For many years there has been considerable research from both an academic and industrial perspective into the monitoring and control of CNC machining processes, and progress has been well documented. It is widely acknowledged within the CIRP community that collection of information into the performance of material cutting processes is a worthwhile research topic, and this is mirrored in the work of the Scientific Technical Committee-Cutting (STC-C) and other Scientific Technical Committees.This work has been continued by the consortium engaged in the REALISM project, an EU-FP7 funded project which is investigating the use of sensor fusion in a real time production environment, to monitor CNC tool wear through the use of three sensor technologies- Force, Acoustic Emission and Vibration. However, the real work of the project consortium will be in the analysis and interpretation of the data from the collated fusion of the deployed sensors- and the intelligent interrogation of this sensor information. The sensor deployment strategy of this project was outlined in a presentation, poster and paper presented at the 2014 CIRP ICME conference and this current paper provides an update on the ongoing work.An overview is provided in this paper of the challenges that have been overcome as part of the REALISM project, and a brief overview of the initial verification trials that were undertaken on the deployment of the sensors. Further results will also be presented that show promising initial sensor data, which shows conditions leading to Catastrophic Tool Failure (CTF)

This paper presents a methodology aimed at the identification of a catastrophic tool failure (CTF) in turning processes based on multiple sensor monitoring. Experimental turning tests were carried out under various cutting conditions (cutting speed, feed, depth of cut) using a multi-sensor monitoring system consisting of a triaxial force sensor to acquire the three components of the cutting force and an acoustic emission sensor. Signals analysis, interpretation and processing was performed on the multi-sensor signals acquired during the turning process and relevant statistical features were extracted and used to develop a methodology for the automatic CTF detection during turning

Robust tool condition monitoring system requires reliable, repeatable selection of representative segments of the sensor signals. In commercial TCM systems and most of laboratory ones useful signal segments are selected by the system user, which is difficult, inconvenient, prone to random changes of cutting conditions and human errors. The paper presents algorithms for fully automatic detection of actual cutting (elimination of air cutting), selection of relatively stable signal segments representative of the tool condition and elimination of the overabundance of signal data in case of long operations or tool lives

This paper presents a multiple sensor automatic data acquisition system deployed on a CNC turning center in a real- time production environment at Schivo Precision, Waterford, Ireland. The machine has been fitted with a variety of sensors measuring acoustic emission, cutting force & vibration installed at the turret of the machine, coupled with an automatic image acquisition system monitoring the wear on the tools in real time after each operation. The combination of sensors and data acquisition is novel in that it brings together all the currently popular sensoring techniques in the field of tool condition monitoring and tests the validity of these techniques in a live production environment. The sensor data acquisition and optical tool wear measurements are controlled by a computer automatically with no intervention from the machine tool operator in normal production on a variety of component geometries, materials and cutting inserts. All the acquired data is available on-line for the research partners in the various countries. Independent operator feedback on the performance of the process in terms of both product dimensional stability and machined surface stability is used for evaluation of the acquired data applicability for tool condition monitoring

In this paper, we describe the needs and specific requirements of the aerospace industry in the field of metal machining; specifically, the concept of an edge-computing-based production supervision system for the aerospace industry using a tool and cutting process condition monitoring system. The new concept was developed based on experience gained during the implementation of research projects in Poland’s Aviation Valley at aerospace plants such as Pratt & Whitney and Lockheed Martin. Commercial tool condition monitoring (TCM) and production monitoring systems do not effectively meet the requirements and specificity of the aerospace industry. The main objective of the system is real-time diagnostics and sharing of data, knowledge, and system configurations among technologists, line bosses, machine tool operators, and quality control. The concept presented in this paper is a special tool condition monitoring system comprising a three-stage (natural wear, accelerated wear, and catastrophic tool failure) set of diagnostic algorithms designed for short-run machining and aimed at protecting the workpiece from damage by a damaged or worn tool.

The paper presents results of investigations on the binderless nanostructured tungsten carbide (WC) cutting tools fabrication and performance. The scientific novelty includes the description of some regularities of the powder consolidation under electric current and the subsequent possibility to utilize them for practical use in the fabrication of cutting tools. The sintering process of WC nanopowder was performed with the electroconsolidation method, which is a modification of spark plasma sintering (SPS). Its advantages include low temperatures and short sintering time which allows retaining nanosize grains of ca. 70 nm, close to the original particle size of the starting powder. In respect to the application of the cutting tools, pure WC nanostructure resulted in a smaller cutting edge radius providing a higher quality of TiC/Fe machined surface. In the range of cutting speeds, v_c = 15–40 m/min the durability of the inserts was 75% of that achieved by cubic boron nitride ones, and more than two times better than that of WC-Co cutting tools. In additional tests of machining 13CrMo4 material at an elevated cutting speed of v_c = 100 m/min, binderless nWC inserts worked almost three times longer than WC-Co composites.