A framework for in-line milling process optimisation

This work proposes a possible framework for implementing model-based optimization of process parameters in a milling operation. The latter is the first step in the development of an artificial machine tool operator, i.e. a supervising controller that looks at the process status and continuously estimate an optimal set of controls on the basis of a given process model. After a description of the software architecture, the discussion on the process model adopted for the definition of the target function, and the illustration of the optimization algorithm (the Nelder-Mead Method), the paper presents the results obtained from the application of the optimization system to two different case studies, showing how the same part-program can be run with significant improvements in productivity when the feed rate and spindle speed overrides are continuously varied during the machining according to profiles calculated by the proposed process optimization system. Copyright © 2013 by ASME.