OPTIMIZATION OF TURNING PARAMETERS FOR SURFACE INTEGRITY PROPERTIES ON INCOLOY 800H SUPERALLOY USING CRYOGENICALLY TREATED MULTI-LAYER CVD COATED TOOL

A. Palanisamy and T. Selvaraj ()
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A. Palanisamy: Department of Production Engineering, National Institute of Technology, Tiruchirappalli 620015, Tamilnadu, India
T. Selvaraj: Department of Production Engineering, National Institute of Technology, Tiruchirappalli 620015, Tamilnadu, India

Surface Review and Letters (SRL), 2019, vol. 26, issue 02, 1-16

Abstract: In this work, an attempt has been made to optimize the process parameters on turning operation of INCOLOY 800H, with the aid of cryogenically treated (24h, 12h and untreated) multi-layer chemical vapor deposition (CVD) coated tools. The influencing factors like cutting speed, feed rate, depth of cut and cryogenic treatment were selected as input parameters. Surface roughness, microhardness and material removal rate (MRR) were considered as output responses. The experimentation was planned and conducted based on Taguchi L27 standard orthogonal array (OA) with three levels and four factors. Multi-criteria decision making (MCDM) methods like grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) have been used to optimize the turning parameters in this work. Similar results were obtained from these MCDM techniques. Analysis of variance (ANOVA) was employed to identify the significance of the process parameters on the responses. Experimental research proved that machining performance could be improved efficiently at cutting speed is 55m/min, feed rate is 0.06mm/rev, depth of cut is 1mm and 24h cryogenically treated tool. Tool wear was analyzed for the cutting tool machined at the optimum cutting condition with the help of scanning electron microscope (SEM) and energy dispersion spectroscopy (EDS). Dry sliding wear test was also conducted for the optimal condition. The percentage improvement in machining performances is 12.70%.

Keywords: Incoloy 800H; microhardness; cryogenic treatment; optimization; tool wear; wear test (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1142/S0218625X18501391

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