnam 3 1 4 3 4 4 .38

Thirupathi .25 .25 1 .17 .25 .25 .04

Mathav 1 .33 4 1 3 2 .18

Lal Ganapathi .33 .25 4 .33 1 .25 .08

J.K.Steels .5 .25 4 .5 4 1 .14

Sum 6.08 2.14 21 6 15.25 9.5


WSV = 1.17

2.5

0.27

1.17

0.49

0.9

Mahaveer = (1.17/.18) = 6.5

Paripurnam = (2.5/ .38) = 6.58

Thirupathi = (.27/ .04) = 6.75

Mathav = (1.17/ .18) = 6.5

Lal Ganapathi = (0.49/.08) = 6.13

J.K.Steels = (0.9/.14) = 6.43

λ max =(6.5+6.58+6.75+6.5+6.13+6.43)/ 6 = 6.482

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.482-6)/(6-1))

= .096

RI = 1.24(for n= 6)

CR = CI/RI = .096/ 1.24 = .077 (CR< 0.1 OK).

50

Supplier Based on TECHNICAL ABILITY:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 .5 3 3 5 .25 .16

Paripurnam 2 1 3 3 7 .33 .21

Thirupathi .33 .33 1 2 5 .2 .1

Mathav .33 .33 .5 1 5 .2 .08

Lal Ganapathi .2 .14 .2 .2 1 .14 .03

J.K.Steels 4 3 5 5 7 1 .42

Sum 7.83 5.3 12.7 14.2 30 2.14


WSV = 1.06

1.42

0.62

0.49

0.19

2.8

Mahaveer = (1.06/ .16) = 6.63

Paripurnam = (1.42/ .21) = 6.76

Thirupathi = (062/ .1) = 6.2

Mathav = (.49/ .08) = 6.13

Lal Ganapathi = (0.19/.03) = 6.33

J.K.Steels = (208/.42) = 6.67

λ max =(6.63+6.76+6.2+6.13+6.33+6.67)/ 6 = 6.45

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.45-6)/(6-1))

= .075

RI = 1.24(for n= 6)

CR = CI/RI = .075/ 1.24 = .06 (CR< 0.1 OK).

51

Supplier Based on I.S.O:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 3 5 3 9 3 .38

Paripurnam .33 1 7 2 9 2 .24

Thirupathi .2 .14 1 .2 3 .25 .05

Mathav .33 .5 5 1 7 .5 .15

Lal Ganapathi .11 .11 .33 .14 1 .2 .03

J.K.Steels .33 .5 4 2 5 1 .16

Sum 2.3 5.25 22.33 8.34 34 6.95


WSV = 2.55

1.61

0.32

0.94

0.17

1.06

Mahaveer = (2.55/ .38) = 6.7

Paripurnam = (1.61/ .24) = 6.7

Thirupathi = (.32/ .05) = 6.4

Mathav = (.94/ .15) = 6.3

Lal Ganapathi = (0.17/.03) = 5.7

J.K.Steels = (1.06/.16) = 6.6

λ max =(6.7+6.7+6.4+6.3+6.6+5.7)/ 6 = 6.4

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.4-6)/(6-1))

= .08

RI = 1.24(for n= 6)

CR = CI/RI = .08/ 1.24 = .065 (CR< 0.1 OK).

52

Supplier Based on WARRANTY:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 .33 8 3 3 7 .26

Paripurnam 3 1 9 3. 3 9 .39

Thirupathi .13 .11 1 .17 .2 2 .04

Mathav .33 .33 6 1 .33 6 .1

Lal Ganapathi .33 .33 5 3 1 6 .17

J.K.Steels .14 .11 .5 .17 .17 1 .03

Sum 4.93 2.1 29.5 10.34 7.6 31


WSV = 1.73

2.61

0.23

0.79

1.06

0.18

Mahaveer = (1.73/ .26) = 6.65

Paripurnam = (2.61/ .39) = 6.69

Thirupathi = (.23/ .04) = 5.75

Mathav = (.79/ .1) = 7.9

Lal Ganapathi = (1.06/.17) = 6.2

J.K.Steels = (0.18/.03) = 6

λ max =(6.65+6.69+5.75+7.9+6.2+6)/ 6 = 6.532

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.532-6)/(6-1))

= .106

RI = 1.24(for n= 6)

CR = CI/RI = .106/ 1.24 = .085 (CR< 0.1 OK).

53

Supplier Based on T.M.C:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 5 3 .33 9 7 .29

Paripurnam .2 1 .2 .14 2 .33 .05

Thirupathi .33 5 1 .33 7 3 .17

Mathav 3 7 3 1 5 5 .38

Lal Ganapathi .11 .5 .14 .2 1 .33 .04

J.K.Steels .14 3 .33 .2 3 1 .07

Sum 4.78 21.5 7.67 2.2 27 16.66


WSV = 2.03

.3

1.13

2.66

.22

.51

Mahaveer = (2.03/ .29) =7

Paripurnam = (.3/ .05) = 6

Thirupathi = (1.13/ .17 = 6.65

Mathav = (2.66/ .38) = 7

Lal Ganapathi = (.22/.04) = 5.5

J.K.Steels = (0.51/.07) = 7.29

λ max =(7+6+6.65+7+5.5+7.29)/ 6 = 6.573

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.573-6)/(6-1))

= .115

RI = 1.24 (for n= 6)

CR = CI/RI = .115/ 1.24 = .09 (CR< 0.1 OK).

54

Supplier Based on CUSTOMER FOCUS:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 3 .11 .2 5 3 .11

Paripurnam .33 1 .11 .14 1 .33 .04

Thirupathi 9 9 1 3 7 7 .47

Mathav 5 7 .33 1 9 7 .29

Lal Ganapathi .2 1 .14 .11 1 .33 .03

J.K.Steels .33 3 .14 .14 3 1 .06

Sum 15.33 24 1.83 4.59 26 18.66


WSV = .67

.22

3.32

1.97

.21

.41

Mahaveer = (0.67/ .11) = 6.09

Paripurnam = (.22/ .04) = 5.5

Thirupathi = (3.32/ .47) = 7.06

Mathav = (1.97/ .29) = 6.79

Lal Ganapathi = (0.21/.03) = 7

J.K.Steels = (0.41/.06) = 6.8

λ max =(6.09+5.5+7.06+6.79+7+6.8)/ 6 = 6.54

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.54-6)/(6-1))

= .108

RI = 1.24 (for n= 6)

CR = CI/RI = .108/ 1.24 = .087 (CR< 0.1 OK).

55

Supplier Based on On Time Delivery:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 3 7 9 3 3 .37

Paripurnam .33 1 9 9 3 3 .27

Thirupathi .14 .11 1 3 .14 .2 .04

Mathav .14 .14 .33 1 .14 .2 .03

Lal Ganapathi .33 .33 7 7 1 3 .18

J.K.Steels .33 .33 5 5 .33 1 .11

Sum 2.27 4.91 29.33 34 7.61 10.4


WSV = 2.6

1.71

.26

.18

1.21

.73

Mahaveer = (2.6/ .37) = 7.02

Paripurnam = (1.71/ .27) = 6.3

Thirupathi = (.26/ .04) = 6.5

Mathav = (.18/ .03) = 6

Lal Ganapathi = (1.21/.18) = 6.72

J.K.Steels = (0.73/.11) = 6.64

λ max =(7.02+6.3+6.5+6+6.72+6.64)/ 6 = 6.53

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.53-6)/(6-1))

= .106

RI = 1.24(for n= 6)

CR = CI/RI = .106/ 1.24 = .085 (CR< 0.1 OK).

56

Supplier Based on Service Flexibility:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 1 7 9 5 3 .33

Paripurnam 1 1 7 9 3 5 .33

Thirupathi .14 .14 1 3 .14 .2 .04

Mathav .11 .11 .33 1 .11 .2 .03

Lal Ganapathi .2 .33 7 9 1 3 .17

J.K.Steels .33 .2 5 5 .33 1 .1

Sum 2.78 2.78 27.33 36 9.58 12.4


WSV = 2.36

2.22

.27

.15

1.19

.68

Mahaveer = (2.36/ .33) = 7.15

Paripurnam = (2.22/ .33) = 6.73

Thirupathi = (.27/ .04) = 6.75

Mathav = (.15/ .03) = 5


J.K.Steels = (0.68/.1) = 6.8

λ max =(7.15+6.73+6.75+5+7+6.8)/ 6 = 6.572

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.572-6)/(6-1))

= .114

RI = 1.24(for n= 6)

CR = CI/RI = .114/ 1.24 = .09 (CR< 0.1 OK).

57

Supplier Based on Delivery Lead Time:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 3 5 7 3 3 .38

Paripurnam .33 1 5 7 1 3 .22

Thirupathi .2 .2 1 3 .2 .33 .04

Mathav .14 .14 .33 1 .2 .14 .03

Lal Ganapathi .33 1 5 5 1 3 .2

J.K.Steels .33 .33 3 7 .33 1 .13

Sum 2.33 5.67 19.33 30 5.73 10.47


WSV = 2.44

1.35

.33

.19

1.29

.72

Mahaveer = (2.44/ .38) = 6.42

Paripurnam = (1.35/ .22) = 6.14

Thirupathi = (.33/ .04) = 8.25

Mathav = (.19/ .03) = 6.33

Lal Ganapathi = (1.29/.2) = 6.45

J.K.Steels = (0.72/.13) = 5.54

λ max =(6.42+6.14+8.25+6.33+6.45+5.54)/ 6 = 6.522

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.522-6)/(6-1))

= .104

RI = 1.24(for n= 6)

CR = CI/RI = .104/ 1.24 = .084 (CR< 0.1 OK).

58

Supplier Based on Location:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 .2 3 5 1 7 .19

Paripurnam 5 1 7 7 1 7 .38

Thirupathi .33 .14 1 1 .14 1 .05

Mathav .2 .14 1 1 .14 .33 .04


J.K.Steels .14 .14 1 3 .14 1 .05

Sum 7.67 2.62 20 24 3.42 23.33


WSV = 1.26

2.6

.3

.24

1.84

.34

Mahaveer = (1.26/ .19) = 6.63

Paripurnam = (2.6/ .38) = 6.84

Thirupathi = (.6/ .05) = 6

Mathav = (.24/ .04) = 6

Lal Ganapathi = (1.84/.29) = 6.34

J.K.Steels = (0.34/.05) = 6.8

λ max =(6.63+6.84+6+6+6.34+6.8)/ 6 = 6.435

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.435-6)/(6-1))

= .087

RI = 1.24(for n= 6)

CR = CI/RI = .087/ 1.24 = .07 (CR< 0.1 OK).

59

Supplier Based on Packaging Ability:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 5 7 3 5 1 .3

Paripurnam .2 1 5 3 3 .14 .12

Thirupathi .14 .2 1 .33 .33 .11 .03

Mathav .33 .33 3 1 5 .14 .1

Lal Ganapathi .2 .33 3 .2 1 .11 .05

J.K.Steels 1 7 9 7 9 1 .4

Sum 2.87 13.86 28 14.53 23.33 2.5


WSV = 2.06

.84

.19

.63

.3

2.8

Mahaveer = (2.06/ .03) = 6.87

Paripurnam = (.84/ .12) = 7

Thirupathi = (.19/ .03) = 6.33

Mathav = (.63/ .1) = 6.3


J.K.Steels = (2.8/.4) = 7

λ max =(6.87+7+6.33+6.3+6+7)/ 6 = 6.583

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.583-6)/(6-1))

= .117

RI = 1.24(for n= 6)

CR = CI/RI = .117/ 1.24 = .09 (CR< 0.1 OK).

60

Supplier Based on Net Price:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 3 5 7 .33 1 .18

Paripurnam .33 1 7 9 .33 .33 .15

Thirupathi .2 .14 1 3 .2 .14 .05

Mathav .14 .11 .33 1 .14 .14 .03


J.K.Steels 1 3 7 7 .33 1 .21

Sum 5.67 10.25 25.33 34 2.33 5.61


WSV = 1.39

.99

.28

.16

1.96

1.49

Mahaveer = (1.39/ .18) = 7.72

Paripurnam = (.99/ .15) = 6.6

Thirupathi = (.28/ .05) = 5.6

Mathav = (.16/ .03) = 5.33


J.K.Steels = (1.49/.21) = 7.1

λ max =(7.72+6.6+5.6+5.33+7+7.1)/ 6 = 6.537

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.537-6)/(6-1))

= .107

RI = 1.24(for n= 6)

CR = CI/RI = .107/ 1.24 = .087 (CR< 0.1 OK).

61

Supplier Based on Ordering Cost:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 9 9 9 9 3 .47

Paripurnam .11 1 .33 .33 .2 .11 .02

Thirupathi .11 3 1 3 1 .11 .07

Mathav .11 3 .33 1 .33 .11 .04

Lal Ganapathi .11 5 1 3 1 .11 .08

J.K.Steels .33 9 9 9 9 1 .32

Sum 1.77 30 20.66 25.33 20.53 4.44


WSV = 3.32

.14

.42

.24

.46

2.37

Mahaveer = (3.32/ .47) = 7.06

Paripurnam = (.14/ .02) = 7

Thirupathi = (.42/ .07) = 6

Mathav = (.24/ .04) = 6

Lal Ganapathi = (0.46/.08) = 5.75

J.K.Steels = (2.37/.32) = 7.41

λ max =(7.06+7+6+6+5.75+7.41)/ 6 = 6.54

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.54-6)/(6-1))

= .108

RI = 1.24(for n= 6)

CR = CI/RI = .108/ 1.24 = .087 (CR< 0.1 OK).

62

Supplier Based on Profitability:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 7 9 7 9 7 .59

Paripurnam .14 1 3 1 3 1 .11

Thirupathi .11 .33 1 .33 1 .33 .04

Mathav .14 1 3 1 3 1 .11

Lal Ganapathi .11 .33 1 .33 1 .33 .04

J.K.Steels .14 1 3 1 3 1 .11

Sum 1.64 10.66 20 10.66 20 10.66


WSV = 3.62

.65

.25

.65

.25

.65

Mahaveer = (3.62/ .59) = 6.14

Paripurnam = (.65/ .11) = 5.91

Thirupathi = (.25/ .04) = 6.25

Mathav = (.65/ .11) = 5.91

Lal Ganapathi = (0.25/.04) = 6.25

J.K.Steels = (0.65/.11) = 5.19

λ max =(6.14+5.91+6.25+5.19+6.25+5.19)/ 6 = 6.062

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.062-6)/(6-1))

= .012

RI = 1.24(for n= 6)

CR = CI/RI = .012/ 1.24 = .001 (CR< 0.1 OK).

63

Supplier Based on Capital Investment:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 5 3 7 6 6 .44

Paripurnam .2 1 .5 5 3 3 .15

Thirupathi .33 2 1 6 3 4 .21

Mathav .14 .2 .17 1 .33 .25 .03

Lal Ganapathi .17 .33 .33 3 1 .25 .06

J.K.Steels .17 .33 .25 4 4 1 .1

Sum 2.01 8.86 5.25 26 17.33 14.5


WSV = 3.04

1.01

1.45

.21

.38

.66

Mahaveer = (3.04/ .44) = 6.85

Paripurnam = (1.01/.15) = 6.86

Thirupathi = (1.45/.21) = 6.91

Mathav = (.21/ .03) = 6.23

Lal Ganapathi = (0.38/.06) = 6.1

J.K.Steels = (0.66/.1) = 6.39

λ max =(6.85+6.86+6.91+6.23+6.1+6.39)/ 6 = 6.56

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.56-6)/(6-1))

= .112

RI = 1.24(for n= 6)

CR = CI/RI = .112/ 1.24 = .09 (CR< 0.1 OK).

64

Supplier Based on Attitude:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 5 3 7 6 6 .44

Paripurnam .2 1 .33 5 3 3 .14

Thirupathi .33 3 1 6 3 4 .23

Mathav .14 .2 .17 1 .33 .25 .03

Lal Ganapathi .17 .33 .33 3 1 .5 .07

J.K.Steels .17 .33 .25 4 2 1 .09

Sum 2.01 9.86 5.08 26 15.33 14.75


WSV = 2.99

.93

1.54

.21

.4

.53

Mahaveer = (2.99/ .44) = 6.74

Paripurnam = (.93/ .14) = 6.52

Thirupathi = (1.54/.23) = 6.81

Mathav = (.21/ .03) = 6.18

Lal Ganapathi = (0.4/.07) = 6.15

J.K.Steels = (0.53/.09) = 6.15

λ max =(6.74+6.52+6.81+6.18+6.15+6.15)/ 6 = 6.423

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.423-6)/(6-1))

= .085

RI = 1.24(for n= 6)

CR = CI/RI = .085/ 1.24 = .07 (CR< 0.1 OK).

65

Supplier Based on Impression:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 2 6 6 6 5 .41

Paripurnam .5 1 5 5 7 .5 .22

Thirupathi .17 .2 1 2 4 .25 .08

Mathav .17 .2 .5 1 3 .33 .06

Lal Ganapathi .17 .14 .25 .33 1 .17 .03

J.K.Steels .2 2 4 3 6 1 .2

Sum 2.21 5.54 16.75 17.33 27 7.25


WSV = 2.89

1.44

.49

.38

.21

1.41

Mahaveer = (2.89/ .41) = 7.14

Paripurnam = (1.44/.22) = 6.56

Thirupathi = (.49/ .08) = 6.28

Mathav = (.38/ .06) = 6.34

Lal Ganapathi = (0.21/.03) = 6.3

J.K.Steels = (1.41/.2) = 6.94

λ max =(7.14+6.56+6.28+6.34+6.3+6.94)/ 6 = 6.5899

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.5899-6)/(6-1))

= .118

RI = 1.24(for n= 6)

CR = CI/RI = .118/ 1.24 = .095 (CR< 0.1 OK).

66

Supplier Based on Reliability:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 .33 8 3 3 7 .25

Paripurnam 3 1 9 3 3 9 .39

Thirupathi .13 .11 1 .17 .2 2 .04

Mathav .33 .33 6 1 .33 6 .13

Lal Ganapathi .33 .33 5 3 1 6 .17

J.K.Steels .14 .11 .5 .17 .17 1 .03

Sum 4.93 2.21 29.5 10.34 7.7 31


WSV = 1.74

2.6

.22

.78

1.1

.17

Mahaveer = (1.74/ .25) = 6.84

Paripurnam = (2.6/ .39) = 6.69

Thirupathi = (.22/ .04) = 6.14

Mathav = (.78/ .13) = 6.18

Lal Ganapathi = (1.1/.17) = 6.62

J.K.Steels = (0.17/.03) = 6.29

λ max =(6.84+6.69+6.14+6.18+6.62+6.29)/ 6 = 6.459

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.459-6)/(6-1))

= .092

RI = 1.24(for n= 6)

CR = CI/RI = .092/ 1.24 =. 07 (CR< 0.1 OK).

67

Supplier Based on Culture:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 .5 3 3 5 .25 .16

Paripurnam 2 1 3 3 7 .33 .21

Thirupathi .33 .33 1 1 5 .2 .09

Mathav .33 .33 1 1 5 .2 .09

Lal Ganapathi .2 .14 .2 .2 1 .14 .03

J.K.Steels 4 3 5 5 7 1 .42

Sum 7.86 5.3 13.2 13.2 30 2.12


WSV = 1.04

1.4

.53

.53

.19

2.78

Mahaveer = (1.04/ .16) = 6.5

Paripurnam = (1.4/ .21) = 6.54

Thirupathi = (.53/ .09) = 6.17

Mathav = (.53/ .09) = 6.17

Lal Ganapathi = (0.19/.03) = 6.15

J.K.Steels = (2.78/.42) = 6.57

λ max =(6.5+6.54+6.17+6.17+6.15+6.57)/ 6 = 6.352

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.352-6)/(6-1))

= .07

RI = 1.24(for n= 6)

CR = CI/RI = .07/ 1.24 = .057 (CR< 0.1 OK).

68

Supplier Based on Capability of Supplier:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 4 9 6 6 5 .45

Paripurnam .25 1 7 5 5 3 .24

Thirupathi .11 .14 1 .2 .2 .14 .03

Mathav .17 .2 5 1 1 .33 .07

Lal Ganapathi .17 .2 5 1 1 .33 .07

J.K.Steels .2 .33 7 3 3 1 .14

Sum 1.9 5.87 34 16.2 16.2 9.8


WSV = 3.19

1.66

.16

.44

.44

.91

Mahaveer = (3.19/ .45) = 7.02

Paripurnam = (1.66/.24) = 6.96

Thirupathi = (.16/ .03) = 6.25

Mathav = (.44/ .07) = 6.15

Lal Ganapathi = (0.44/.07) = 6.15

J.K.Steels = (0.91/.14) = 6.51

λ max =(7.02+6.96+6.25+6.15+6.15+6.51)/ 6 = 6.511

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.511-6)/(6-1))

= .102

RI = 1.24(for n= 6)

CR = CI/RI = .102/ 1.24 = .08 (CR< 0.1 OK).

69

Supplier Based on Dimension:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 6 3 6 7 5 .47

Paripurnam .17 1 .33 .25 .5 .5 .05

Thirupathi .33 3 1 2 3 2 .18

Mathav .17 4 .5 1 .33 .5 .09

Lal Ganapathi .14 2 .33 3 1 2 .12

J.K.Steels .2 2 .5 2 .5 1 .1

Sum 2.01 18 5.66 14.25 12.33 11


WSV = 3.15

.32

1.21

.55

.8

.61

Mahaveer = (3.15/ .47) = 6.74

Paripurnam = (.32/.05) = 6.32

Thirupathi = (1.21/.18) = 6.67

Mathav = (.55/ .09) = 6.1

Lal Ganapathi = (0.8/.12) = 6.76

J.K.Steels = (0.61/.1) = 6.49

λ max =(6.74+6.32+6.67+6.1+6.76+6.49)/ 6 = 6.529

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.529-6)/(6-1))

= .106

RI = 1.24(for n= 6)

CR = CI/RI = .106/ 1.24 = .085 (CR< 0.1 OK).

70

Supplier Based on Communication System:



Ganapathi

J.K.Steels Relative

Priority

Mahaveer 1 2 6 7 8 5 .42

Paripurnam .5 1 5 5 7 .3 .21

Thirupathi .17 .2 1 2 2 .25 .07

Mathav .14 .2 .5 1 .3 .33 .06

Lal Ganapathi .13 .14 .5 .33 1 .17 .03

J.K.Steels .2 3 4 3 6 1 .14

Sum 2.14 6.54 17 18.33 27 7.08


WSV = 2.97

1.32

.41

.36

.2

1.56

Mahaveer = (2.97/.42) = 7.1

Paripurnam = (1.32/.21) = 6.28

Thirupathi = (.41/.07) = 6.33

Mathav = (.36/.06) = 6.34

Lal Ganapathi = (.2/.03) = 6.41

J.K.Steels = (1.56/.14) = 7.07

λ max =(7.1+6.28+6.33+6.34+6.41+7.07)/ 6 = 6.588

C.I = ((λ max – n)/(n-1)) (here n=6)

= ((6.588-6)/(6-1))

= .118

RI = 1.24(for n= 6)

CR = CI/RI = .118/ 1.24 = .095 (CR< 0.1 OK).

71

Ahp

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Transcript of Ahp