THERMAL EFFECTS ON THE ACCURACY OF NUMERICALLY CONTROLLED MACHINE TOOLS (NUMERICAL METHODS, EXPERIMENTAL)

RAGHUNATH VENUGOPAL, Purdue University

Abstract

Thermal effects on the accuracy of numerically controlled machine tool are specially important in the context of unmanned manufacture or under conditions of precision metal cutting. Removal of the operator from the direct control of the metal cutting process has created problems in terms of maintaining accuracy. The objective of this thesis is to study thermal effects on the accuracy of numerically controlled machine tools. The initial part of the thesis is concerned with the analysis of a hypothetical machine. The thermal characteristics of this machine are studied. Numerical methods for evaluating the errors exhibited by the slides of the machine are proposed and the possibility of predicting thermally induced errors by the use of regresssion equations is investigated. A method for computing the workspace error is also presented. Machine tools are generally made of box type structures. Based on analysis of box type structures, theoretical evidence for the prediction of machine tool errors is presented. The problem of heat flow in a box made of thin plates is studied and analytic solutions are derived. The final part is concerned with the actual measurement of errors on a modern CNC machining center. Thermal influences on the errors is the main objective of the experimental work. Based on experimental evidence, it is shown that thermal effects on the accuracy of machine tools can be predicted by the use of simple regression equations. Finally, numerical methods are used to predict thermal influences on the errors of machine tools. These methods make use of measured values of temperatures for prediction of errors. Based on the evidence presented in this thesis, it is shown conclusively that thermal influences on the errors of machine tools are predictable. Techniques for determining thermal effects on machine tools at a design stage are also presented.

Degree

Ph.D.

Subject Area

Industrial engineering

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