This study investigated the role of multi-layer lever type flexure hinges for high magnification of piezoelectric actuators and their optimal design. In order to obtain a displacement higher than 700 μm with a common PZT actuator of displacement less than 15 μm, the magnification ratio of a flexure hinge must be at least 50 or higher. Under a limited compact space, a multi-layer lever structure represents a useful alternative. Restricting the important design parameters to the number of layers and rotational stiffness of notch, the maximum required input displacement/force and the maximum output displacement were analyzed according to the number of layers. The two-layer structure was selected as the best option for large magnification ratio because the required input displacement was drastically reduced. FEM analysis revealed that the lever thickness should be larger than 12 mm to exhibit a rigid body behavior. The output displacement was 664 μm, which was less than 704 μm expected in the design stage. It might be attributed to elastic deformation of the notches of 1st and 2nd layers, which was not considered in the design stage.

The goal of this study is to develop a fast, controllable PZT-driven depth adjustment device with a flexure hinge. The device can be used to trace rapidly a flat or curved surface with several hundreds of micrometers’ variance in height. The lever type flexure hinge designed for a magnification ratio of 10 and no other axes motion has been confirmed through FEM analysis; the actual performance has been verified through static/dynamic experiments. A micro-depth control system, which is comprised of a DAQ with a LabVIEW, PZT amplifier, PZT actuator, flexure hinge, and laser displacement sensor, is implemented, and its static/dynamic characteristics of depth control is investigated with a PID gain tuned control algorithm on LabVIEW. It has been verified that the developed device can trace a micro-depth command as fast as 0.5 s to get an accurate position of 0.1 μm, even under a load of 1 N.

The aim of this paper is the development of a PZT-driven apparatus for testing the force-deflection behavior of thin 0.1/0.5-㎜-thick plates. Thin plates are widely used as the diaphragm of pressure sensors, as they are much stronger than the thin films with thicknesses of up to several tens of ? that are used in MEMS applications. Therefore, a proper PZT actuator should be selected to acquire the static- and dynamic-material properties of these thin plates to perform testing in terms of the force and frequency responses. Based on the investigation of the PZT characteristics, a test apparatus is developed. It is verified for the Hastelloy C-276 that the static-force deflection, acquired through sample testing, is compatible with the theoretical one; moreover, the dynamic test is available up to approximately 20 ㎐.

A worm screw is widely used in a geared motor unit for motion conversion from rotation to linear. For mass production of a high quality worm, the current rolling process is substituted with the milling process. Since the milling process enables the integration of all operations of worm manufacturing on a CNC(Computer Numerical Control) lathe, productivity can be remarkably improved. In this study, the tooling system for side milling on a CNC lathe to improve machinability is developed. However, the cutting tool-workpiece interference is important factors to be considered for producing high quality worms. For adaptability of various worms machining, the tool-workpiece interference simulation system based on a tool-tip trajectory model is developed. The developed simulation system is verified through several kinds of worms and experimental results.

A worm screw is widely used in a geared motor unit for motion conversion from rotation to linear. For mass production of a high quality worm, the current rolling process is substituted with the milling process. Since the milling process enables the integration of all operations of worm manufacturing on a CNC(Computer Numerical Control) lathe, productivity can be remarkably improved. In this study, the tooling system for planetary milling on a CNC lathe to improve machinability is developed. However, the cutting tool-workpiece interference is important factors to be considered for producing high quality worms. For adaptability of various worms machining, the tool-workpiece interference simulation system based on a tool-tip trajectory model is developed. The developed simulation system is verified through several kinds of worms and experimental results.

The accuracy of the machine tools is degraded because of thermal error of structure due to thermal variation. To improve the accuracy of a machine tools, measurement and prediction of thermal error is very important. The main part of thermal source is spindle due to high speed with friction. The thermal error of spindle is very important because it is over 70% in total thermals errors. In this paper, the suitable thermal error prediction technology for machine tools with open architecture controller is developed and implemented to machine tools. Two thermal error prediction technologies, neural network and multi-linear regression, are investigated in several methods. The multi-linear regression method is more effective for implementation to CNC. The developed thermal error prediction technology is implemented on the internal function of CNC.

According to global trend of the expanding need of high-quality automobiles, the usage of small precise worm consisting of gearing part for motors to actuate convenience modules has increased rapidly. Precision of those worms has very sensitive characteristic to motor performance and noise. Forming process has been generally used to manufacture worms because of its mass productivity. However, it has problems such as deformation due to residual stress and wear of dies. Planetary milling and side milling are among alternatives using cutting tools. To overcome those problems the two machining methods have some contrast features in the sense of tool numbers and cutting mechanism. In this paper, machinability of both methods was compared in terms of cutting force, precision and cycle time.

Ultraprecision machining and MEMS technology have been taken more and more important position in machining of microparts. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro parts to micro products. Also, the method of micro-grooving using micro endmill is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This investigation deals with state monitoring using acoustic emission(AE) signal in the micro-grooving. Characteristic evaluation of AE raw signal, AE hit and frequency analysis for condition monitoring is presented. Also, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by the fuzzy C-means algorithm.

A monitoring system is necessary to make the polishing process more reliable in order to ensure the high quality and performance of the final products. Generally, AE (Acoustic Emission) is known to be closely related to the material removal rate (MRR). As the surface becomes rougher, the MRR and AE increase. Therefore, the surface roughness can be indirectly estimated using the AE signal measured during the polishing. In this study, an AE sensor-based monitoring system was fabricated to detect the very small AE signal resulting from the friction between a tool and a workpiece during polishing. The performance of this monitoring system was estimated according to polishing conditions, the relation between the level of the AE RMS and the surface roughness during the polishing was investigated.

Shoe with leather upper such as safety and golf shoe requires a roughing process where the upper is roughed for helping outsole to be cemented well. It is an important and basic process for production of leather shoe but is not automated yet. Thus, there are problems that the defect rate is high and the quality of roughed surface is not uniform. In order to solve such problems, the interest in automation of roughing process is being increased and this paper introduces CAM system for 5-axis automatic roughing machine as one part of automation of roughing process.
The CAM system developed interpolates a B-spline curve using points measured from the Roughing Path Measurement System. The B-spline curve is used to generate the tool path and orientation data for a roughing tool which has not only stiffness but also flexibility to rough the inclined surface efficiently. For productivity, the upper of shoe is machined by side of the roughing tool and tool offset is applied to the roughing tool for machining of inclined surface.
The generated NC code was applied to 5-axis polishing machine for the test. The upper of shoe was roughed well along the roughing path data from CAM and the roughed surface was proper for cementing of the outsole.

In case of fine machining processes, the cutting state monitoring by a skilled operator is impossible because the physical changes generated during fine machining are very weak. To realize the high efficient and precise fine machining, it is necessary to develop the sensor based monitoring system which is able to detect the fine changes of cutting state. In this paper, the fine acoustic emission monitoring system is developed to monitor the state of the fine machining process. The developed system consists of the AE sensor and the AE signal processing unit. And this has the high-sensitivity and bandwidth which can detect fine AE signal generated during fine machining process. In order to investigate the feasibility of the developed system, evaluation experiments were performed in the fine fixed-abrasive machining processes such as polishing and glass ferrule slicing. Experimental results show that the developed monitoring system possesses an excellent real-time monitoring capability at fine machining processes.

Gearing system emits inconsistent noise from gear teeth impact in case of gear defects. But, it is not easy for inspection operator in production line to distinguish objectively the defective product. Therefore, customer complains continuously bad noise of the geared motor. Because impulsive signal at low frequency has a tendency not to appear in frequency domain, it is difficult to separate the gear inconsistent noise of defective gear from overall geared motor's noise using general signal processing method such as FFT. In this paper, the method to estimate more objectively the inconsistent noise of gearing system and to measure the quantities is suggested. Suggested method uses Cepstrum, Autocorrelation, Comb Lifter and Inverse Cepstrum by turns to make objective quantities about noise level.

From the Beckmann's reflection model of wave incident, reflected light from a surface is known to have not only specular but also diffuse components. The specular component dominant a surface for a mirror-like surface is distributed on the almost the same area as the spot on the surface, but the diffuse component region dominant for a rough surface spreads scattered on the larger areas than the spot. Therefore, statistic parameters from the scattered light distribution are more meaningful in the diffuse region, while the magnitude of rather meaning in the specular region. In usual, there need two sensors to acquire two kinds of information: Photo-detector for light intensity magnitude and image sensor for light intensity distribution. But dual sensor scheme requires a beam splitter usually to feed light to each sensor, and moreover there is not a combination rule to relieve the different sensor characteristics. In this study a new method is proposed for acquisition of the dual information using only an image sensor. Specular region is established on an image area being distinguished from a diffuse component, and laser power is adjusted so that no pixel of the image sensor in the specular region is saturated. Simulation based on the light reflection theory and the experimental results are quite well matched, and thus the proposed method was proved to be very useful for mirror-like surface measurement.

The light pattern reflected from a machined surface contains some information like roughness and profile on the projected surface as expected in the Beckmann-Spizzichino model. In applying the theory into a real reliable measuring device, many parameters such as incident light power, wave length, spot size shoud be kept a constant optical value. However, the reflected light power is likely to change with the environmental noise, the variations of the light source, the reflectivity of the surface, etc. even though the incident light power is constant. In this study, a method for adjusting the incident light power to keep the reflected light power projected on a CMOS image sensor constant was proposed and a simple adjustment algorithm based on PI digital control was examined. Experiments verified that the proposed method made the surface roughness measurement better and more reliable even under variations of the height of light source.