Machine tool selection using AHP and VIKOR methodologies under fuzzy environment

Ilangkumaran, M.; Sasirekha, V.; Anojkumar, L.; Raja, M. Boopathi

doi:10.1504/ijmom.2012.049133

Cited by 18 publications

(4 citation statements)

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“…Another challenge that might be encountered is associated with the importance of the criteria through the evaluation and benchmarking phases despite their conflict. In addition, this conflict between the criteria poses a significant challenge during the evaluation stage [49]. A suitable procedure for this kind of objectives needs to be developed whilst boosting the significance of a certain evaluation criterion and minimising others [50].…”

Section: Challenge Of Criteria Importancementioning

confidence: 99%

Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects

Albahri

Zaidan

Albahri

et al. 2020

Journal of Infection and Public Health

248

185

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Section: Challenge Of Criteria Importancementioning

confidence: 99%

Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects

Albahri

Zaidan

Albahri

et al. 2020

Journal of Infection and Public Health

248

185

View full text Add to dashboard Cite

“…Computer Aided Machine Tool Selection by Fuzzy AHP approach [15]. Fuzzy AHP and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) applied for machine tool selection and ranking by [16]. Genetic Algorithm machine tool selection problem developed by [17].…”

Section: Machine Tools Ranking and Selection With Madmsmentioning

confidence: 99%

Outsourcing of Machine Tools in Manufacturing Environment: A Review Paper

2017

IJAERD

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In return to new market requirement and competition in manufacturing industries and in order to provide high performance, cost effective products, there is a need of advance manufacturing machine tools. Selection process of machine tool has been very important issue for the companies for the years, because unsuitable selection of the machine tool might cause of many problems affecting precision, flexibility, negativity on productivity. Accordingly machine tool selection can be observed as a multiple-attribute decision making (MADM) problem. Generally, MADM methods deal with the process of selection of an alternative among number of different alternatives in the presence of usually conflict objectives and criteria. In the current research paper aims to provide the learning of the various multi attribute decision making techniques used for machine tool selection. Another Contribution is to transfer the complied information from research to their peer to support in designing or modeling the machine tool selection decision making system. This paper fulfills the demand of researchers in the field of machine tool selection.

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“…İç et al (2012) developed a component-based machining centre selection model based on AHP, which would use only the technical specifications while evaluating the machining centre components. Ilangkumaran et al (2012) developed an evaluation model based on AHP and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) methods under fuzzy environment for selection of the best machine tool among various alternatives. Taha and Rostam (2012) developed a DSS to select the best alternative machine tool using a hybrid approach of fuzzy AHP and PROMETHEE methods.…”

Section: Literature Review In Machine Tool Selectionmentioning

confidence: 99%

Development of a QFD-based expert system for CNC turning centre selection

Prasad

Chakraborty

2015

J Ind Eng Int

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Computer numerical control (CNC) machine tools are automated devices capable of generating complicated and intricate product shapes in shorter time. Selection of the best CNC machine tool is a critical, complex and time-consuming task due to availability of a wide range of alternatives and conflicting nature of several evaluation criteria. Although, the past researchers had attempted to select the appropriate machining centres using different knowledge-based systems, mathematical models and multi-criteria decision-making methods, none of those approaches has given due importance to the voice of customers. The aforesaid limitation can be overcome using quality function deployment (QFD) technique, which is a systematic approach for integrating customers' needs and designing the product to meet those needs first time and every time. In this paper, the adopted QFD-based methodology helps in selecting CNC turning centres for a manufacturing organization, providing due importance to the voice of customers to meet their requirements. An expert system based on QFD technique is developed in Visual BASIC 6.0 to automate the CNC turning centre selection procedure for different production plans. Three illustrative examples are demonstrated to explain the realtime applicability of the developed expert system.

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Machine tool selection using AHP and VIKOR methodologies under fuzzy environment

Cited by 18 publications

References 0 publications

Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects

Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects

Outsourcing of Machine Tools in Manufacturing Environment: A Review Paper

Development of a QFD-based expert system for CNC turning centre selection

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