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Robert W. Ivester, Michael Kennedy, Matthew A. Davies, R Stevenson, J Thiele, R Furness, S M. Athavale
Abstract
Machining involves extremely localized and nonlinear physical phenomena that occur over a wide range of temperatures, pressures, and strains. This has hindered progress in predictive modeling of machining processes. Many different types of models ranging from theoretical to empirical have been developed, but the wide variety of the models makes assessment difficult. The difficulty in assessing the performance of machining models has been cited by industry as the major factor that limits the use of modern machining models in industry. Thus, current practices in industry are either to use conservative machining settings and tool-change policies, or to conduct costly empirical studies for a limited selection of tools and coolants. Either practice may lead to sub-optimal process performance. The goal of the Assessment of Machining Models project is to assess the ability of modern machining models to predict the outputs of machining processes based upon data typically available on the shop floor. In order to achieve this goal, the participating laboratories plan to develop and provide a clear, consistent, well-measured and relevant data set, and use that data set to benchmark the predictive capability of machining models in blind tests. This paper presents the project motivation, goals, and some representative results.
Ivester, R.
, Kennedy, M.
, Davies, M.
, Stevenson, R.
, Thiele, J.
, Furness, R.
and Athavale, S.
(2000),
Assessment of Machining Models: Progress Report, 50th CIRP General Assembly, Sydney, AS
(Accessed October 14, 2025)