The selection of flexible manufacturing system using preference selection index method

Maniya, Kalpesh D.; Bhatt, M. G.

doi:10.1504/ijise.2011.043142

Cited by 32 publications

(17 citation statements)

References 48 publications

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“…In the past few decades, a good number of researchers have proposed and applied many decision-making techniques to guide in dealing with the issue of evaluation and selection of advanced manufacturing technologies, like FMS for specific industrial applications. Analytic hierarchy process (AHP) [6][7][8][9], data envelopment analysis (DEA) [10][11][12][13][14], mixed integer linear programming model [15], intelligent tools and expert systems [16], decision algorithm based on fuzzy set theory [17], TOPSIS [18], fuzzy multi-objective programming [19], axiomatic design method [20], digraph and matrix approach [21], artificial neural network [22], combinatorial mathematics [23], PROMETHEE [24], analytic network process (ANP) [25], preference selection index (PSI) method [26], GRA [27], principal component analysis (PCA) [28] etc methods have been apllied to solve the FMS selection problems. Although, MCDM methods are observed to have immense potential to deal with such complex decision-making problems in conflicting situations, no effort yet been put to show the effet of normalization techniques on the ranking performance of MCDM methods while solving the FMS slection problems in discrete m,anufacturing environment.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Effect of Normalization Norms in Flexible Manufacturing Sytem Se-lection Using Multi - Criteria Decision - Making Methods

Chatterjee¹,

Chakraborty²

2014

JESTR

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The main objective of this paper is to assess the effect of different normalization norms within multi-criteria decisionmaking (MADM) models. Three well accepted MCDM tools, namely, preference ranking organization method for enrichment evaluation (PROMETHEE), grey relation analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) methods are applied for solving a flexible manufacturing system (FMS) selection problem in a discrete manufacturing environment. Finally, by the introduction of different normalization norms to the decision algorithms, its effct on the FMS selection problem using these MCDM models are also studied.

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Section: Introductionmentioning

confidence: 99%

Investigating the Effect of Normalization Norms in Flexible Manufacturing Sytem Se-lection Using Multi - Criteria Decision - Making Methods

Chatterjee¹,

Chakraborty²

2014

JESTR

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“…The steps involved in PSI methodology are as follows (Maniya and Bhatt, 2010, 2011b, 2013Vahdani et al, 2011;Sawant et al, 2011;Joseph and Sridharan, 2011):…”

Section: Psi Methodsmentioning

confidence: 99%

Selection of cutting-fluids using a novel decision-making method: preference selection index method

Attri

Dev

Kumar

et al. 2014

IJIDS

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This paper presents a simple and systematic multi-criteria decision making methodology to select a cutting fluid for the given application using the preference selection index (PSI) method. In this methodology, cutting fluid is selected for a given machining application without considering relative importance between the selection attributes. Two real time examples are cited from the literature in order to demonstrate and validate the applicability and potentiality of PSI method in solving the cutting-fluid selection problem. It is observed that the relative rankings of the alternative cutting fluid as obtained using PSI method match quite well with those as derived by the past researchers.Reference to this paper should be made as follows: Attri, R., Dev, N., Kumar, K. and Rana, A. (2014) 'Selection of cutting-fluids using a novel decision-making method: preference selection index method', Int.

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“…Rao and Singh (2011) used Euclidean distance-based integrated approach (EDBA) to solve the same problem having linguistic terms in the decision matrix. Maniya and Bhatt (2011) solved the same problem using preference selection index method. Karande and Chakraborty (2013) used MACBETH software to select the best FMS.…”

Section: Examplementioning

confidence: 99%

Interval valued multi criteria decision making methods for the selection of flexible manufacturing system

Mathew¹,

Thomas²

2019

10.5267/j.ijdns

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In real world multi criteria decision making (MCDM) problem, it is tough to solve a decision matrix with vague and imprecise data. The degree of impreciseness depends on the kind of data available. For interval valued data this impreciseness is less and interval-valued MCDM methods can be effectively used to solve the problem. A flexible manufacturing system (FMS) selection problem was taken into consideration to find the best FMS among available alternatives. An interval extension of CODAS method is proposed in this paper which was used to solve the problem along with two other interval-valued decision-making methods i.e. interval-valued TOPSIS, interval-valued EDAS. All the three methods are distance-based approaches and it was found that the interval-valued CODAS method gave the exact same ranking with that of interval-valued TOPSIS and interval-valued EDAS.

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The selection of flexible manufacturing system using preference selection index method

Cited by 32 publications

References 48 publications

Investigating the Effect of Normalization Norms in Flexible Manufacturing Sytem Se-lection Using Multi - Criteria Decision - Making Methods

Investigating the Effect of Normalization Norms in Flexible Manufacturing Sytem Se-lection Using Multi - Criteria Decision - Making Methods

Selection of cutting-fluids using a novel decision-making method: preference selection index method

Interval valued multi criteria decision making methods for the selection of flexible manufacturing system

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