Toru Kizaki 교수

Yttria-stabilized tetragonal zirconia polycrystal is a promising material for dental restoratives. The dominant manufacturing method of the dental restoratives comprises three steps. (1) Pressing (2) machining (3) final sintering. The method has disadvantages such as low geometrical accuracy and long process time in the final sintering stage. Thus, the direct machining method of the fully sintered Y-TZP which is difficult to machine is desired to realize an accurate, efficient and inexpensive fa

A novel temperature measuring system named LATSIS was proposed to realize a robust and accurate prediction of the thermal deformation of machining centers, even under external disturbances such as cutting fluid supply. LATSIS enables a drastic increase in the number of sensors employed for measuring the temperature of the machine tool. Thus, the entire temperature distribution can be obtained by interpolating the measured temperature 3-dimensionally without calculating the heat conduction. A set

To compensate for thermal errors in machine tools, strategic sensor placement and rapid error calculation are crucial. This study addresses these challenges using model order reduction. A transfer function matrix and a sensitivity function were defined to optimize the number and locations of sensors without physically attaching them to the machine tool. This methodology was validated through experiments on a 3-axis machining center. The number of sensors was reduced by 50 %, and the calculations

Temperature measurement of machine tools is very important for high precision machining as 70% of the machining error is due to thermal displacement. However, the temperature of the feed drive system has not been measured directly so far. In this study, we developed a wireless multi-point series temperature sensor system. The temperature distribution of the ball screw feed drive system was directly measured on a three-axis horizontal machining center. The results showed that the heat generated b

Yttria-stabilized tetragonal zirconia polycrystal is promising ceramic for artificial implants despite its difficult-to-cut feature. Thus, a machining method that enhances the process performance is required. We proposed UV laser-assisted machining of Y-TZP. In the process, the laser beam is utilized to ablate the material as well as to heat it. First, the optimal wavelength of the laser was determined by considering the fluence threshold for the ablation. In order to obtain the fluence threshol

Yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) is a promising material for dental restoratives. Although grinding or polishing with diamond tools is widely used to machine Y-TZP, the processing efficiency and cost of the process are problematic. In this study, we applied laser-assisted machining (LAM) to Y-TZP, in which non-diamond tools were used. Unlike LAM applied to other materials, decrease of the fracture toughness at elevated temperatures which is a unique feature of the Y-TZP

• A novel clogging detection method combining resonance frequency and mode shape vectors. • Mode shape vectors help overcome modal symmetry challenges in clogging detection. • A random forest algorithm enables automatic recognition of clogging location and level. • Polynomial fitting enhances mode shape resolution for better clogging detection. • The proposed method is scalable for larger and more complex pipeline systems. Clogging or leakage in material transportation pipeline systems can cause