2018
DOI: 10.1016/j.matpr.2018.02.152
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Effect Of Machining Parameters On Cutting Tool Temperature And Tool Life While Turning EN24 And Hchcr Grade Alloy Steel

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Cited by 13 publications
(7 citation statements)
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“…Otherwise, the MTCVD TiCN/Al 2 O 3 //TiN proved to be better at turning the other steels. The authors also found that the hardness and microstructure of these steels were the limiting factor, meaning that the carbide fraction that is present in the steel microstructure limits tool life, due to the impact on the cutting edge, similar to the study presented in the beginning of the chapter by Asha et al [73].…”
Section: Tool Lifesupporting
confidence: 66%
See 1 more Smart Citation
“…Otherwise, the MTCVD TiCN/Al 2 O 3 //TiN proved to be better at turning the other steels. The authors also found that the hardness and microstructure of these steels were the limiting factor, meaning that the carbide fraction that is present in the steel microstructure limits tool life, due to the impact on the cutting edge, similar to the study presented in the beginning of the chapter by Asha et al [73].…”
Section: Tool Lifesupporting
confidence: 66%
“…Machining parameters also influence the tool's life, such as cutting speed, feed rate and even tool geometry, as there are some papers that study the influence of the micro-textures of cutting tools, relating their surface geometry with tool life [72]. Regarding the influence of machining parameters on cutting tool life, the study carried out by Asha et al [73], analyzes the effect of these parameters on cutting temperature and tool life while turning EN24 and HCHCr Grade alloy steel. The authors carried out tests where the cutting speed and feed rate were varied, and the depth of the cut was kept constant.…”
Section: Tool Lifementioning
confidence: 99%
“…30 Since influence of some factors is assumed as negligible and other factors are unknown, tool wear is considered as uncertain and relatively complex process. Reliability model is established according to equation (7), where C, p, and q are random constants variables. The model can be used to predict tool life reliability for various cutting parameters.…”
Section: Tool Life Reliability Analysismentioning
confidence: 99%
“…Numerous efforts have been made to increase the productivity of the machining process, including optimization of the cutting parameters, first of all cutting speed [7][8][9], development of novel coolants and lubricants, as well as methods of their supply into the cutting zone [10,11], and, most importantly, surface engineering of the cutting tool [12,13]. The deposition of the coatings on the cemented carbide tool substrate is one of the most commonly used ways of significantly enhancing the tool performance.…”
Section: Introductionmentioning
confidence: 99%