Development of a software-automated intelligent sculptured surface machining optimization environment

Fountas, Nikolaos, Vaxevanidis, Nikolaos, Stergiou, Constantinos and Benhadj-Djilali, Redha (2014) Development of a software-automated intelligent sculptured surface machining optimization environment. The International Journal of Advanced Manufacturing Technology, 75(5-8), pp. 909-931. ISSN (print) 0268-3768

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Abstract

To ensure the quality of machined products at minimum cost and maximum effectiveness, it is crucial that selection of optimum machining parameters should be done when computer numerically controlled (CNC) machine tools technology is employed. Traditionally, experience of the operator plays a major role in the selection of efficient parameter values; however, attaining optimum ones each time by even skilled end users, is extremely difficult. This paper takes advantage of the possibilities of current computer-aided design (CAD)/computer-aided manufacturing (CAM) technology and implements a genetic algorithm for optimising CNC machining operations mainly for sculptured surfaces. The algorithm has been developed as a hosted application to a cutting-edge CAD/CAM system. Collaboration among applications has been achieved through programming for software automation by utilising the application programme interface of the system. The approach was implemented to a group of test sculptured models with different properties whilst one of them has been actually machined using typical resources. Results obtained after the implementation indicated that the methodology is capable of providing optimum values for process parameters on its way to maintain both productivity and high quality.

Item Type: Article
Research Area: Computer science and informatics
Mechanical, aeronautical and manufacturing engineering
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing > School of Mechanical and Automotive Engineering
Depositing User: Redha Benhadj-Djilali
Date Deposited: 01 Dec 2014 17:16
Last Modified: 01 Dec 2014 17:16
URI: http://eprints.kingston.ac.uk/id/eprint/29064

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