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International Heat Transfer Conference 15

ISSN: 2377-424X (online)
ISSN: 2377-4371 (flashdrive)

Experimental Investigation of the Work Piece Temperatures in Dry Orthogonal Metal Turning

Marc Deppermann
Institute of Heat and Mass Transfer, RWTH Aachen University

Hendrik Puls
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University

Michael Burghold
Institute of Heat and Mass Transfer, RWTH Aachen University

Reinhold Kneer
Institute of Heat and Mass Transfer, RWTH Aachen University, Augustinerbach 6, 52062 Aachen, Germany

Fritz Klocke
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University

DOI: 10.1615/IHTC15.mnf.009223
pages 5071-5079


KEY WORDS: Manufacturing, Conduction, dry machining

Abstract

Dry machining is one of the most important developments in manufacturing technology of metals due to its economic and ecological benefits. The investment costs for any cooling lubricant equipment are omitted as well as the running costs for the fluids and their proper disposal. The major disadvantage is the higher warming of the treated work piece compared to wet machining, which could cause dimensional deviations and profile defects. A steady heat flux from the primary cutting zone and the hot cutting tool flows into the work piece, causing very high local temperatures and a significant thermal expansion especially for long machining times. Up to the present day, there is no universal model to predict either the maximum temperatures of the work piece or the temperature distribution during dry turning based on the cutting parameters. The aim of the present investigation is to determine the dominant thermal mechanisms and temperature distributions of a basic orthogonal cutting process. The transient temperature distribution of the work piece is measured by an infrared camera with high spatial and temporal resolution. Based on these results, a numerical solver can be developed to calculate the associated heat source in future work, simulations of the cutting process can be developed and validated to predict and compensate thermal deviations.

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