SENSORS AS AN ENABLER FOR SELF-OPTIMIZING GRINDING MACHINES

Abstract

Today, an operator performs experiments to adaptively select grinding process parameters using observations, expert knowledge, and rules of thumb. Self-optimizing grinding machines cannot use operator observations and must, therefore, extract enough information out of the grinding process. In this study, a holistic sensor set-up as foundation for self-optimizing machines are presented exemplarily for cup wheel grinding machines. In-process detection of grinding burn, based on temperature and gas measurements, is tested and compared. Afterwards, the influence of input variables such as feed rate and cutting speed on grinding cost, grinding burn, and surface roughness are investigated.

Recommended articles

PRODUCTIVITY INCREASE OF HIGH PRECISION MICRO-MILLING BY TRAJECTORY OPTIMIZATION

A. Schorderet, R. Herzog, N. Jacquod, Y. Marchand, Ch. Prongue
Keywords: Milling; Vibrations; Trajectory optimization; Surface quality; CNC

RESOURCE CONSUMPTION CLASSES OF MACHINE TOOLS

M. Putz, H. J. Koriath, A. P. Kuznetsov
Keywords: Machine tool; Energy; Resource; Efficiency; Costs

DESIGN OF A MICRO TOOL FOR HIGH-EFFICIENCY MICRO SLOTTING

L. Zhong, D. Peng, Q. Yin
Keywords: Tool design; Micro slotting tool; Novel structure; Micro arrayed slots; High efficiency

METHODOLOGY FOR A MODEL-BASED CONTROL OF THE BOUNDARY ZONE PROPERTIES DURING MILLING OF TI-6AL-4V

M. Wimmer, P. Rinck, R. Kleinwort, M. F. Zäh
Keywords: Milling; Boundary zone properties; Internal stress states; Titanium; sensor tool holder; In-process measurement