Tool wear predictability estimation in milling based on multi-sensorial data

Author:

Stavropoulos P.,Papacharalampopoulos A.,Vasiliadis E.,Chryssolouris G.

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Reference56 articles.

1. Chryssolouris G (2006) Manufacturing systems—theory and practice, 2nd edn. Springer, New York

2. Ji C, Liu Z, Ai X (2014) Effect of cutter geometric configuration on aerodynamic noise generation in face milling cutters. Appl Acoust 75:43–51

3. Larreina J., Gontarz A., Giannoulis C., Nguyen V.K., Stavropoulos P., Sinceri B. (2013) Smart Manufacturing Execution System (SMES): The possibilities of evaluating the sustainability of a production process, (GCSM) 11th Global Conference on Sustainable Manufacturing, 23-25 September, Berlin, Germany, pp.517–522

4. Wright P.K., Trent E.M. (1974) Metallurgical appraisal of wear mechanisms and processes on high-speed-steel cutting tools, Metals Technology, January 13–23

5. Tarasov SY, Rubtsov VE, Kolubaeva EA (2014) A proposed diffusion-controlled wear mechanism of alloy steel friction stir welding (FSW) tools used on an aluminum alloy. Wear 318(1–2):130–134

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