Study of face milling of hardened AISI D3 steel with a special design of carbide tools

• Published in: International journal of advanced manufacturing technology Vol. 40; no. 1-2; pp. 12 - 25
• Main Authors: Siller, H. R., Vila, C., Rodríguez, C. A., Abellán, J. V.
• Format: Journal Article
• Language: English
• Published: London Springer-Verlag 2009; Springer Nature B.V
• Subjects: CAE) and Design; Carbide tools; Cold work tool steels; Computer-Aided Engineering (CAD; Cutting parameters; Cutting wear; Engineering; Face milling; Histograms; Industrial and Production Engineering; Mechanical Engineering; Media Management; Milling (machining); Morphology; Original Article; Process parameters; Production planning; Surface properties; Surface roughness; Tool life; Tool wear; Tungsten carbide; Viability; Workpieces; Face milling; Tungsten carbide tools; Hardened steel
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-007-1309-0

This paper studies the impact of a special carbide tool design on the process viability of the face milling of hardened AISI D3 steel (with a hardness of 60 HRC), in terms of surface quality and tool life. Due to the advances in the manufacturing of PVD AlCrN tungsten carbide coated tools, it is possible to use them in the manufacturing of mould and die components. Experimental results show that surface roughness (R a ) values from 0.1 to 0.3 μm can be obtained in the workpiece with an acceptable level of tool life. These outcomes suggest that these tools are suitable for the finishing of hardened steel parts and can compete with other finishing processes. The tool performance is explained after a tool wear characterization, in which two wear zones were distinguished: the region along the cutting edge where the cutting angle (κ) is maximum (κ max ) for a given depth of cut, and the zone where the cutting angle is minimum (κ = 0) that generates the desired surface. An additional machining test run was made to plot the topography of the surface and to measure dimensional variations. Finally, for the parameters optimal selection, frequency histograms of R a distribution were obtained establishing the relationship between key milling process parameters (V c and f z ), surface roughness and tool wear morphology.