In this study, a method for evaluating the mechanical properties, specifically the initial stiffness and martensitic transformation onset stress, of NiTi lattice structures, Body Centered Cubic (BCC) and Rhombic Dodecahedral (RD) structures, under compressive loading was proposed. In particular, a theoretical evaluation method that takes into account the effective length of the strands constituting the lattice was developed. For both BCC and RD lattice structures, the theoretical solutions for the initial stiffness and transformation stress show good agreement with the finite element (FE) analysis results. In particular, the evaluation proposed in this study is up to three times more accurate than those proposed by other researchers. The variation in transformation stress depends on the difference between the transformation start and finish stresses inherent to the material, as well as the relative density. In addition, for RD structures, accurate prediction can be ensured when the ratio of strand diameter d to the width of the unit-cell L satisfies d/L ≤ 0.2.

The influence of engine operating conditions and fuel properties on the graphite crystallite size of soot particles from a small DI diesel engine were experimentally investigated. To examine the effect of aroma content in fuel on the graphite crystallite, both the conventional diesel fuel and the paraffinic hydrocarbon fuel (CN55) with similar ignitability to the diesel fuel but without aroma content were used. The soot particles were extracted from the exhaust gas, and its graphite crystallite size and oxidation reactivity were analyzed by laser Raman spectroscopy, high-resolution transmission electron microscopy (HRTEM) and thermalgravimetric analyzer (TGA). The results showed that there is no significant difference in the shape of rate of heat release and the indicated thermal efficiency with both fuels. However, the graphite crystallite size with the CN55 was smaller than with the diesel fuel under several engine operating conditions, resulting in the higher oxidation reactivity with the CN55. Regardless of the type of fuel and engine operating conditions, a strong positive correlation was observed between graphite crystallite size and high temperature residence time calculated from combustion duration defined as from 10% heat release crank angle timing to 90% heat release crank angle timing and engine speed. These results suggest that the residence time in combustion significantly influences the graphitization of soot particles.

NV (Noise and vibration) performance of a mechanical system is determined by the contributions of all subsystems that make up the mechanical system. However, complex mechanical systems such as automobiles are concurrently developed, in which the supplier subsystem is mounted onto the OEM (Original Equipment Manufacturer) subsystem, it is not easy to share intellectual property such as shape information between companies. As a result, NV problems often occur in the final stages of product development. This leads to extensive redevelopment, resulting in longer development times and higher development costs. Therefore, it is necessary to be able to design the NV performance of a whole structure from the supplier's viewpoint at the upstream product development stage. In this paper, we proposed a method to solve the inverse problem of allocating the single resonant frequency of a whole structure, which occurs due to a large contribution from the supplier subsystem, by modifying the structure of the supplier subsystem. This method is composed of kCA (kernel Compliance Analysis) and CEAM (Constrained Eigenstructure Assignment Method), and is realized by using the compliance-FRF matrix of the OEM subsystem provided by the OEM in the upstream design stage. Finally, numerical verification of the proposed method was demonstrated.

To meet the demand of mass customization and address labor shortages in industry, the implementation of flexible production line with industrial robots is essential. Reconfiguring production lines requires robot motion planning, but discrepancies between the simulated environment and operational environment—such as position or shape errors—often leads to rework. This study aims to prevent rework in robot motion planning during production line reconfiguration, especially focusing on the deformable cable fixed across a robot joint. The proposed approach integrates the robot's operational environment, including the deformable cable, into the simulated environment using 3D measurements. The deformable cable is extracted through point cloud registration, and its deformation is predicted by introducing angular and radial deformations in polar coordinates around the robot joint axis. When registering point clouds with discrepancies between the operational environment and simulated environment, the iterative closest point (ICP) method with threshold is effective. However, determining the appropriate threshold value usually involves trial and error. To address this issue, this study proposed threshold determination methods that account for discrepancies in part shape, part existence and measurement errors. To predict cable deformation extracted through ICP with the determined threshold, a method based on the deformation curve of a fixed-ended beam is introduced. This eliminates the need for manual parameter adjustment in physical simulations through trial and error. Validation in a real-world robot environment showed that proposed ICP threshold achieved the lowest registration error, ranging from 1 to 100mm. Furthermore, cable deformation prediction yielded a maximum error of 2.9 mm within joint angles of 0 to 90 degrees. An application test demonstrated a 92% reduction in rework during robot motion planning. This study contributes to the development of flexible production lines with industrial robots by providing accurate deformation predictions without relying on physical simulations.

The manufacturing industry has been required to suppress CO₂ emissions with the collaboration of the whole supply chain including parts manufacturing. Additive Manufacturing is a novel method that allows flexible production with a minimal amount of material, and the cooperative manufacturing of conventional manufacturing methods and Additive Manufacturing has a potential to suppress CO₂ emission in the manufacturing supply chain. In this study, we propose a method to analyze the trade-off between CO₂ emissions and parts manufacturing costs in a cooperative manufacturing system between additive manufacturing and conventional manufacturing, using multi-objective optimization method, use cases of parts manufacturing are investigated. A set of conditions that minimize CO₂ emissions under a given cost condition is derived as a Pareto set. Sensitivity analysis is conducted to evaluate the impact of factors such as the amounts of materials consumed during parts manufacturing and energy consumption during manufacturing on the reduction of CO₂ emissions. Case study is conducted and we derived the optimal condition set. Furthermore, we analyze factors that are sensitive to reduction of CO₂ emissions.

Flow-dependent dilatation test using Endo-PAT is conventionally used to evaluate vascular endothelial function; however, this method is costly. Therefore, in the previous paper, the author presented an alternative method to Endo-PAT using vascular visualization technology. However, this device was impractical owing its large size. Therefore, we thought it possible to use a pulse oximeter probe similar in mechanism to the device shown in the previous paper. The purpose of this study was to determine whether vasodilatation following cuff pressure release in the upper arm can be detected using a pulse oximeter probe. We also determined the correlation between vasodilation measurement values and the reactive hyperemia index (RHI). Using a sample of 49 healthy subjects, we measured the amount of light transmitted through the fingertip using a pulse oximeter probe and recorded digital pulse volume by RH-PAT (Reactive hyperemia peripheral artery tonometry). The amount of light transmitted through the index finger tip was obtained by separately measuring the output voltage of a photodiode receiving light emitted from a red light-emitting diode (LED, wavelength: 660 nm) or an infrared LED (940 nm) incorporated within the pulse oximeter probe. During this process, the upper arm was compressed for 5 min with a cuff at 200 mmHg so that output voltages before and after cuff compression release could be obtained. We observed decreased output voltages for both lights following cuff pressure release, presumably caused by vasodilation. From the temporal variation in output voltage, R2 was defined as the ratio of the increase in output voltage after cuff compression to the decrease in output voltage following cuff compression release. We found significant positive correlations between RHI and R2 for both red and infrared light (ρ = 0.53 and 0.55). Next, when comparing RHI quartiles, the R2 value of the lowest RHI quartile was significantly smaller than those of higher RHI quartiles (p < 0.05). These results show that the pulse oximeter probe was able to detect vasodilation following cuff pressure release, and that this was significantly correlated with RHI values recorded via RH-PAT.