Abstract
This paper investigates the unified theory of automation in process planning of the milling operation. The unified function has been developed based on the cost and rate of production. The unified objective function thus developed is supposed to act as a true arbiter of individual objective functions. The unified objective function is optimized under a large number of real-world constraints. Because of the discrete nature of machine settings the feed and speed are discretized, and integrality constraints are imposed on the feed and speed. Because of these constraints the process planning automation of the milling operation becomes a nonlinear mixed integer programming (NLMIP) problem. The approach has been illustrated with an example. The results obtained show relevance to real-world practice.
Published Version
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