Improvement Performance Characteristics of CNC Turning Operation by Exploit Immune System's Properties

• Main Authors: Jameel Abbas, Adnan, Minhat, Mohamad, Abd. Rahman, Md. Nizam
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: TS Manufactures; TJ Mechanical engineering and machinery
• Online Access: http://eprints.utem.edu.my/id/eprint/10927/1/Improvement_Performance_Characteristics_of_CNC_ICMSCE_2013.docx; http://eprints.utem.edu.my/id/eprint/10927/
• Institution: Universiti Teknikal Malaysia Melaka

This paper presents the application of artificial immune system (AIS) intelligent algorithm for multiple output optimization of two passes dry CNC turning operation. In this work, a mild steel work piece type (A36) and tungsten carbide insert cutting tool type (SPG4220) use for theoretical calculations. Three types of objective functions are utilized as optimization criteria, the first one estimate the chip-tool interface temperature where the heat is generated due to rubbing or shearing between the chip and cutting tool rake face. The second and third objective functions calculate the work piece surface roughness and operation cutting time respectively. Optimum values of machining parameters (cutting speed, feed rate and depth of cut) are calculated by AIS algorithm to achieve the requirements of ideal chip- tool interface temperature, work piece surface roughness and operating cutting time. The ideal values (4.9 mm depth of cut, 1.3 mm /rev feed rate and 79 m / min cutting force) accomplished an ideal performance of (132 Cо cutting temperature, 0.0005µm surface roughness and 0.45 S cutting time). The results illustrate that the feed rate has a huge affect on cutting time and surface roughness and the cutting speed largely affects on the cutting time while the depth of cut is more affect on the surface roughness