• 한국기계가공학회지
• /
• 제20권9호
• /
• pp.90-96
• /
• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.

• 한국재료학회지
• /
• 제20권11호
• /
• pp.559-569
• /
• 2010

The liquid-phase sintering method was used to prepare a glass lens forming core composed of SiC-$Al_2O_3-Y_2O_3$. Spark plasma sintering was used to obtain dense sintered bodies. The sintering characteristics of different SiC sources and compositions of additives were studied. Results revealed that, owing to its initial larger surface area, $\alpha$-SiC offers sinterability that is superior to that of $\beta$-SiC. A maximum density of $3.32\;g/cm^3$ (theoretical density [TD] of 99.7%) was obtained in $\alpha$-SiC-10 wt% ($6Al_2O_3-4Y_2O_3$) sintered at $1850^{\circ}C$ without high-energy ball milling. The maximum hardness and compression stress of the sintered body reached 2870 Hv and 1110 MPa, respectively. The optimum ultra-precision machining parameters were a grinding speed of 1243 m/min, work spindle rotation rate of 100 rpm, feed rate of 0.5 mm/min, and depth of cut of $0.2\;{\mu}m$. The surface roughnesses of the thus prepared final products were Ra = 4.3 nm and Rt = 55.3 nm for the aspheric lens forming core and Ra = 4.4 nm and Rt = 41.9 for the spherical lens forming core. These values were found to be sufficiently low, and the cores showed good compatibility between SiC and the diamond-like carbon (DLC) coating material. Thus, these glass lens forming cores have great potential for application in the lens industry.