EVALUATION OF SENSOR-BASED CONDITION MONITORING METHODS AS IN-PROCESS TOOL WEAR AND BREAKAGE INDICES - CASE STUDY: DRILLING

John A. TSANAKAS, Pantelis N. BOTSARIS, Iraklis G. AMIRIDS, Georgios G. GALERIDIS Democritus University of Thrace, School of Engineering Department of Production Engineering and Management Faculty of Materials, Processes and Engineering Xanthi, 67100, Thrace, Greece Telephone (and Telefax): +302541079878 itsanaka@ee.duth.gr , panmpots@pme.duth.gr , irakamoi@pme.duth.gr , ggalerid@xan.duth.gr Summary Today, effective unmanned machining operations and automated manufacturing are unthinkable without tool condition monitoring (TCM). Undoubtedly, the implementation of an adaptable, reliable TCM and its successful employment in industry, emerge as major instigations over the recent years. In this work, a sensor-based approach was deployed for the in-process monitoring and detection of tool wear and breakage in drilling. In particular, four widely reported indirect methods for tool wear monitoring, i.e. vibration signals together with thermal signatures, spindle motor and feed motor current measurements were obtained during numerous drillings, under fixed conditions. The acquired raw data was, then, processed both statistically and in the frequency domain, in order to distinguish the meaningful information. The study of the latter is influential in identifying the trend of specific signals toward tool wear mechanism. The efficiency of this information as a tool wear and/or breakage index is the feature that determines the effectiveness and reliability of a potential indirect TCM approach based on a multisensor integration. The paper concludes with a discussion of both advantages and limitations of this effort, stressing the necessity to develop simple, fast condition monitoring methods which are, generally, less likely to fail. Key words: tool condition monitoring, vibration signals, thermal signatures, spindle motor current, tool wear, statistical analysis, frequency domain analysis.