In this study, polyacetal plates were machined with an indexable drill (Ø18mm) to measure the dimensional error of holes according to the cutting conditions and investigate the influencing factors to obtain precision holes. Cutting velocity, feed, and depth of cut were selected as experimental variables, analyzed using design of experiment, and optimal cutting conditions were investigated. Cutting velocity and feed were significant factors affecting hole accuracy, whereas depth of cut had little effect. The factor with the greatest influence on hole accuracy was cutting velocity, and the dimensional error of the holes tended to increase as the cutting velocity increased. Dimensional error tended to decrease as feed increased. In addition, the interaction effect between cutting velocity and feed and cutting velocity and depth of cut were significant. In this experiment, the optimal cutting velocity, feed, and depth of cut needed to minimize the dimensional error of holes were 100 m/min, 0.15 mm/rev, and 2 mm, respectively.

Bone plates made of biodegradable polymers have been used to fix broken bones. 3D printers are used to produce the bone plates for fracture fixing in the industry. The dimensional accuracy of the product printed by a 3D printer is less than 80%. Fracture fixing plates with less than 80% dimensional accuracy cause problems during surgery. There is an urgent need to improve the dimensional accuracy of the product in the industry. In this paper, a methodology using machine learning was proposed to improve the dimensional accuracy. The proposed methodology was evaluated through case studies. The results predicted by the machine learning methodology proposed in this paper and the experimental results were compared through the experiment. After verification, results of the proposed prediction model and the experimental results were in good agreement with each other.

Recently, as various damages are expected due to the risk of falling space debris, many studies are being carried out to acquire space object information. In this research, an optical-based space object surveillance system was developed to acquire information about space objects. To acquire orbit information by photographing a space object with this system, the accuracy of position data of the space object is important. The telescope coordinate is located in the 2D CCD plane of the telescope, and the space objects are in the celestial coordinate. The two coordinates have a non-linear relation caused by a deflection of the mechanical system, a scattering of the atmosphere and so on. In this study, we propose an alignment method for two coordinate systems. First, a model that analyzes the geometric relation between the telescope system on earth and space objects is explained. Then, we also propose a second model with the addition of correction parameters. As a result of performing coordinate alignment according to the method and procedure proposed in this study, the pointing accuracy is lowered below 3 arcsec.

A new technique based on the reversal method, is suggested to measure squareness error of the two-linear axes system. The technique uses the L-type steel bar, a capacitive sensor, and three experimental installations required to measure squareness error and two horizontal straightness errors. Profile and squareness of the L-type steel bar are estimated, by using the principle of the reversal method. Also, setup errors inevitable at installation, are separated from measured data using the least square method. Multi-DOF errors of two-linear axes system are measured and analyzed, using the suggested technique. Also, the reference mirror with flatness of 30 nm is used to verify the suggested measurement technique. Difference between the two measurement methods is 3.25 arcsec, a value within measurement repeatability.

UVW Stage is widely used in manufacturing processes of PCB, LCD, OLED, and semiconductor industries. The precision of UVW Stage is closely associated with the quality of products. Two approaches for kinematics of UVW Stage are proposed for comparative analysis. Program of proposed kinematics algorithm is developed for motion control and applied to UVW Stage driving. The position of the stage for each algorithm is sequentially measured by laser interferometer. Both virtual stage and real stage are used for accuracy analysis. The performance of each algorithm is evaluated based on this accuracy analysis.