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Tzivelekis C.A.,Northumbria University | Yiotis L.S.,Laboratory of Manufacturing Processes and Machine Tools LMProMaT | Fountas N.A.,Laboratory of Manufacturing Processes and Machine Tools LMProMaT | Krimpenis A.A.,Technological Educational Institute of Central Greece TEICG
International Journal on Interactive Design and Manufacturing | Year: 2015

For product lifecycle management reasons, research trends impose the need of automated engineering tasks, such as computer-aided design and manufacturing. This paper proposes a novel approach of automating both the design and manufacturing processes of impeller-type geometries, when CAD/CAM technology is employed. To do so, a newly developed application was built; exploiting application programming interface objects of parametric instances, in order to automate time-consuming repetitive tasks for the preparation of 3D models and their direct manufacturing process. The developed application incorporates Simpson’s method, Bezier-Bernstein equation and Non-Uniform Rational B-Spline for curve approximation describing blades of centrifugal impellers, as a representative case study. The machining technology is that of 3-axis CNC, thereby; each curve extends along a constant x-y plane. In the first step of the application, the entire 3D model of the impeller-type model is automatically generated according to variable values taken as user-defined entities from the interface. The application then carries on by automatically modeling the manufacturing process and ultimately generating the NC program from the cutter location data for a given CNC machine tool. © 2015 Springer-Verlag France Source


Krimpenis A.A.,Technological Educational Institute of Central Greece TEICG
Advances in Manufacturing | Year: 2016

This paper presents results obtained from the implementation of a genetic algorithm (GA) to a simplified multi-objective machining optimization problem. The major goal is to examine the effect of crucial machining parameters imparted to computer numerical control machining operations when properly balanced conflicting criteria referring to part quality and process productivity are treated as a single optimization objective. Thus the different combinations of weight coefficient values were examined in terms of their significance to the problem’s response. Under this concept, a genetic algorithm was applied to optimize the process parameters exist in typical; commercially available CAM systems with significantly low computation cost. The algorithm handles the simplified linear weighted criteria expression as its objective function. It was found that optimization results vary noticeably under the influence of different weighing coefficients. Thus, the obtained optima differentiate, since balancing values strongly affect optimization objective functions. © 2016, Shanghai University and Springer-Verlag Berlin Heidelberg. Source

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