Fountas, N., Vaxevanidisa, N., Stergiou, C. and Benhadj-Djilali, R. (2015) Evaluation of 3- and 5-axis sculptured surface machining in CAM environment through design of experiments. International Journal of Computer Integrated Manufacturing, 28(3), pp. 278-296. ISSN (print) 0951-192X
Abstract
Sculptured surface machining (SSM) is an operation widely applied to several industrial fields such as aerospace, automotive and mould/die. The number of the parameters and strategies involved to program such machining operations can be enormously large owing to surface complexity and advanced design features. This study focuses on the examination of machining strategies and related parameters for the assessment of roughing and finishing stages. A fractional factorial design implementing an L27 Taguchi orthogonal array (OA) was established to conduct machining experiments with the use of a computer-aided manufacturing (CAM) software. Fractional factorial design specifics involve the statistical elimination of unimportant parameters, thus reducing experimental runs without the loss of useful information. Two scenarios were considered to machine a sculptured part; one involving 3-axis roughing/3-axis finish machining experiments and the other one involving 3-axis roughing/5-axis finish machining experiments. Roughing operation was common for both scenarios. The problem was subjected to discrete technological constraints to reflect the actual industrial status. For each machining phase, two quality objectives reflecting productivity and part quality were determined. Roughing experiments were tested to minimise machining time and remaining volume, whilst finishing experiments were subjected to minimise machining time and surface deviation between the designed and the machined 3D model. Quality characteristics were properly weighted to formulate a single objective criterion for both machining phases. Results indicated that DOE applied to CAM software, enables NC programmers to have a clear understanding about the influence of process parameters for SSM operations, thus generating efficient toolpaths to improve productivity, part quality and process efficiency. Practically the work contributes to machining improvement by through the proposition of machining experimentation methods using safe and useful platforms such as CAM systems; the investigation of approaches to avoid problem oversimplification mainly when large number of machining parameters should be exploited and the evaluation of quality criteria which allow their assessment directly form CAM software.
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