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Exploitation of the advanced manufacturing machine tool evaluation model under objective-grey information: a knowledge-based cluster with the grey relational analysis approach

Zitong He (School of Business Administration, University of Science and Technology Liaoning, Anshan, China)
Xiaolin Ma (School of Business Administration, University of Science and Technology Liaoning, Anshan, China)
Jie Luo (School of Geography and Tourism, Chongqing Normal University, Chongqing, China)
Anoop Kumar Sahu (Department of Quality and Operations Management, University of Johannesburg, Johannesburg, South Africa)
Atul kumar Sahu (Department of Industrial and Production Engineering, Guru Ghasidas Vishwavidyalaya, Bilaspur, India)
Nitin Kumar Sahu (Department of Industrial and Production Engineering, Guru Ghasidas Vishwavidyalaya, Bilaspur, India)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 15 October 2020

Issue publication date: 18 June 2021

Abstract

Purpose

Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical circumstances, i.e. production of high-quality of goods under feasible cost. AMMs are significant in holding the managers against their rivals and competitors with high profit margins. The authors developed the decision support mechanism/portfolio (DSM-P) consist of knowledge-based cluster approach with a dynamic model. The purpose of research work is to measure overall economic worth of AMMs under objective and grey-imperfect (mixed) data by exploring the proposed DSM-P.

Design/methodology/approach

The authors developed the DSM-P that consist of knowledge-based cluster, three multi-criteria decision-making (MCDM) techniques-1-2-3 with complementary grey relational analysis-4(GRA), approach with a dynamic model (complied by technical plus cost and agility measures of AMMs). The proposed DSM-P enables the manager to map the overall economic worth of candidate AMMs under objective and grey-mixed data.

Findings

The presented DSM-P assist the managers for handling the selection problem of AMMs, i.e. CNCs, robots, automatic-guided vehicle, etc under mixed (objective cum grey) data. To enable the readers for intensely understand the work, the utility of proposed approach is displayed by illustrating a polar robot evaluation and selection problem. It is ascertained that the robot candidate-11 alternative is fulfilling the entire technical cum cost and agility measures.

Originality/value

The DSM-P provides more precise and reliable outcomes due to a usage of the dominance theory. Under the dominance theory, the ranks are obtained by MCDM techniques-1-2-3 are compared with ranks gathered by the GRA-4 under objective cum grey data, formed the novelties in presented research work. From a future perspective, the grey-based models in DSM-P can be built/extended/constructed more extensive and can be simulated by the same approach.

Keywords

Citation

He, Z., Ma, X., Luo, J., Sahu, A.K., Sahu, A.k. and Sahu, N.K. (2021), "Exploitation of the advanced manufacturing machine tool evaluation model under objective-grey information: a knowledge-based cluster with the grey relational analysis approach", Grey Systems: Theory and Application, Vol. 11 No. 3, pp. 394-417. https://doi.org/10.1108/GS-03-2020-0028

Publisher

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Emerald Publishing Limited

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