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Stainless steel is widely used as material in many industries and medicine. As biomedical material, it has been used for making devices, implants as well as tools and equipment in surgery and dentistry. The most of them is processed by turning. Modeling of temperature in the metal cutting process is very important step in understanding and analysis of the metal cutting process. The objective of this study is to develop an artificial neural network model which can be used successfully for accurate prediction of cutting temperature while performing turning of the biomedical stainless steel. Before the modeling, cutting temperature was measured, as one of the significant parameters in turning process, by using the infrared thermal imaging camera. Finally, based on the mathematical model, the effects of the turning parameters on the cutting temperature were examined.
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