Multiobjective optimization of performance characteristics in turning of AZ91 Mg alloy using grey relational analysis. (2021)

• Record Type: Journal Article
• Authors: Vasu, Ch; Andhare, Atul B.; Dumpala, Ravikumar
• Is Part Of: Materials today. Volume 42:Part 2(2021)
• Page Start: 642
• Page End: 649
• Publication Date: 2021
• Subjects: Magnesium alloy -- Optimization -- GRA -- Surface roughness -- Turning -- Cutting force; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2020.11.049
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: In recent decades, magnesium and its alloys have attracted more attention because of their exceptional mechanical properties. These Mg alloys are known for their high strength to weight ratio and found enormous applications in automobile and aeronautical industries. Machining of these alloys is always a challenge because of the issues related to the work surface integrity. In the present work, an experimental study on turning of AZ91 Mg alloy using the uncoated carbide tools in dry condition has been presented. This work comprises input factors such as cutting tool edges (45° and 90°), cutting speed, and feed rate. The full factorial experimentation has been performed for the analysis. And the optimization of the performance characteristics (surface finish and main cutting forces) is done by using grey relational analysis. Finally, the GRA method provided the optimal conditions for achieving the minimum surface roughness and minimum cutting forces are at cutting edge angle 90° (A2), cutting speed 270 m/min (V2), and feed rate 0.04 mm/rev (F1). The next optimal conditions close to desired outputs are at cutting edge angle 45° (A1), cutting speed 200 m/min (V1), and feed rate 0.04 mm/rev (F1). Chip morphology (size and shape) were also studied and found that the continuous type chip formation at a lower feed rate (0.04 mm/rev) and at the machining speed of 270 m/min, using both the cutting tool edges (45° and 90°).