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Development of mathematical model for describe the thermal behaviour in machining tool

Grant number: 12/22194-9
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): March 06, 2013
Effective date (End): October 05, 2013
Field of knowledge:Engineering - Mechanical Engineering - Manufacturing Processes
Principal researcher:Reginaldo Teixeira Coelho
Grantee:Cláudia Hespanholo Nascimento
Supervisor abroad: Philip Koshy
Home Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Research place: McMaster University, Canada  
Associated to the scholarship:10/19203-0 - Study of Dimensional Deviations in Machined Parts Caused by Heating, BP.DR

Abstract

Taking into account the new technologies of high performance machining, the research works in precision machining has grown in number for the past years. For CNC machine tools, its positioning accuracy can be related, in a large extent, with distortions cause by several thermal sources inside it. Thus, the study to minimize thermal distortion problems in machine tool is becoming increasingly important. The need for accurate measurement techniques and uncertainty estimates is obvious and the issue of thermal distortion can cause problems in machining process when tolerances must be met. Every manufactured part will vary in its dimensions as environment or machine parts temperatures changes.Therefore, this study aims at experimentally measure temperature variation and dimensional distortion due to several working cycles and, subsequently, develops a numerical model which predicts the distortion errors caused by them. An error compensation model will be developed and tested through Finite Element Analysis (FEA) in ABAQUS software. Structural analysis in machine tools using the FEA already is an important tool to predict the machine behavior and can determine the best stiffness and strain configuration. In the working cycle of a machine tool, the thermal deformations are non-linear and time-variant according to the change of environment conditions and operating conditions. That indicates how complex is the thermally induced errors and becomes a challenge to determine a numeric model for error compensation. The input parameters for the study will be the thermal data acquired with the experimental set up during the several heating cycle conditions. Model output parameter will be the position and distortion errors. The numerical results will be compared with results obtained in Laboratory for Optmization of Manufacturing Process. (AU)

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