PREDICTIVE MODELING OF SURFACE ROUGHNESS, MATERIAL REMOVAL RATE AND KERF USING MULTIPLE REGRESSION ANALYIS IN PLASMA ARC CUTTING PROCESS OF HARDOX AND ABREX STEEL

Deepak Kumar Naik () and Kalipada Maity
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Deepak Kumar Naik: Department of Mechanical Engineering, Sree Vidyanikethan Engineering College (Autonomous), Tirupati, Andhra Pradesh 517102, India
Kalipada Maity: #x2020;Department of Mechanical Engineering, National Institute of Technology, Rourkela 769008, Odisha, India

Surface Review and Letters (SRL), 2020, vol. 27, issue 09, 1-12

Abstract: Plasma arc cutting (PAC) process is widely used in metal cutting industries and modern fabrication units. Precise cutting of high strength material is still a challenging task to the industries. PAC process uses thermal energy to melt the material through highly energized plasma gas. Mostly, “hard-to-cut” type materials is used to cut through this process to meet the demands. The present work proposes an experimental investigation of PAC process of hardox 400 and abrex 400. Both the materials are high strength and high abrasion resistance in nature. Experiments were conducted based on Taguchi’s L25 orthogonal array design. The cutting parameters analyzed were arc current, cutting speed, stand-off distance and supply gas pressure whereas material removal rate, kerf and surface roughness were selected as responses. Also, a prediction model was developed to estimate the responses using multiple regression analysis. A comparison between experimental and predicted result shows the accuracy of the model. Analysis of variance (ANOVA) was used to verify the effect of each parameter on the surface quality to be assessed.

Keywords: Hardox; Abrex; Kerf; regression analysis (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0218625X19502068

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