The cutting performance of cutting tools in high-speed machining (HSM) is an important factor restricting the machined surface integrity of the workpiece. The HSM of AISI 4340 is carried out by using coated tools with TiN/TiCN/TiAlN multi-coating, TiAlN + TiN coating, TiCN + NbC coating, and AlTiN coating, respectively. The cutting performance evaluation of the coated tools is revealed by the chip morphology, cutting force, cutting temperature, and tool wear. The results show that the serration and shear slip of the chips become more clear with the cutting speed. The lower cutting force and cutting temperature are achieved by the TiN/TiCN/TiAlN multi-coated tool. The flank wear was the dominant wear form in the milling process of AISI 4340. The dominant wear mechanisms of the coated tools include the crater wear, coating chipping, adhesion, abrasion, and diffusion. In general, a TiN/TiCN/TiAlN multi-coated tool is the most suitable tool for high-speed milling of AISI 4340, due to the lower cutting force, the lower cutting temperature, and the high resistance of the element diffusion.

To address the strong coupling, nonlinearity, and disturbances caused by microbial biochemical reactions in temperature and humidity control during soy sauce koji production, this study presents an engineering application and comparative investigation of three progressive control strategies: feedforward decoupling PI (FFD-PI) control, particle swarm optimization-based PI (PSO-PI) control, and fuzzy gain-scheduled PI (FGS-PI) control. A dynamic temperature–humidity model is first identified, and a multi-input multi-output closed-loop system based on PI control is established. Feedforward decoupling is then introduced to reduce the interactions between the temperature and humidity control loops, followed by offline optimization of the two PI controllers using particle swarm optimization. Based on the optimized parameters, fuzzy gain scheduling is further applied to adjust the controller gains online. Simulation results show that all three strategies achieve effective temperature and humidity setpoint tracking. PSO-PI improves the dynamic response and disturbance rejection capability, whereas fuzzy gain-scheduled PI provides better overshoot suppression and lower error indices. Under the koji-turning disturbance, the temperature and humidity overshoots are reduced by 62.2% and 48.3%, respectively. These results indicate that the PSO-initialized fuzzy gain-scheduled PI method improves temperature and humidity control performance and provides a useful reference for the intelligent control of koji production environments.