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BITS Pilani Pilani Campus Supply Chain Management

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BITS PilaniPilani Campus

Supply Chain Management

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Multi-criteria decision making approaches for supplier evaluation and selection

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Presenting Team:

Gaurav Mittal

Sauvik Datta

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• Importance of Supplier Selection• Supplier Selection Process• Supplier Evaluation Criteria• Supplier Evaluation Methods

Objective:

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• One of the most important processes performed in organizations today is the evaluation, selection and continuous measurement of suppliers. Selecting a vendor is now as important a process as developing new products.

• Supplier selection process is a multi-criteria problem, which includes both qualitative and quantitative factors.

Importance of Supplier Selection

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• Purchasing commands a significant position in most organizations since purchased parts, components, and supplies typically represent 40 to 60 percent of the sales of its end products.

• Suppliers have a large and direct impact on the cost, quality,technology, and time-to-market of new products.

• Organization’s ability to produce a quality product at a reasonable cost and in a timely manner is heavily influenced by its suppliers’capabilities

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• Supplier selection is one of the key issues of SCM because the cost of raw materials and component parts constitutes the main cost of a product Management.

• A sound supplier selection decision today can reduce or prevent a host of problems tomorrow.

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• The most effective supplier are those who offer products or services that match or exceed the needs of your business.

• For example if you want to cut down the time it takes you to serve your customers, supplier that offer you faster delivery will rate higher than those that compete on price alone.

• It's well worth examining how many suppliers you really need

Buying from a carefully targeted group Better to have choice of sources

Supplier Selection Process

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Steps in Supplier Selection Process

Evaluating Needs and Defining Objectives list of requirements, objective and criterias to

evaluate the vendors and the way to score different criteria

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Supplier selection criteria

• Reliability• Quality• Value for money• Strong service and clear communication• Financial security• A partnership approach

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Gathering a Limited Pool of Vendors

You can find suppliers through a variety of channels• Recommendations• Directories• Trade associations• Business advisors• Exhibitions• Trade press

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Interviewing with Vendors• Can these suppliers deliver what you want, when

you want it?• Are they financially secure?• How long have they been established?• Do you know anyone who has used and can

recommend them?• Are they on any approved supplier lists from trade

associations or government?

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Selecting and Applying the Method• Once you have a manageable shortlist, you can

approach the potential suppliers and ask for a written quotation and if appropriate, a sample

• When you've got the quotation, compare the potential suppliers in terms of what matters most to you

• Price is important, but it shouldn't be the only reason you choose a supplier

.

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• Check that the supplier you employ is the one that will be doing the work. Some suppliers may outsource work to subcontractors, in which case you should also investigate the subcontractor to determine if you are happy with this arrangement

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The six classes for the supplier evaluation measurement:

• Financial health• Expertise• Operational performance metrics• Business processes & practices• Enabling behaviors or cultural factors• Risk factors

Supplier Evaluation Criteria

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In order to evaluate if a potential supplier is in good

financial position, a buyer can use indicators such as:SalesProfitabilityLiquidityROIDebt ratioTransparency of finances

Financial Health

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The purchasing department of the firm should choose its suppliers according to its capabilities:

Network capabilities Quality and production capabilities (dedicated

level?)Technical level compared to sector averageSpread of technical creationInvestment in R&D

Expertise

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There are a large number of criteria in this category,such as: On-time delivery Lead time Responsiveness Inventory management and control: Reorder

management, forecasting capabilities… Order acceptance, processing & fulfillement Customer service Preventive maintenance Hours of operators training in Total Quality Control (TQC) or JIT

Operational Performance

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How does supplier provide a product or service at the

best value, on time and exactly as required from the

buyers?

Best practice and quality based information. This evaluation business can help get at the root

causes of supplier problems.

Business Processes and Practices

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For example: Is the quality standard of the products met by the production process (preventing defection) or by inspecting the quality of the products after production?

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The evaluation criteria of such a category focus on the

long term sustainability of potential suppliers:

What is the improvement culture of the supplier? Are

his information capabilities always up-to-date? What is his intention of coordination?

Behavior and Cultural factors

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A supplier’s risks are risks for the buyer. Indeed, if a supplier takes too much risk, it can have a great impact on his customer.

Risk factors can be uncovered in the previous criteria exposed, but also in criteria such as: trade relations, currency exchange, insurance, legislations.

Risk Factors

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Supplier evaluation and selection problem has been studied extensively. Various decision making approaches have been proposed to tackle the problem.

Through this presentation, we try to answer these questions:

Which approaches are prevalently applied? Which evaluating criteria are paid more attention to? Is there any inadequacy of the approaches that will

be discussed?

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• Supplier selection has turned to be an important constituent of the organization decision making and has proved to provide a competitive edge over the competitors, while maintaining the strategic and operational bindings.

• Therefore, supplier selection belongs to the class of multi-criteria decision making (MCDM) problem in which the firms need to identify the top priorities of selecting the best supplier based on its working style and the industry type.

.

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• Different researchers have proposed extensive MCDM techniques to provide a feasible and effective solution to supplier selection problem

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The techniques that we are going to discuss are :

Criteria based methods: DEMATEL method for developing supplier selection criteria

Data envelopment analysis (DEA) Analytic hierarchy process (AHP) Analytical models for supplier selection and order

quantity allocation (Mathematical Programming)

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Supplier Selection Using DEMATEL Technique

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Presenting Team:

C V Sunil Kumar Sharan

Siddhrath Akhil Umat

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• DEMATEL Technique applied for supplier selection.• Data envelopment analysis (DEA)• Analytic hierarchy process (AHP)• Analytical models for supplier selection and order quantity allocation (Mathematical Programming)

Topics Discussed

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“Fuzzy DEMATEL method for developing supplier selection criteria” (Betty Chang et. al. 2011)

The DEMATEL method was first conducted by The Battelle Memorial Institute through its Geneva Research Centre in 1973 {Gabus, 1973, #17}.

Decision making trial and evaluation laboratory (DEMATEL) method to find influential factors in selecting Supply Chain Management (SCM) suppliers.

DEMATEL Technique

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The DEMATEL method evaluates supplier performance to find key factor criteria to improve performance and provides a novel approach of decision-making information in SCM supplier selection.

Accurate supplier forecasts help enterprises find proper supply chain partners and consequently enhance organizational performance.

DEMATEL Technique

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The advantage of the DEMATEL method is the capability of revealing the relationship between these factors which influence other factors in supplier selection.

Direct and indirect influence among criteria is obtained using the DEMATEL technique, and computes the causal relationship and strength among supplier selection factors.

DEMATEL Technique

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DEMATEL method is based on digraphs, which separate involved factors into cause group and effect group.

The DEMATEL can convert the relationship between cause and effect factors into an intelligible structural model of the system. The DEMATEL can propose the most important criteria which affects other criteria.

DEMATEL Technique

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(1) Product quality,

(2) Product price,

(3) Technology ability,

(4) Service,

(5) Delivery performance,

(6) Stable delivery of goods,

(7) Lead-time,

(8) Reaction to demand change in time,

(9) Production capability and

(10) Financial situation.

Criteria influencing Supplier Selection

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Questionnaire to 17 Experts

Asked to score 1, 2, 3 and 4 to represent the degree of significance as ‘‘no importance”, ‘‘low importance”, ‘‘high importance”, and ‘‘very high importance”, respectively and

Pair-wise comparison to evaluate the influence of each score, where scores of 0, 1, 2, 3 and 4 represent ‘‘no influence’’, ‘‘low influence”, ”normal influence”, ‘‘high influence’’, and ‘‘very high influence’’, respectively.

DEMATEL Steps

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DEMATEL Steps

Step 1. Set up Direct-Relation Matrix T

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Step 2. Design the fuzzy linguistic variables

DEMATEL Steps

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DEMATEL Steps

Step 3. Transform triangular fuzzy numbers into the initialdirect-relation matrix F.

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The questionnaires are defuzzified as a crisp value Using CFCS (Converting Fuzzy data into Crisp Scores) method.

DEMATEL Steps

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Step 4. Obtain average value.

Step 5. Set up the generalized direct-relation matrix S.

DEMATEL Steps

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DEMATEL Steps

The generalized direct-relation matrix S.

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Step 6. Set up the total-relation matrix M.

DEMATEL Steps

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Step 7. Obtain the sum of rows and columns.

Where D and R denote the sum of rows and the sum of columns, respectively.

DEMATEL Steps

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Step 8. Set up degrees of central role and relation.

Step 9. Set up the causal diagram.

DEMATEL Steps

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Causal Diagram

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Research results show that stable delivery of goods has the greatest influence among the criteria for selecting suppliers.

Conclusion

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DEA is an application of Linear Programming to measure the relative efficiency of operating units with the same goals and objectives.

In each application, the performance of each institution or organization is measured relative to

the performance of all operating units in the same system

Data Envelopment Analysis(DEA)

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DEA is particularly useful in an organization where there are multiple inputs and multiple outputs In many cases, the goal of DEA is to identify the inefficient units that should be targeted for further study and, if necessary, corrective action.

DEA

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DEA creates a fictitious composite unit made up of an optimal weighted average (W1, W2,…) of existing units.

An individual unit, k, can be compared by determining E, the fraction of unit k’s input resources required by the optimal composite unit.

If E < 1, unit k is less efficient than the composite unit and be deemed relatively inefficient.

If E = 1, there is no evidence that unit k is inefficient, but one cannot conclude that k is absolutely efficient.

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The DEA Model MIN Es.t. 1. Sum of weights = 1 2. Weighted outputs > Unit k’s output

(for each measured output)

3. Weighted inputs < E [Unit k’s input](for each measured input)

E, weights > 0

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The case of using DEA to improve performance at four hospitals is used as an example

To evaluate the use of DEA, 3 input and 4 output measures are identified

ExampleEvaluating performance of Hospitals

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Input Measures 1.The number of full-time equivalent (FTE)

nonphysician personnel 2. The amount spent on supplies 3. The number of bed-days available Output Measures1.Patient-days of service under Medicare2. Patient-days of service not under Medicare3. Number of nurses trained4. Number of interns trained

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In this case,a linear programming model is developed for each hospital whose efficiency has to be evaluated.

Then a composite hospital is created based on the outputs and inputs for all the four hospitals

For each output, an output for the composite hospital is determined by computing a weighted average of corresponding output for all the four hospitals.

DEA- An Overview

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Similarly, input for the composite hospital is calculated using the same weighted average method for all the inputs.

Constraints in the LP model require all outputs for the composite to be greater than or equal to the outputs of the county hospital, the one which is being evaluated.

If the inputs are less than that of the county hospital, the hospital being evaluated is having more output for the same input.

DEA- An Overview

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wg= weight applied to inputs and outputs for General Hospital

wu = weight applied to inputs and outputs for University Hospital

wc = weight applied to inputs and outputs for County Hospital

ws = weight applied to inputs and outputs for State Hospital

THE DEA LP Model

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General hospital County hospital University hospital State hospital

1) Medicare Patient 48.14 34.62 36.72 33.16

days

2) Non medicare patient 43.10 27.11 45.98 56.96

days

3) Nurses 253 148 175 160

4 ) Interns 41 27 23 84

5) Amount spent on 285.20 162.3 275.7 210.4

supplies

6) Number of beds available 123.80 128.70 348.50 154.10

7) Number of physicians 106.72 64.21 104.10 104.4

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The DEA approach requires that the sum of these weights equal 1. Thus, the first constraint is

wg + wu + wc + ws = 1

Medicare Patient-Days = (Medicare Patient-Days for (composite hospital) General Hospital )*wg +

(Medicare Patient-Days for County Hospital)*wc + (Medicare Patient-Days University hospital)*wu

+ (Medicare Patient-Days for state hospital)*ws

Constraints

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Medicare Patient-Days =48.l4wg + 34.62wu + (composite hospital) 36.72wc + 33.l6ws

The other output measures for the composite hospital are computed in a similar fashion.

Constraints (cont.)

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General format for the output constraints:

Output for the composite hospital >= Output for county hospital

Medicare Patient days: 48.14 wg + 34.62 wu + 36.72 wc + 33.16 ws >= 36.72

Non medicare patient days: 43.10 wg + 27.11 wu + 45.98 wc + 56.46 ws >= 45.98

Nurses: 253 wg+148 wu+175 wc+l60 ws >= 175 Interns 41 wg+27 wu+23 wc+84 ws >= 23

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General format for the input constraints: (Input for the composite hospital) <= (resources available

for the composite hospitals)

FTE Non physicians for composite hospital = (FTE Non physicians for general hospital) * wg + (FTE Non physicians for university hospital) * wu+ (FTE Non physicians for county hospital) *wc + (FTE Non physicians for state hospital) * ws

The number of full time equivalent non physicians for the hospital is:

285.20wg + 162.30wu + 275.70wc + 210.40ws

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• E = the fraction of County Hospital’s input available to the composite hospital

• The expression for the number of FTE non physicians available to the composite hospital has to be evaluated

• E is also known as efficiency index• The input constraint corresponding to FTE non physicians:

285.20wg+l62.30wu+275.70wc+2l0.40ws <=275.70E

Two other input constraints are • 123.80wg + 128.70wu + 348.50wc + l54.10ws <= 348.50E (Supplies) • 106.72wg + 64.21wu + lO4.l0wc ± l04.04ws <= 104.10E (Bed-days)

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Minimize E

The decision rule is:– If E = 1, the composite hospital requires as

much input as County Hospital does. There is no evidence that County Hospital is inefficient.

– If E< 1, the composite hospital requires less input to obtain the output achieved by County Hospital. The composite hospital is more efficient; thus, County Hospital can be judged relatively inefficient

Objective Function

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Wg + wu + wc + ws = 1

48.14wg+ 34.62wu +36.72wc+33.16ws >=36.72

43.10wg+ 27.11wu +45.98wc+33.16ws >=45.98

253wg + 148wu +175wc + 160ws >=175

41wg + 27wu +23wc + 84ws >=23

123.80wg+ 128.70wu +348.50wc+154.10ws <=348.50E

285.20wg+ 162.30wu +275.70wc+210.40ws <=275050E

106.72wg + 64.21wu + 104.10wc + 104.04ws<= 104.10E

E, wg, wu, ws, wc >= 0

The complete model

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• Step 1: Define decision variables or weights (one for each operating unit) that can be used to determine the inputs and outputs for the composite operating unit.Step 2: Write a constraint that requires the weights to sum to 1.

• Step 3: For each output measure write a constraint that requires the output for the composite operating unit to be greater than or equal to the corresponding output for the jth operating unit.

• Step 4: Define a decision variable, E, which determines the fraction of the jth operating unit’s input available to the composite hospital.

Summary of Approach

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• Step 5: For each input measure write a constraint that requires the input for the composite operating unit to be less than or equal to the resources available to the composite operating unit.

• Step 6: Write the objective function as Min E.

Summary (contd.)

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1.Remember that the goal of data envelopment analysis is to identify operating units that are relatively inefficient. The method does not necessarily identify the operating units that are relativelyefficient. Just because the efficiency index is E = 1, we cannot conclude that the unit being analyzed is relatively efficient. Indeed, any unit that has the largest output on any one of the output measures cannot be judged relatively inefficient.

2.DEA could show all but one unit to be relatively inefficient. Such would be the case if a unit producing the most of every output also consumes the least of every input. Such cases are extremely rare in practice.

Notes

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AHP approach for supplier evaluation and selection in a steel manufacturing company

Farzad Tahriri; M. Rasid Osman; Aidy Ali; Rosnah Mohd Yusuff; Alireza Esfandiary

University Putra Malaysia

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• It is a structured technique for organizing and analyzing complex decisions.

• It was developed by Thomas L. Saaty in the 1970s and has been extensively studied and refined since then.

• It has particular application in group decision making.

• It helps decision makers find one that best suits their goal and their understanding of the problem

Analytic Hierarchy Process

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• Used in choosing the best suppliers.

• AHP process makes it possible to introduce the optimum order quantities among the selected suppliers so that the Total Value of Purchasing (TVP) becomes maximum.

• 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.

Contd…

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• 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.

Why AHP

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• In order to comply with collecting quantitative and qualitative data for AHP supplier selection model that could be applied by the steel manufacturing company a six steps approach was performed to ensure successful implementation.

MODEL DEVELOPMENT

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• Structured interview to evaluate the criteria.

Step 1: Define criteria for supplier selection

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Factors

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Define sub criteria and sub sub-criteria for supplier selection

• To find sub-criteria and sub sub-criteria.

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

Step 2: sub criteria and sub sub-criteria

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• Building the AHP hierarchy model and calculating the weights of each levels of supplier selection model

• Level 1 - selecting the supplier for the steel manufacturing company.

• Level 2 - cost, delivery, quality, management and organization, trust and financial.

• Level 3 - consist 9 sub criteria.• Level 4 - 30 sub sub-criteria.• Level 5 - contains the alternatives, namely the different

supplier

Step 3: Structure the hierarchical model

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Level 3 & 4

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Judgmental Matrix

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Normalized Matrix

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• Software programming is applied for easily using and calculating the future supplier selection model.

• This software programming, which is for AHP supplier selection model.

• Microsoft visual studio 2005 has been used for

Step 5 : Measure Supplier Performance

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• Among the four given suppliers, supplier "C" has the highest weight.

• Therefore, it must be selected as the best supplier to satisfy the needs of the company.

Step 6: Identify Supplier Priority and Selection

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• Identification of the important criteria for supplier selection process.– Trust between key men– Net price

• Results show the models are able to assist decision-makers to examine the strengths and weaknesses of suppliers.

Conclusion

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BITS PilaniPilani Campus By: Abraham Mendoza & José A. Ventura

Analytical models for supplier selection and order quantity selection

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• In the literature, decision models and techniques for supplier selection do not often consider inventory management of the items being purchased as part of the analysis. In this article, two mixed integer nonlinear programming models are proposed to select the best set of suppliers and determine the proper allocation of order quantities while minimizing the annual ordering, inventory holding, and purchasing costs under suppliers’ capacity and quality constraints. The first model allows independent order quantities for each supplier while the second model restricts all order quantities to be of equal size, as it would be required in a multi-stage (supply chain) inventory model.

INTRODUCTION

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PURCHASING PROCESS ACTIVITES

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• The two models proposed in this article consider a multiple-supplier, one manufacturer system. The models assume a

constant demand rate at the manufacturer’s site. This assumption makes sense given that our models are intended for stra- tegic planning

NOTATIONS AND ASSUMPTIONS

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length of an order cycle:

Total number of order cycles per time unit:

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• Size of the order quantity allocated to each supplier is different.

• Quantity allo-cated to a particular supplier is always of the same size.

• Annual ordering cost (AOC):

• Annual holding cost(AHC):

• Annual purchasing cost(APC):

Model with different-size order quantities

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MODEL:M1

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Model with equal-size order quantities

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• The first proposed model allows different order quantities for the various suppliers. The constraints of the model are lin-earized, so that the model can be efficiently solved by commercial optimization software. In this model, the optimal value of M(number of orders allowed within a repeating order cycle) that minimizes TAC may result in a large cycle time. A very practical solution to this problem is to restrict M to a reasonable small value. Our results show that, a small increase in TAC can be justified by the advantages of having a shorter cycle time. Short cycle times facilitate the interaction with sup-pliers and simplify the inventory planning process.

• The second proposed model restricts all order quantities to be of equal size for all selected suppliers. In addition, and similarly to the first proposed model, by restricting M to a reasonable small value, the results can be easily implemented in practice. In addition to these advantages, the objec-tive function is streamlined, which makes the mathematical model considerably simpler and thus easier to solve.

Conclusions