Lithography techniques are generally used to manufacture nano-patterns on silicon, however, it is difficult to make a V-shaped pattern using these techniques. Although silicon is a brittle material, it can be treated as a ductile material if mechanically machined at extremely low force scale. The manufacturing technique of nano-patterns on single crystal silicon using a mechanical method was developed in this study. First, the linear pattern was machined on the silicon with increasing thrust force. Then, the correlation between measured cutting force and machined pattern was analyzed. Based on the analysis, the critical thrust force was quantitatively determined, and then the silicon was machined at a force lower than the critical thrust force. The machined pattern was observed using SEM and AFM to check for the occurrence of brittle fractures. Finally, the sharp V-shaped nano-pattern was manufactured on the single crystal silicon.

In smart factories, the entire manufacturing process from design to the final product is simulated in a virtual manufacturing environment and optimized before starting production. Suppliers and customers make decisions based on the simulation results. Therefore, effective rendering of the information of the virtual products to suppliers and customers is essential for this manufacturing paradigm. In this study, a method of rendering the surface roughness of the virtual products using a tactile display is presented. A tactile display device comprising a $3{\times}3$ array of individually controlled piezoelectric stack actuators is constructed. The surface topology of the virtual products is rendered directly by controlling the piezoelectric stack actuators. A series of experiments is performed to evaluate the performance of the tactile display device. An electrical discharge machined surface is rendered using the proposed method.

In this paper, a real-time condition diagnosis system for the lens injection molding process is developed through the use of LabVIEW. The built-in-sensor (BIS) mold, which has pressure and temperature sensors in their cavities, is used to capture real-time signals. The measured pressure and temperature signals are processed to obtain features such as maximum cavity pressure, holding pressure and maximum temperature by the feature extraction algorithm. Using those features, an injection molding condition diagnosis model is established based on a response surface methodology (RSM). In the real-time system using LabVIEW, the front panels of the data loading and setting, feature extraction and condition diagnosis are realized. The developed system is applied in a real industrial site, and a series of injection molding experiments are conducted. Experimental results show that the average real-time condition diagnosis rate is 96%, and applicability and validity of the developed real-time system are verified.

For reaction injection molding (RIM) polyurethane was mixed in the mixing head by impingement mixing, injected into the mold, and cured quickly, as soon as the mold is filled. The shape of the nozzle in the mixing head is critical to improve the quality of polyurethane. To achieve homogeneous mixing, an intensive turbulence energy in the mixing nozzle is essential. In this study, a mixing nozzle for RIM was designed, and mixing efficiency was investigated based on experiment. Experiments were conducted with different combinations of nozzle tips and exit diameter to measure the mixing efficiency by measuring jet force and investigating mixing image with high speed camera. Jet force increased gradually and reaches steady state conditions. The jet force depended on shape of nozzle tip and outlet sizes. These results suggest that optimized nozzle configurations are necessary for high efficiency mixing with RIM.

Friction of mechanical components affects the life and reliability of various machines. In order to improve the wear resistance of mechanical components, grease has been used as a lubricant. However, depending on the operating condition of the machine, the grease may be contaminated with water, which lowers the its lubricating ability. In this work, the effect of the water content on the lubricating ability of grease was investigated. Friction tests using grease were performed between a stainless steel ball and an acrylic plate. Water content in the grease was varied (0, 5, 10 wt.%). It was found that the contact angle varied due to the addition of water in the grease. The friction and wear of the specimens were assessed with respect to amount of water content. Wear of the specimens was relatively severe when water was added. A water content of 10 wt.% resulted in significant lubricant degradation.

The present study uses an electron beam (e-beam) to modify the wetting characteristics of thermoplastic polymer surfaces. A high energy e-beam irradiated various polymer surfaces (PET, PMMA, and PC), with variations in irradiation time and applied current. The water contact angles were measured on the e-beam irradiated surfaces in order to investigate the changes in the surface energy and the relevant wettability. Furthermore, XPS analyses were performed to investigate the chemical composition change in the e-beam irradiated surfaces; the results showed that the hydrophilic groups (C-O) increased after the electron beam irradiation. Also, water collection tests were performed for various polymer samples in order to investigate the effect of the surface energy on the ability of water collection, from which it can be seen that the irradiated surfaces revealed better water-collecting capability than pure polymer surfaces.

Angular misalignment has a significant effect on the characteristics of angular contact ball bearings (ACBBs). This paper presents an analysis of fatigue life for ACBBs subjected to angular misalignment. A simulation model is developed with de Mul's bearing model and the ISO basic reference rating life model. Simulation is performed to calculate the life of the ACBBs subjected to angular misalignment. The numerical results show that angular misalignment influences the load distribution significantly, thus reducing the bearing rating life. The fatigue life of ACBBs is decreased by angular misalignment regardless of axial preload, external radial load and rotational speed. The results show that angular misalignment should be maintained at less than 1mrad for ACBBs.

We present a method of fabricating poly (lactic-co-glycolic acid) (PLGA) porous microfibers using a pore template. PLGA microfibers were synthesized using a glass capillary tube in a poly-(dimethylsiloxane) (PDMS) microfluidic chip. Gelatin solution was used as a porous template to prepare pores in microfibers. Two phases of PLGA solutions in different solvents-DMSO (dimethyl sulfoxide) and DCM (dichloromethane)-were used to control the porosity and strength of the porous microfibers. The porosity of the PLGA microfibers differed depending on the ratio of flow rates in the two phases. The porous structure was formed in a spiral shape on the microfiber. The porous structure of the microfiber is expected to improve transfer of oxygen and nutrients, which is important for cell viability in tissue engineering.

Polydimethylsiloxane (PDMS) is used as a scaffold for cell culture. Because both the stress and strain acting on the substrate and the hemodynamic environment are important for studying mechano-transduction of cellular function, the traction force of the surface of a substrate has been measured using fluorescence images of particle distribution. In this study, deformation of the cross-sectional plane of a PDMS block was measured by correlating particle image distributions to validate the particle image strain measurement technique. Deformation was induced by a cone indentor and a shearing parallel plate. Measured deformations from particle image distributions were in agreement with the results of a computational structure analysis using the finite-element method. This study demonstrates that the particle image correlation method facilitates measurement of deformation of a polymer scaffold in the cross-sectional plane.

Intricate deflection requires many conventional actuators (motors, pistons etc.), which can be financially and spatially wasteful. Novel smart soft composite (SSC) actuators have been suggested, but fabrication complexity restricts their widespread use as general-purpose actuators. In this study, a hybrid manufacturing process comprising 3-D printing and casting was developed for automated fabrication of SSC actuators with $200{\mu}m$ precision, using a 3-D printer (3DISON, ROKIT), a simple polymer mixer, and a compressor controller. A method to improve precision is suggested, and the design compensates for deposition and backlash errors (maximum, $170{\mu}m$). A suitable flow rate and tool path are suggested for the polymer casting process. The equipment and process costs proposed here are lower than those of existing 3D printers for a multi-material deposition system and the technique has $200{\mu}m$ precision, which is suitable for fabrication of SSC actuators.