Tool wear modelling using micro tool diameter reduction for micro-end-milling of tool steel H13

• Published in: International journal of advanced manufacturing technology Vol. 105; no. 5-6; pp. 2531 - 2542
• Main Authors: Manso, C. S., Thom, S., Uhlmann, E., de Assis, C. L. F., del Conte, E. G.
• Format: Journal Article
• Language: English
• Published: London Springer London 01.12.2019; Springer Nature B.V
• Subjects: Aluminum; CAE) and Design; Computer-Aided Engineering (CAD; Cutting parameters; Cutting tools; Cutting wear; Diameters; End milling; Engineering; Industrial and Production Engineering; Mathematical models; Mechanical Engineering; Media Management; Microtools; Miniaturization; Modelling; Order parameters; Original Article; Production planning; Reduction; Size effects; Slot milling; Teeth; Tolerances; Tool life; Tool steels; Tool wear; Variance analysis; Workpieces; Full slot milling; Machining parameters; Tool wear; Micro milling
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-019-04575-4

Micro components have been demanded increasingly due to the global trend of miniaturization of products and devices. Micro milling is one of the most promising processes for micro-scale production and differs from conventional milling due to the size effect introducing phenomena like the minimum chip thickness, making the prediction of micro milling process hard. Among challenges in micro milling, tool life and tool wear can be highlighted. Understanding tool wear and modelling in micro milling is challenging and essential to maintaining the quality and geometric tolerances of workpieces. This work investigates how to model the diameter reduction of a tool caused by tool wear for micro milling of H13 tool steel. Machining experiments were carried out in order to obtain cutting parameters affecting tool wear by considering the diameter reduction. Dry full slot milling with TiAlN (titanium aluminium nitride)-coated micro tools of diameter d = 400 μm was performed. Three levels of feed per tooth ( f z = 2 μm, 4 μm and 5 μm) and two spindle speed levels ( n = 30,000 rpm and 46,000 rpm) were used and evaluated over a cutting length of l c = 1182 mm. The results show that lower levels of feed per tooth and spindle speed lead to higher tool wear with a total diameter reduction over 22%. The magnitude of the cutting parameters affecting tool wear was determined by ANOVA (analysis of variance), and the model validation meets the statistical requirements with a coefficient of determination R 2 = 83.5% showing the feasibility of the approach to predict tool wear using diameter reduction modelling in micro milling.