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Optimization of a 2.5D milling process is generally considered to be one of the most significant issues for high-speed machining during mass production to amplify productivity and quality of production. Total time spent during 2.5D milling primarily comprises of productive and non-productive time. The productive time, cost and quality of production is highly influenced by machining parameters such as cutting speed, feed rate, width of cut (step over), depth of cut, tool diameter etc. Also selection of optimal machining conditions for better machining process efficiency is one of the key…mehr

Produktbeschreibung
Optimization of a 2.5D milling process is generally considered to be one of the most significant issues for high-speed machining during mass production to amplify productivity and quality of production. Total time spent during 2.5D milling primarily comprises of productive and non-productive time. The productive time, cost and quality of production is highly influenced by machining parameters such as cutting speed, feed rate, width of cut (step over), depth of cut, tool diameter etc. Also selection of optimal machining conditions for better machining process efficiency is one of the key factors for this problem. The objective of the present work is to identify and organize the controllable variables such that there is minimum effect of uncontrollable or noise variables on the process performance. The machining processes which maintain balance between cost and quality of production are presumed to be efficient. The movements of tool are synchronized with the help of automatically generated CNC codes. In the present work an attempt also been made on minimization of non-productive time by synchronizing cutting tool movements for malti pockets job problems.
Autorenporträt
Arun Kumar Gupta is presently serving as an Assistant Professor in the Department of Mechanical Engineering at the Vaish College of Engineering, Rohtak, INDIA. He is PhD from Mechanical Engineering Department, NIT Kurukshetra, INDIA. His current research interest areas include Industrial Automation, Mechatronics, Manufacturing and Soft Computing.