Analysis of machining parameters effects on surface roughness: a review
Source: International Journal of Computational Materials Science and Surface Engineerin, Volume 5, Number 1, September 2012 , pp. 68-84(17)
Publisher: Inderscience Publishers
Abstract:This paper aims at presenting the effective parameters on surface roughness in machining process. Many investigations have been carried out on the offline or online machining parameters estimation. Both the optical and artificial intelligence (AI) techniques have been investigated to achieve the objective. AI-based methods which are divided into three branches, including the genetic algorithms (GA), knowledge-based expert systems, and artificial neural networks (ANN), have been discussed. Online or real time AI based systems for monitoring the machine surface roughness have also been described. The effective machining parameters have been categorised into six main branches: such as machine tool, workpiece, tool properties, cutting, thermal and dynamic parameters.
Keywords: COMPUTING AND MATHEMATICS; Computing Science, Applications and Software; SCIENCE, ENGINEERING AND TECHNOLOGY; Electronic Systems, Control and Artificial Intelli; Materials and Manufacturing; Nanoscience and Nanotechnology; Simulation and Modelling
Document Type: Research article
Affiliations: 1: Mechanical Engineering Department, Iran University of Industries and Mines (IUIM), North Kargar, 15th St., No. 86, Tehran, 1439763163, Iran. 2: Imam Hussein University, Babaee Freeway, Tehran, 1659756578, Iran. 3: Iran University of Science and Technology, Narmak, Tehran, 1684613114, Iran
Publication date: 2012-09-01
- The objective of the International Journal of Computational Materials Science and Surface Engineering is to establish an effective channel of communication between academic and research institutions and persons concerned with industrial research supported by practical application. It also aims at promoting and coordinating developments in the field of computational materials science and computational surface engineering by publishing original scientific papers which describe computer-aided methods of modelling, simulation and prediction for designing new engineering materials and the technological processes of the manufacturing in materials that are used for solving problems posed by materials and surface engineering professionsals, industrial managers and administrators, and technical education personnel.
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