Tool Life Prediction for Ceramic Tools in Intermittent Turning of Hardened Steel Based on Damage Evolution Model
نویسندگان
چکیده
منابع مشابه
designing an artificial neural network based model for online prediction of tool life in turning
artificial neural network is one of the most robust and reliable methods in online prediction of nonlinear incidents in machining. tool flank wear as a tool life criterion is an important task which is needed to be predicted during machining processes to establish an online tool life estimation system. in this study, an artificial neural network model was developed to predict the tool wear and ...
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Most published research works on the development of tool life model in machining of hardened steels have been mainly concerned with the turning process, whilst the milling process has received little attention due to the complexity of the process. Thus, the aim of present study is to develope a tool life model in end milling of hardened steel AISI D2 using PVD TiAlN coated carbide cutting tool....
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This paper describes an experimental investigation on machining of a difficult-to-cut material, AISI D2 steel of hardness 62 HRC with PCBN tools. It was found that the most feasible feeds and speeds fall in the ranges 0.08–0.20 mm/rev and 70–120 m/min, respectively and that most of the tested PCBN tools reached the end of life mainly due to flank wear. The highest acceptable values of tool life...
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Noteworthy results have been obtained in the turning and drilling of hardened high-strength steels using tungsten carbide based cutting tools. In a finish turning process, it was seen that surface roughness and tool flank wear followed very different trends against cutting time. The suggested explanation for this behaviour is that the profile cut into the workpiece surface is determined by the ...
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2011
ISSN: 1742-6596
DOI: 10.1088/1742-6596/305/1/012111