Multi-attribute decision making parametric optimization and modeling in hard turning using ceramic insert through grey relational analysis: A case study

• Published in: Decision Science Letters Vol. 5; no. 4; pp. 581 - 592
• Main Authors: Panda, Amlana, Sahoo, Ashok Kumar, Rout, Arun Kumar
• Format: Journal Article
• Language: English
• Published: Growing Science 2016
• Subjects: Flank wear; Grey relational analysis; Hard turning; Surface roughness; Taguchi
• DOI: 10.5267/j.dsl.2016.3.001
• ISSN: 1929-5804

Machining of hardened work materials with appropriate levels of process parameters is still a burning issue in manufacturing sectors and challenging. It is because of pressing demand of surface quality which adversely affected by evolution of tool wear. Therefore the present investigation is undertaken to make a decision on parametric optimization of multi-responses such as flank wear and surface roughness during machining hardened AISI 52100 steel (55±1) steel using mixed ceramic insert under dry environment through grey relational analysis combined with Taguchi approach. Also predicted mathematical models of 1st and 2nd order have been developed for responses and checked for its accuracy. Second order mathematical model presented higher R2 value and represents best fit of the model and adequate compared to first order model. Model indicates good correlations between the experimental and predicted results. The proposed grey-based Taguchi methodology has been proved to be efficient for solving multi-attribute decision making problem as a case study in hard machining environment.