In the world package sorting machines are playing an essential role. Most of the machines are based on PLC or color sensor-based. In this paper, we have made a unique design of a package sorting machine that is based on bar code detection. The microcontroller we are using is Arduino, and the conveyor design is based on a new conveyor method that will make the sorting speed faster and have perfect accuracy. This paper and design introduce the application of parcel box sorting, which saves the sorting time and reduces the cost. With the continuous improvement of the level of the manufacturing industry, to increase the efficiency output of production and distribution, a simple automatic sorting based on bar code detection is realized in mechanical design. The belt conveyor system is designed for low friction, fast sorting, and high precision. The main purpose of the system is to save production time and manufacturing labor costs. Discusses the project, size, capacity, speed, roller diameter, pulley, power, tension, control mode, and advanced conveyor mechanical design.

Tungsten alloys are widely used in aerospace, military defense, the nuclear industry, medical applications, and other critical manufacturing fields due to their exceptional physical and chemical properties, including corrosion resistance, high hardness, high boiling point, low vapor pressure, and high strength. As the demand for tungsten alloys grows, there is a need for improved accuracy, quality, and surface integrity in their manufacturing and processing. Conventional Grinding (CG) methods for tungsten alloys faced challenges such as fast tool wear, brittle fracture, high grinding force, and high temperature. Rotary Ultrasonic Grinding (RUG) was developed to overcome these limitations, combining traditional and ultrasonic machining to enhance Material Removal Rates (MRR). This research involved grinding of tungsten alloy (W-Ni-Fe) simulations in Abaqus software and experiments on CNC machines, comparing RUG and CG carried out by Taguchi experimental design method to study the influences of spindle speed, grinding depth, feed rate, ultrasonic frequency, and amplitude on the grinding force generated in grinding of tungsten alloy. Results indicated that RUG reduces grinding force compared to CG. Increased grinding depth and feed rate raised the grinding force, while the grinding force was reduced by increasing ultrasonic amplitude. Finally, for optimal grinding force reduction in processing, a smaller grinding depth and feed rate, higher spindle speed, moderate ultrasonic frequency, and amplitude should be selected.

Large-diameter rescue shafts serve as critical infrastructure for emergency response in mining disaster scenarios, and their structural deformation directly affects the safe passage of rescue capsules. In this paper, we investigate three-dimensional (3D) reconstruction techniques for large-diameter rescue shaft environments and develop a Neural Radiance Fields (NeRF)-based reconstruction and deformation assessment scheme. The proposed workflow integrates no reference signal-to-noise-ratio (NR-SNR), image-quality filtering, SfM-based camera-pose estimation, Nerfacto reconstruction, point-cloud export, and circular-section fitting. The NR-SNR retention-ratio experiment shows that retaining approximately 35% high-quality images provides a practical efficiency–quality trade-off for the present dataset, reducing the computational burden of SfM pose estimation while preserving sufficient geometric information for subsequent reconstruction. The reconstructed radiance field is further exported as a dense point cloud and evaluated using relative radius error, circle-fitting residuals, and image-level rendering metrics. Experiments on a simulated large-diameter rescue shaft platform show that the proposed NeRF-based scheme provides favorable geometric measurement applicability and visual reconstruction quality under weak-texture and low-illumination conditions. Compared with conventional MVS and the tested 3DGS baseline, the proposed scheme produces a point-cloud output that is more suitable for subsequent circular-section fitting and deformation-related assessment. In addition, comparison with a representative SDF-based baseline indicates that direct implicit surface recovery remains challenging for the tested hollow cylindrical shaft-wall scene. The results demonstrate the potential of the proposed NeRF-based workflow for rescue-shaft inner-wall reconstruction and engineering-oriented deformation evaluation.