Fredrik Kantojärvi , Elias Vikenadler , Daniel Johansson , Sören Hägglund , Rachid M’Saoubi
{"title":"Predicting tool life for side milling in C45 E using Colding and Taylor tool life models","authors":"Fredrik Kantojärvi , Elias Vikenadler , Daniel Johansson , Sören Hägglund , Rachid M’Saoubi","doi":"10.1016/j.aime.2023.100126","DOIUrl":null,"url":null,"abstract":"<div><p>This paper investigates the possibility of using empirical tool life models to predict tool life in a side milling application in a medium carbon steel, C 45E. To do this, an extensive dataset containing 46 data points with different machining parameters are produced. Four different empirical models: Taylor’s equation, Colding’s equation and Extended Taylor both using depth of cut and feed as well as an Extended Taylor using equivalent chip thickness has been considered. It is found that Colding’s equation is best suited to predict the tool life for this application. Furthermore, this paper suggests a novel method to fit the experimental data to the empirical models. Based on the results from previously published papers it is shown that the proposed method performs equally or better to determine the model constants.</p></div>","PeriodicalId":34573,"journal":{"name":"Advances in Industrial and Manufacturing Engineering","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Industrial and Manufacturing Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666912923000156","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
This paper investigates the possibility of using empirical tool life models to predict tool life in a side milling application in a medium carbon steel, C 45E. To do this, an extensive dataset containing 46 data points with different machining parameters are produced. Four different empirical models: Taylor’s equation, Colding’s equation and Extended Taylor both using depth of cut and feed as well as an Extended Taylor using equivalent chip thickness has been considered. It is found that Colding’s equation is best suited to predict the tool life for this application. Furthermore, this paper suggests a novel method to fit the experimental data to the empirical models. Based on the results from previously published papers it is shown that the proposed method performs equally or better to determine the model constants.