This paper presents a computer aided design for machining (DFMc) platform that enables designers to customize the design for the available machine tools and to estimate the effect of design decisions on the accuracy of the final machined products, particularly those containing sculptured surfaces. The platform contains two modules to model and simulate the actual machined surface and to evaluate the resulting minimum deviation zone compared to the desired geometry. In the first module, based on the configuration of the available machine tool and the limitations imposed by its inherent errors, the machined surface is simulated and presented as a nonuniform rational B-spline (NURBS) surface. In the second module, the minimum deviation zone between the actual and the nominal NURBS surfaces is evaluated when the developed method to do this task efficiently improves the convergence of the resulting optimization process. Utilizing this platform, two different applications are developed; design tolerance allocation based on the minimum deviation zone of the machined surface and adaptation of the nominal design to compensate for the effect of machining errors. Employing these applications during the design stage improves the acceptance rate of the produced parts and reduces the rate of scrap and rework. The DFMc platform and its presented applications can be implemented in any integrated computer aided design/computer aided manufacturing (CAD/CAM) system. The presented methods can be applied to any type of input geometries and are particularly efficient for design and manufacturing of precise components with complex surfaces. Products in this group, such as dies and tools, medical instruments, and biomedical implants, mostly have critical and important functionalities that demand very careful design and manufacturing decisions.
Design for Manufacturing of Sculptured Surfaces: A Computational Platform
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Barari, A., ElMaraghy, H. A., and ElMaraghy, W. H. (June 4, 2009). "Design for Manufacturing of Sculptured Surfaces: A Computational Platform." ASME. J. Comput. Inf. Sci. Eng. June 2009; 9(2): 021006. https://doi.org/10.1115/1.3130143
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