High-skill tasks such as aircraft maintenance procedures generally require considerable on-the-job training (OJT). Because OJT requires a considerable amount of time, long-term scheduling of OJT by considering both working efficiency and skill development is required. The authors have proposed education coefficient (EC) as a parameter that adjusts the frequency of OJT and have proposed a scheduling support system for long-term scheduling of OJT considering working efficiency and skill education. Users of the proposed scheduling support system can easily adjust the balance between working efficiency and skill education by changing EC. However, it is difficult for them to find effective values of EC that realize a good balance between working efficiency and skill education to maintain a certain number of skilled workers. In this paper, we propose a simulation-based scheduling optimization system using a simple genetic algorithm (GA). The purpose of this study is to adjust the value of EC automatically by considering the balance between working efficiency and skill education and to find effective rules for adjusting the value of EC. The experimental results show that the proposed system computes solutions that are better than those computed by using a constant EC.

Introducing compressive residual stress by a cavitating jet into the sub-surface of components used in nuclear power plants can mitigate stress corrosion cracking in these components. Although applying the jet is an effective method for this purpose, it should be used without causing damage to the surface from water jet droplets arising from high-pressure injection of the water jet. Thus, in introducing compressive residual stress, the injection pressure needs to be optimized. In this paper, in order to determine the optimum injection pressure, the residual stress of stainless steel treated by a jet at various injection pressures was measured using an X-ray diffraction method. The injection pressure of the jet was varied from 5 MPa to 300 MPa, and the diameter of the nozzle throat of the jet was varied from 0.35 mm to 2.0 mm. The variation of residual stress with depth was measured by alternating X-ray diffraction measurements with electropolishing. It was revealed that a cavitating jet at an injection pressure of 10 MPa with a nozzle diameter of 2.0 mm can introduce higher compressive residual stress to deeper into stainless steel compared with a jet at 300 MPa with a nozzle diameter of 0.35 mm when the downstream pressure of the nozzle was constant.

In this review, the analysis of melting and solidification phenomena and the mechanism of the occurrence of defects as well as the analysis of melting and solidification using the numerical simulation in laser powder bed fusion (LPBF) process were introduced. In addition, the strategies of suppression of defects were described. The melting and solidification phenomena during LPBF process are relatively similar to those during welding. Since the plume brings about the strong recoil pressure on the melt pool, the keyhole takes place. And when the depth of keyhole becomes more than a threshold, the keyhole pore remains at the bottom of melt pool. Since the plume also brings about spattering and blows out powder, the gas pores are prone to occur easily. The micro-simulation of melting and solidification enables to reproduce the real phenomena. The macro-simulation of melting and solidification phenomena is one of the effective tools to predict the optimum fabrication condition. In order to prevent the occurrence of defects, it is significant not only to obtain the optimum fabrication condition using the process map but also to develop the simulation software. In addition, the use of the monitoring and feedback control system is greatly effective. Therefore the development of the cyber-physical system is needed.