Tool damage state condition monitoring in milling processes based on the mechanistic model goodness-of-fit metrics

被引:20
作者
Asadzadeh, Mohammad Zhian [1 ]
Eibo, Andreas
Geanser, Hans-Peter
Kluensner, Thomas [1 ]
Muecke, Manfred [1 ]
Hanna, Lukas [1 ]
Teppernegg, Tamara [2 ]
Treichler, Martin [3 ]
Peissl, Patrick [4 ]
Czettl, Christoph [2 ]
机构
[1] Mat Ctr Leoben Forsch GmbH MCL, Roseggerstr 12, A-8700 Leoben, Austria
[2] Ceratizit Austria GmbH, Metallwerk-Plansee Str 71, A-6600 Reutte, Austria
[3] Tool Consulting & Management GmbH, Technologiepark 3, A-8510 Stainz, Austria
[4] Ro Ra Aviat Syst, Gewerbepark 8, A-4861 Schorfling, Austria
关键词
Milling; Condition monitoring; Tool wear; Cumulative sum status chart; Cutting edge fracture; NEURAL-NETWORK; CUTTING COEFFICIENTS; BREAKAGE DETECTION; ACOUSTIC-EMISSION; WEAR; FORCE; SENSOR; IDENTIFICATION; DECOMPOSITION; PREDICTION;
D O I
10.1016/j.jmapro.2022.05.034
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Monitoring of the end milling tool wear in real-time is very crucial for the quality control of a surface finish. In the model-based approaches, usually the tool wear is monitored by tracking the force model coefficients during the milling operation. In this work, we explore a monitoring approach based on two metrics derived from the goodness-of-fit of the milling mechanistic model. The cumulative sum control charts are constructed to monitor changes occurring to the tool condition during a milling operation. Compared to previously suggested methods based solely on the values of force model coefficients, our approach facilitates a preciser and less conservative identification of the point of transition from homogeneous wear to onset of breakout formation at the cutting edges. The proposed strategy is an alternative approach for real time monitoring of tool condition based on mechanistic models.
引用
收藏
页码:612 / 623
页数:12
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