Supplier evaluation and selection via Taguchi loss functions and an AHP

Pi, Wei-Ning; Low, Chinyao

doi:10.1007/s00170-004-2227-z

Cited by 101 publications

(53 citation statements)

References 15 publications

(35 reference statements)

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“…Many papers on a wide variety of applications of Taguchi's loss function is published in the recent past (Liao & Kao, 2010;Pi & Low, 2006;Antony, 2000;Antony, 2001;Wu, 2004;Kethley, 2002;Chan & Ibrahim, 2004;Cho & Cho, 2008;John, 2012). The QLP method is to…”

Section: Methodsmentioning

confidence: 99%

A dual response surface optimization methodology for achieving uniform coating thickness in powder coating process

John¹

2015

10.5267/j.ijiec

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The powder coating is an economic, technologically superior and environment friendly painting technique compared with other conventional painting methods. However large variation in coating thickness can reduce the attractiveness of powder coated products. The coating thickness variation can also adversely affect the surface appearance and corrosion resistivity of the product. This can eventually lead to customer dissatisfaction and loss of market share. In this paper, the author discusses a dual response surface optimization methodology to minimize the thickness variation around the target value of powder coated industrial enclosures. The industrial enclosures are cabinets used for mounting the electrical and electronic equipment. The proposed methodology consists of establishing the relationship between the coating thickness & the powder coating process parameters and developing models for the mean and variance of coating thickness. Then the powder coating process is optimized by minimizing the standard deviation of coating thickness subject to the constraint that the thickness mean would be very close to the target. The study resulted in achieving a coating thickness mean of 80.0199 microns for industrial enclosures, which is very close to the target value of 80 microns. A comparison of the results of the proposed approach with that of existing methodologies showed that the suggested method is equally good or even better than the existing methodologies. The result of the study is also validated with a new batch of industrial enclosures.

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Section: Methodsmentioning

confidence: 99%

A dual response surface optimization methodology for achieving uniform coating thickness in powder coating process

John¹

2015

10.5267/j.ijiec

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“…Chin et al (2006) propose an AHP based assessment system for supplier quality management. Pi and Low (2006) perform supplier evaluation and selection via Taguchi loss functions and AHP. de Boer et al (1998) present outranking methods in support of supplier selection.…”

Section: Related Workmentioning

confidence: 99%

Supplier Quality Evaluation Using a Fuzzy Multi Criteria Decision Making Approach

Awasthi

2014

Studies in Fuzziness and Soft Computing

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Supplier quality evaluation is a vital decision for buyer organizations. Every year, several organizations suffer not only monetary loss but waste of materials, man power, resources etc. due to poor quality product and services leading to loss of clientele and market reputation. In this paper, we address the problem of supplier quality evaluation and propose a multi-perspective fuzzy multicriteria decision making approach based on fuzzy TOPSIS. Four perspectives namely product quality, process quality, service quality, and organizational quality are considered to identify the supplier quality evaluation criteria. Supplier quality evaluation is performed by a committee of decision making experts who use linguistic assessments to rank the criteria and the suppliers in the lack of quantitative information. These assessments are then combined through fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is finally chosen and recommended for procurement. A practical application is provided. Sensitivity analysis and comparison with another approach called fuzzy SAW is performed for model verification and validation. The novelty of the proposed approach is supplier quality evaluation from multiple perspectives namely product quality, process quality, organizational quality, and service quality and ability to perform supplier quality evaluation under limited or lack of quantitative data.

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“…In available DSS methods, application of the AHP [23][24][25][26][27][28][29] to the project selection problem is not now in the art. Among formal decision tools' Satty's analytic network process (ANP) model [30] is assumed to be suitable for the project evaluation process.…”

Section: Related Workmentioning

confidence: 99%

A Novel Integrated AHP-QFD Model for Software Project Selection under Fuzziness

Bakshi¹,

Sarkar²,

Sanyal³

2012

IJCA

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Now-a-days software manufacturing companies usually try to capture market share with rapid software development. Actually the development of high quality software products can decrease cost by reducing rework and increasing productivity. For that, reason selection of software projects is an important task. Several factors come into consideration while selection of proper project for a specified job. To deal with this typical situation the current researchers combined the much known AHP(Analytic Hierarchy Process) with QFD (Quality Function Deployment). Here the AHP method redefined under fuzziness. Then QFD process is applied to identifying and ranking customer's need and translating them into product / service specification. At the last sensitivity analysis has been done to make the process more robust from the characterization of integration of the fuzzy AHP & QFD.

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Supplier evaluation and selection via Taguchi loss functions and an AHP

Cited by 101 publications

References 15 publications

A dual response surface optimization methodology for achieving uniform coating thickness in powder coating process

A dual response surface optimization methodology for achieving uniform coating thickness in powder coating process

Supplier Quality Evaluation Using a Fuzzy Multi Criteria Decision Making Approach

A Novel Integrated AHP-QFD Model for Software Project Selection under Fuzziness

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