Graph theory and matrix approach for performance evaluation of TQM in Indian industries

Kulkarni, S. S.

doi:10.1108/09544780510627615

Cited by 58 publications

(31 citation statements)

References 1 publication

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“…From literature it has been found that Wani and Gandhi (1999) have used data from previous research for selecting the values of the variables while Kulkarni (2005) used a questionnaire to measure each attribute in quantitative terms.…”

Section: Permanent Representation Of Gtpp System Matrixmentioning

confidence: 99%

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Evaluation of gas turbine power plant efficiency using graph theoretic approach

Dev

Attri

2016

Int J Syst Assur Eng Manag

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This paper presents a methodology based on graph theoretic approach (GTA) to design a new gas turbine power plant (GTPP), upgrading of existing plant and evaluation of two real life operating gas turbine power plants. Different combinations may be recommended by a manufacturer to an organization for selecting or improving the thermal efficiency of a power plant. This paper recognizes various design parameters affecting the gas turbine power plant efficiency. All these parameters are interacting with each other by different amounts. An attempt has been made to develop a mathematical model of GTPP from these interacting parameters using GTA. A GTPP efficiency index is proposed which assesses the influence power of these parameters.

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Section: Permanent Representation Of Gtpp System Matrixmentioning

confidence: 99%

“…The permanent function is a mathematical model that helps determine index that can be used for comparison. GTA is a systematic and logical approach that is applied in various disciplines (Jurkat and Ryser 1966;Deo 2000;Attri et al 2014;Faisal et al 2007;Wani and Gandhi 1999;Kulkarni 2005;Dev et al 2014c). …”

Section: Graph Theoretic Approach (Gta)mentioning

confidence: 99%

Evaluation of gas turbine power plant efficiency using graph theoretic approach

Dev

Attri

2016

Int J Syst Assur Eng Manag

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“…Note that, during this process, the permanent function, and neither the determinant function nor the permutation function (which totally differs in its meaning), is used to provide the complete information of the assessed alternative without any loss (see [51]). Some recent studies have successfully resolved the selection decisions or alternative ranking problems using this method [54][55][56][57][58]. Within the scope of GTMA, in addition to the abovementioned articles, there have been studies using the AHP-GTMA hybrid approach [59][60][61].…”

Section: Literature Reviewmentioning

confidence: 99%

Rank-Based Comparative Research Flow Benchmarking the Effectiveness of AHP–GTMA on Aiding Decisions of Shredder Selection by Reference to AHP–TOPSIS

et al. 2018

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The AHP–GTMA (analytic hierarchy process and graph theory and matrix approach) has been applied to select the best paper shredder before a company was making a bulk purchase order. However, there is a question as to whether one such relatively recent approach is effective to aid the selection decision problems in industrial/commercial practice. In this paper, a novel multi-measure, rank-based comparative research flow is proposed. The real decision problem case mentioned above is solved using the AHP–GTMA and the AHP–TOPSIS methods, respectively, with relevant datasets sourced. Several measures in the proposed flow, i.e., the arithmetical, geometrical, or even statistical ones, are multiplexed and used to validate the similarity between the rank order vectors (ROVs) (and thus between the final preferential orders determined over the alternatives) that are obtained using these two different methods. While AHP–TOPSIS is a confident multi-attribute decision-making (MADM) approach which has been successfully applied to many other fields, the similarity validated between these individual results using the proposed method is used to confirm the efficacy of the AHP–GTMA approach and to determine its applicability in practice. In addition, along with this study, some contributable points are also rendered for implementing the decision models, e.g., the optimized recursive implementation in R to compute the permanent value of a square ASAM (alternative selection attribute matrix, which is the computational basis required by AHP–GTMA) of any dimension. The proposed methodological flow to confirm the similarity based on the ordinal rank information is not only convenient in operational practice with ubiquitous tool supports (e.g., the vector-based R statistical platform), but also generalizable (to verify between another pair of results obtained using any other MADM methods). This gives options for future research.

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“…Digraph and matrix approach has been used extensively by a number of researchers in various engineering applications such as failure cause analysis [11], reliability evaluation [12], proactive fault identification [13], TQM evaluation [14,15], risk mitigation [16] and in other areas also. Digraph and matrix approach is a well systematic one which considers all the influencing factors (attributes) and its relative importance of one factor on the other on the objective.…”

Section: Interviewing Users To Identify Users' Needsmentioning

confidence: 99%

Analysis and evaluation of product design through design aspects using digraph and matrix approach

Paramasivam

Senthil²

2009

Int J Interact Des Manuf

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Product design evaluation is essential for all manufacturing industries to explore the soundness and effectiveness of the product design. This paper presents a mathematical model for evaluating and analyzing the product design alternatives using graph theory and matrix approach. In this paper, various contributing factors are identified and their relative importance has been considered. A digraph model is constructed to represent the abstract information of the product design which takes into account of all the factors and is much useful for visual analysis. The digraph model is converted into matrix form, which is used for computer processing. An index is obtained from the product design evaluation function, derived from the matrix for all product design alternatives and it shows the effectiveness of the product design. Indices are calculated for all product design alternatives and they are ranked in ascending order and the product design corresponding to the first rank is selected as best one. The proposed methodology is quite versatile from the point of view that it integrates all factors of the product design. An example has been included to illustrate the methodology proposed in this paper.Keywords Product design · Digraph and matrix approach · Product design evaluation index

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Graph theory and matrix approach for performance evaluation of TQM in Indian industries

Cited by 58 publications

References 1 publication

Evaluation of gas turbine power plant efficiency using graph theoretic approach

Evaluation of gas turbine power plant efficiency using graph theoretic approach

Rank-Based Comparative Research Flow Benchmarking the Effectiveness of AHP–GTMA on Aiding Decisions of Shredder Selection by Reference to AHP–TOPSIS

Analysis and evaluation of product design through design aspects using digraph and matrix approach

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