Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/11425
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dc.coverage.spatialSupplier selection processen_US
dc.date.accessioned2013-09-23T06:02:41Z-
dc.date.available2013-09-23T06:02:41Z-
dc.date.issued2013-09-23-
dc.identifier.urihttp://hdl.handle.net/10603/11425-
dc.description.abstractTraditionally, in all manufacturing industries, the functions of marketing, distribution, planning, manufacturing, and purchasing operate independently. These functions have their own objectives. Many manufacturing operations are designed to maximize throughput and to minimise costs with a little consideration for the impact on inventory levels and distribution capabilities. Presently, the purchasing contracts are often negotiated with minimum information beyond the historical purchasing patterns of the customer. This research, first takes up the application of Analytic Network Process (ANP) model in the supplier selection process (Saaty 1980). It is generally agreed that taking an unbiased decision is the prime objective which is very hard to reach. In the model, proposed in this research, twelve potential evaluation criteria viz. Quality, Quantity, Delivery time, Demand, Cost, Discount, Sales after service, Communication system, Technical Capability, Production facilities, Geographical location and Professionalism of Sales person are considered to select important criteria. In this model, AHP was applied for four products namely Back plate, Wheel Cylinder, Lining Shoe and Auto Adjuster for back wheel assembly by five automotive ancillary suppliers (Supplier A, Supplier B, Supplier C, Supplier D and Supplier E) to a leading industry which manufactures brake systems for automobiles at India. The best supplier was identified from the overall priority vectors obtained using AHP. The application of the Fuzzy Inference System (FIS) is used to check the suitability of the selected supplier which is obtained as the result of AHP. Also results were obtained using MAT LAB. Quality, Quantity, Delivery time, Demand, and Cost were the five criteria which were considered. The result of fuzzy logic shows that the selected supplier as the result of AHP is acceptable. Finally sensitivity analysis was made and based on the priority vectors it was found that the AHP model for selecting the best supplier was stable. newline newline newlineen_US
dc.format.extentxviii, 168en_US
dc.languageEnglishen_US
dc.relation120en_US
dc.rightsuniversityen_US
dc.titleAn integrated multi criteria decision making model approach in supplier selection processen_US
dc.title.alternativeen_US
dc.creator.researcherElanchezhian Cen_US
dc.subject.keywordDecision making model, analytic network process, analytic hierarchy process, consistency ratioen_US
dc.description.noteAppendix 1, pp.142-153en_US
dc.contributor.guideKesavan, R.en_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Mechanical Engineeringen_US
dc.date.registered1, October 2010en_US
dc.date.completeden_US
dc.date.awardeden_US
dc.format.dimensions23.5 cm x 15 cmen_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Mechanical Engineering

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01_title.pdfAttached File41.1 kBAdobe PDFView/Open
02_certificates.pdf943.18 kBAdobe PDFView/Open
03_abstract.pdf14.85 kBAdobe PDFView/Open
04_acknowledgement.pdf14.03 kBAdobe PDFView/Open
05_contents.pdf36.33 kBAdobe PDFView/Open
06_chapter 1.pdf287.14 kBAdobe PDFView/Open
07_chapter 2.pdf78.06 kBAdobe PDFView/Open
08_chapter 3.pdf246.62 kBAdobe PDFView/Open
09_chapter 4.pdf357.09 kBAdobe PDFView/Open
10_chapter 5.pdf369.04 kBAdobe PDFView/Open
11_chapter 6.pdf121.44 kBAdobe PDFView/Open
12_chapter 7.pdf21.73 kBAdobe PDFView/Open
13_appendix 1.pdf60.12 kBAdobe PDFView/Open
14_references.pdf42.34 kBAdobe PDFView/Open
15_publications.pdf16.74 kBAdobe PDFView/Open
16_vitae.pdf12.66 kBAdobe PDFView/Open


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