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

Attri, Rajesh; Dev, Nikhil; Kumar, Kishor; Rana, A.S.

doi:10.1504/ijids.2014.066636

Cited by 8 publications

(1 citation statement)

References 49 publications

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“…There are various MCDM techniques which are accessible in the writing to empower the inventors to assemble the superior option, in most of these techniques, the alternative rankings are influenced by the measure weight and are very strenuous to fathom and cloud to execute needful widespread mathematical complexity. It contains several strategies, specifically, grey relation analysis, preference ranking organization method for enrichment evaluations, elimination and choice translating reality, compromise ranking method, technique for order preference by similarity to ideal solutions and analytic hierarchy method which have been effectively used to take care of numerous decision-making issues Attri et al [37], Mesran et al [38] and Madić et al [39]. The PSI approach is more generalized to understand as compared to all MCDM techniques as it doesn't contain any comparative importance between the standards and the overall preference value which is attained by using the statistical concept.…”

Section: Introductionmentioning

confidence: 99%

Selection of Erosive Wear Rate Parameters of Pelton Turbine Buckets using PSI and TOPSIS Techniques

Thakur¹,

Kumar²,

Kashyap³

et al. 2019

IJITEE

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Hydro turbine machineries erosion due to silt is a complex issue for the effective practice of hydropower plants. Erosion caused by silt of the Pelton turbine buckets is a compound phenomenon that depends on size of silt particles , silt particles concentration , velocity of jet , and working time . This paper deals with the influence of silt erosion for various silt loaded factors and effective parameters. The preference selection index (PSI) and technique for order of preference by similarity to ideal solution (TOPSIS) approaches has been adopted to find optimal set of parameters which offers the highest performance for the Pelton turbine. Based up on the results obtained from both PSI and TOPSIS approaches it is found that optimal performance has been provided by A-1 alternate with geometric and flow parameters as , , and respectively

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Section: Introductionmentioning

confidence: 99%

Selection of Erosive Wear Rate Parameters of Pelton Turbine Buckets using PSI and TOPSIS Techniques

Thakur¹,

Kumar²,

Kashyap³

et al. 2019

IJITEE

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show abstract

Development of Fuzzy-Single Valued Neutrosophic MADM Technique to Improve Performance in Manufacturing and Supply Chain Functions

Nirmal¹,

Bhatt²

2018

Fuzzy Multi-Criteria Decision-Making Using Neutrosophic Sets

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Application of combined MADM methods as MOORA and PSI for ranking of FMS performance factors

Jain

2018

BIJ

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Purpose Due to the increasing demand of customer and competitive market pressure, manufacturing organizations should be modernized in strategies, production operations, processes and its procedures to remain competitive. So, a flexible manufacturing system (FMS) was adopted by the manufacturing system to fight with competitive pressure. The purpose of this paper is to enhance the performance of manufacturing system, with a focus on its factors. Design/methodology/approach In this research, the ranking of the performance factor of FMSs is done by using multiple attribute decision-making (MADM) methods as multi-objective optimization on the basis of ratio analysis (MOORA) and preference selection index (PSI). Weights of attributes are defined by the AHP method. Findings Ranking of performance factor is done on the basis of six variables which affect three elements of performance of FMS, i.e. productivity, flexibility and quality. MOORA is applied in three ways such as the ratio-based, reference point and full multiplicative method. In the MOORA method, ranking was done considering weights of attributes and also without it. A PSI method is used to find the best factor among the factors. The results of these methodologies, i.e. MOORA and PSI, are same, i.e. productivity is the primary factor in the manufacturing system. The ranking is validated by the result of different methodology used in this research. Practical implications This research has evaluated the important factors and performance variables which can enhance the performance of manufacturing organizations. So, the manufacturing persons can focus on these to enhance its performance. Originality/value Combined MADM methods, i.e. MOORA and PSI methodologies, are used in this paper to deal with the ranking of performance factors of the FMS considering qualitative characteristics. These approaches show the conversion of a qualitative attribute to quantitative attributes by using fuzzy logic.

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

Cited by 8 publications

References 49 publications

Selection of Erosive Wear Rate Parameters of Pelton Turbine Buckets using PSI and TOPSIS Techniques

Selection of Erosive Wear Rate Parameters of Pelton Turbine Buckets using PSI and TOPSIS Techniques

Development of Fuzzy-Single Valued Neutrosophic MADM Technique to Improve Performance in Manufacturing and Supply Chain Functions

Application of combined MADM methods as MOORA and PSI for ranking of FMS performance factors

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