Tool wear monitoring in roughing and finishing processes based on machine internal data

Abstract Data analytics plays a significant role in the realization of Industry 4.0. By generating context-related persistent datasets, every manufacturing process real production becomes an experiment. The vision Internet Production (IoP) is to enable real-time diagnosis and prediction smart productions by acquiring datasets seamlessly from different data silos. This requires interdisciplinary collaboration domain-specific expertise. In this paper, we present novel tool wear monitoring system for milling developed context IoP. based on high-frequency numerical control machine without additional sensors. novelty paper lies introduction virtual workpiece quality fusion multiple build-in sensor signals force model as decision support. bridges time gap between inspection at shop floor level, establishes automated statistical system, provides more plausible lifetime. two processes environment exemplary demonstrated paper. first case face roughing with aim rapidly removing large amounts material. second finishing operation that follows aims achieve desired surface quality.