The long waiting time between examinations is a serious issue in hospitals. This study explores how precedence constraints affect waiting times for examinees in health examination scheduling. We employ a 0-1 integer programming model to schedule examinations while ensuring the conditions for the number of examinees who can be examined concurrently and the precedence constraints between examinations are met. In the numerical analysis, we varied the precedence constraints based on the layout of the examination center and analyzed their effect on the total waiting time of the examinees. Based on these results, we provide recommendations for guiding examinees to achieve more efficient health examinations with reduced waiting times.

Milling is extensively used in manufacturing various products and parts, making it a vital processing method in the industry. The rational choice of milling process parameters is crucial for controlling the roughness of the machined workpiece. The focus of this study is to analyze the stability range of milling process parameters for 2024 aluminum alloy and examine their influence on surface roughness. Through sensitivity analysis integrated with Box-Behnken experimental design and response surface modeling, the impact of these parameters on surface roughness is explored. The response surface method is utilized to develop a second-order regression model that establishes the quantitative relationship between surface roughness and the milling process parameters. Comprehensive relative sensitivity analysis (CRSA, which evaluates the combined effects of global parameter interactions via Monte Carlo simulations) and localized single-parameter sensitivity analysis (LSPSA, quantifying individual parameter sensitivity via derivative-based methods) are integrated to assess parameter sensitivity characteristics and establish stability ranges. The research findings demonstrate that within the experimentally investigated parameter space (n = 6000~9000 r/min, a_e = 0.1~0.3 mm, a_p = 0.03~0.05 mm, v_f = 100~300 mm/min), the identified stability ranges are: spindle speed [7500 r/min~000 r/min], radial depth of cut [0.275 mm~0.300 mm], axial depth of cut [0.03 mm~0.05 mm], and feed rate [200 mm/min~250 mm/min]. This study provides a theoretical foundation for optimizing milling process parameters, while also offering guidance on controlling surface roughness and enhancing part performance.

In recent years, the number of lower limb injuries caused by stroke and traffic accidents has been increasing year by year, and the demand for rehabilitation equipment in the medical field is growing. This article proposes a rope driven lower limb rehabilitation robot and research on the fuzzy assisted interactive control. Firstly, according to the design requirements, the structure of the rope driven lower limb rehabilitation robot was designed, and its kinematics is analyzed to derive the inverse and forward kinematics solutions. Secondly, the feedback tension of the rope was processed with the gravity compensation database to obtain the active driving force for each posture of the patient. After fuzzifying, the active driving force was brought in fuzzy knowledge base to obtain the assisted pose parameters. Again, the obtained assistance pose parameters were softened through impedance control Double S velocity planning and admittance control, thereby achieving fuzzy assistance interaction control. Finally, the prototype of the lower limb rehabilitation robot was developed, and the rehabilitation exercise experiments were conducted to verify the feasibility and correctness of the control method. The research results provide theoretical and experimental basis for the design and control of medical rehabilitation robots.