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Minimization of tool path errors in high speed machining necessitates optimal design of machine tools and application of advanced control strategies. Analytical models that accurately represent interactions between the machine tool, workpiece and cutter prove necessary to accomplish these tasks. Two distinctive methods of modeling, suitable for the design of mechanical hardware and advanced control systems, are presented. One of these methods is highly intuitive and allows interactive model building [1]. The other method is more accurate and comprehensive but does not provide easy insight into the model development process and requires advanced software for performing symbolic computations [2]. Together, these methods form the basis of a systematic and stepwise modeling methodology and environment, and provide information needed for optimal design of a wide range of machine tools.

Cold extrusion and forging processes are complex. They require monitoring and controlling the appropriate parameters to ensure high productivity and continued competitiveness of North American press and manufacturing companies. Current average productivity rates in high-volume, high-tonnage operations are often less than 60 percent, and the lost production capacity is mainly due to equipment failures and unreliable process control. The results presented in this paper pertain to identifying root causes for lost production in an automated facility running multiple high tonnage capacity presses and the tools developed to monitor and control the key parameters to improve productivity and eliminate downtime due to catastrophic equipment failure. To gain insight into various equipment and process related phenomena that lower productivity, a spectrum of sensors was installed inside of the dies and on mechanical components of two identical presses in the facility.

Structural dynamics of machine tools causes deviations between the actual and NC programmed tool paths. These deviations, often negligible in traditional cutting, can become the major cause of errors in high speed machining. This paper presents new methods for: (1) model based assessment of the dynamic performance of machine tools, and (2) derivation of analytical models representing the structural dynamics. The assessment is accomplished by combining measurements obtained by means of the Heidenhain Cross Grid and multi-component, wide bandwidth accelerometers. The proposed performance assessment and modeling methods are illustrated by examples obtained for various machines at different feed speeds.