Among the monitoring technologies in the metal-cutting process, tool wear is the most critical monitoring factor in real machining sites. Extensive studies have been conducted to monitor equipment breakdown in real-time. For example, tool wear prediction studies using cutting force signals and deducting force coefficient values from the cutting process. However, due to many limitations, those wearable monitoring technologies have not been directly adopted in the field. This paper proposes a novel tool wear predictor using the cutting force coefficient with various cutting tools, and its validity evaluates through cutting tests. Tool wear prediction from the cutting force coefficient should conduct in real-time for adoption in real machining sites. Therefore, a real-time calculation algorithm of the cutting force coefficient and a tool wear estimation method proposes, and they compare with actual tool wear in cutting experiments for validation. Validation cutting tests are conducted with carbon steel and titanium, the most commonly used materials in real cutting sites. In future work, validation will be conducted with different materials and cutting tools, considering the application in real machining sites.

Recently, applying nanoscale functional materials, there have been great advances in the flexible sensor system, which provides a large number of applications for soft electronics, such as skin-attachable sensors, artificial electronic skins, and soft robotic systems. Here, we developed a highly sensitive and flexible device on the basis of polymeric piezoelectric nanofibers and elastomeric packing structures. To produce the nanofibers, we applied the electrospinning process with a representative piezoelectric co-polymer, poly (vinylidenefluoride-co-trifluoroethylene) (PVDF-TrFE). Unlike the conventional electrospinning, we applied an anisotropic fiber collection system, which could obtain uniaxially aligned nanofiber array. The aligned nanofibers were sandwich-packed with bridge-shaped PDMS substrates, thereby integrating the flexible piezoelectric sensor. As an external force made a deflection of the bridge in the sensor, the embedded nanofibers generated piezoelectricity in a longitudinal direction of the fibers. The piezoelectric sensor generated good discernable outputs versus the varied mechanical input deflection from tens of micrometers to the sub-micrometer. With this great sensing ability, we could monitor heart pulse signals on the wrist skin by measuring tiny deflections generated from the expansion of the radial artery underneath the skin. Our study suggests a potential application of flexible sensor in the field of wearable health-monitoring medical systems.

Since becoming highly functional, complex and flexible, the machining system of CFRP(Carbon Fiber Reinforced Plastic) has recently become highly functional, complex and flexible, its has its controllers are changing into open and distributed structures. These, and need controlling to be controlled to maintain good quality of for a quality of machined parts. In particularSpecifically, an open controller is required urgently needed to apply the optimal processing program for each material and development of embedded SW, which enables after-production of CFRP, CFRP-metal stack material, waterjet processing, inspection, and modification. As theThe characteristics of CFRP materials may create processing defects such as stratified material stripping and un-cut., a A process monitoring module that can minimize or prevent the defects this technology needs to should be applied to hence reducinge tool wear causedthrough by high hardness carbon fiber. Since CFRP is mostly made from additive forming, there are many drilling processes, that require precision measurement techniques and process signal monitoring technology, exist. Tsince the cutting force load and various signals generated during processing are weaker than those during metal processing. An open controller for process control and monitoring of a CFRP processing system was therefore developed. The system will then It is going to develop open controller SW structural design and open platform, multi-channel signal processing algorithm and sensor system, process specific functions (CFRP process control, boundary detection, etc.) and mount drilling tool parent monitoring algorithm on open platform.