Rapid establishment of optimized production parameters is crucial in manufacturing technology. However, to achieve the desired processing results, complex production technologies such as laser metal deposition (LMD) require evaluating numerous evaluation points and processing parameters. Thus, recent studies have explored the integration of artificial intelligence, especially machine learning, into manufacturing technology for fine-tuning the processing parameters. Nonetheless, laser processing engineers encounter challenges in interpreting the processing parameters identified by machine learning, and the robustness of the parameters enabling stable production is unclarified. To address these issues, this study developed a method to visualize the robustness conditions of key processing parameters. Fundamentally, the approach aims to scalarize and transform multiple objective variables related to processing outcomes into a singular evaluation index via weighted scaling. Thereafter, this index is explored in a two-step process employing both local and global search methods. The local search focuses on regions where the evaluation index is stable and favorable, whereas the global search attends to the remaining parameters where this region reaches its maximum. The proposed method exhibits minimal sensitivity to the initial weight settings and regional thresholds, thereby rendering it relatively straightforward for practical application.

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Towards sustainable societies, there is a demand for multi-material structures that utilize aluminum, which has high electrical conductivity, is lightweight, and is easy to recycle. To produce multi-material structures, the challenge to overcome is to develop a low-cost and versatile aluminum dissimilar metal joining technology. We previously proposed a technology for bonding aluminum and copper by generating and discharging a molten eutectic in less than 1 second using current and pressure in an atmosphere. However, the kind of bonding process used in this method is not clear. In this study, we conducted a bonding experiment using the eutectic reaction between aluminum and copper by applying current and pressure and evaluated the bonding behavior when bonding occurs in a short time. As a result, it was found that the molten eutectic was generated and discharged within 0.35 s from the start of energization, and by continuing this behavior for 0.3 s, it was possible to obtain a bonding strength that would cause the base material fracture (joint efficiency 85-99%). The bonding strength required for base material fracture requires an interface temperature of 548℃ or higher, which is the eutectic temperature (548℃), and the appropriate interface temperature was approximately 600℃. We clarified the relationship between high-speed eutectic reaction behavior and bonding conditions, and confirmed the usefulness of bonding methods that utilize short-time eutectic reactions.

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With the expansion of clean energy, thermal power plants will be used as a load-following power plant. Thus, temperature and strain variations will occur during load fluctuations including start and stop of operation, and large-diameter pipes will be damaged by fatigue in addition to creep due to internal pressure. Especially, in a bent pipe such as an elbow pipe, bending and torsion are simultaneously applied. Therefore, it is important to predict the creep fatigue life in a bending and torsional stress environment. In this study, analysis method for creep fatigue life using Norton's law, ductile exhaustion law, and Manson-Coffin's law is proposed. Next, the proposed method was applied to the prediction of creep fatigue life of the test samples for thermal power plant piping, and the validity of the proposed method was verified by comparing creep fatigue life obtained by proposed method and that obtained by an experiment. In addition, the proposed method is applied to the prediction of creep fatigue life with load fluctuations and investigation of the effects of load fluctuation interval on creep fatigue life.

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Solidification cracking is one of the important problems on high-efficiency narrow-gap welding using the thick Ni-base alloy plate. It is generally said that the bead shape as the ratio of its depth and width (D/W) affects largely on solidification cracking, and the large D/W induces solidification cracking. In this research, the new indicator of the delta W, which is the difference between the maximum and minimum penetration depth, was proposed, and it was found that the delta W is correlated to solidification cracking. In addition, the sound bead without solidification cracking could be achieved by realizing the small delta W under the high efficiency (large D/W) using the optimized conditions for hot-wire laser welding.

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