Unlike the roll-to-roll process that uses a steel roll and a nip roll, a vacuum roll can hold and transfer a thin film using a single roll. To precisely manufacture a vacuum roll, a thin outer cylinder must be machined, which is assembled on the outside of the roll and contacts the film via vacuum pressure. In this study, the effects of jaw width and chucking force on the deformation of the outer cylinder during the turning process were investigated using analysis, and a precision machining and burr removal process was developed. The deformation of the outer cylinder decreased almost linearly with increasing jaw width and increased with higher chucking force and larger cylinder diameter. Additionally, the deflection due to the weight of the outer cylinder was approximately three times greater than that caused by film tension. For the machined outer cylinder, a burr removal experiment was conducted, and concentricity and cylindricity were measured. Using a device that removes burrs by rotating a wheel connected to the main shaft at high speed, it was found that burrs generated on the inner diameter could be removed very efficiently. On the vacuum side, the concentricity errors of the inner and outer diameters were 0.015 mm and 0.014 mm, respectively, and on the opposite side, they were 0.006 mm and 0.010 mm, respectively. Additionally, the measurement of Total Indicator Runout (TIR) according to the angle showed that the maximum cylindricity of the outer and inner diameters was 0.02 mm and 0.025 mm, respectively. Finally, through burr-height measurement at the hole boundary, it was found that the heights were within 0.05 mm.

Recently, there has been extensive research conducted on the miniaturization of semiconductors and the improvement of their integration to achieve high-quality and high-performance electronic devices. To integrate and miniaturize multiple semiconductors, thin and precise wafers are essential. The backgrinding process, which involves high-precision processing, is necessary to achieve this. The backgrinding system is used to grind and polish the back side of the wafer to reduce its thickness to ㎛ units. This enables the high integration and miniaturization of semiconductors and a flattening process to allow for detailed circuit design, ultimately leading to the production of IC chips. As the backgrinding system performs precision processing at the ㎛ unit, it is crucial to determine the stability of the equipment's rigidity. Additionally, the flatness and surface roughness of the processed wafer must be checked to confirm the processability of the backgrinding system. IIn this paper, the goal is to verify the processability of the back grinding system by analyzing the natural frequency and resonance frequency of the equipment through computer simulation and measuring and analyzing the flatness and surface roughness of wafers processed with backgrinding system. It was confirmed whether processing damage occurred due to vibration during the backgrinding process.

Lightweight of plastic containers is becoming an important issue due to increasing environmental legislation and consumer awareness. In this study, the CAE analysis was conducted to optimize the shape of a 500 ml lightweight square polyethylene terephthalate(PET) bottle. First, the linear buckling alaysis using the finite element method was performed to analyze the correlation between the primary geometric parameters of the bottle and the buckling critical load. Then, the optimal geometry parameters were derived, and the actual buckling load was predicted by non-linear buckling simulation. The validity of the simulation results was verified by top-loading tests of PET bottles molded with the optimized geometry. The elastic modulus and tensile yield strength of PET through tensile tests were measured to improve the accuracy of the simulation. As a result of the tensile tests, the modulus of elasticity of PET increased from 2,900 MPa to 4,275 MPa, and the tensile yield strength increased from 52.4 MPa to 88.1 MPa. Finally the buckling load of the optimized PET bottle was found to be approximately 236 N, which is very similar to the simulation precition of 238 N. This study shows the feasibility and accuracy of the CAE analysis approach for the lightweight design of PET bottles, and will provide useful guidelines for the design of PET bottles.

The automobile industry is a wide range of related industries, including parts manufacturing and vehicle assembly, press processing is an essential element in making automobiles. Press processing is a processing method for metal sheets that has relatively high dimensional and shape precision and is suitable for mass production. It refers to processing by attaching a special tool, a mold, to a press machine. Recently, the automobile industry is attempting to reduce the weight of automobiles in order to reduce carbon emissions due to global warming, and the use of high-strength steel sheets, which are lighter than general structural steel sheets, is a natural trend. Shear processing is required to use high-strength steel, and the shape of the shear surface created by shear processing has a significant impact on the quality of the automobile. Therefore, various methods are being attempted to improve the share surface during shear processing. Among them, shaving processing is a method of shearing the primary shearing area again, and it is difficult to obtain an accurate answer because complex deformation occurs in the microscopic shear area. Therefore, in this study, the effect of machining allowance on shaving processing was analyzed using the finite element method using high-strength steel plate (SPFH590), and the differences were compared and examined through actual experiments under the same conditions.

This study intends to reduce forming load by adding die rotation to flange-upsetting process. Materials arc formed by the compression and rotational torque which are accrued from rotation of the lower die accompanied by axial compression of the punch. For the theoretic analysis of flange-upsetting process using rotation die, slab method was used. Furthermore, for the verification of the theoretic analysis results, FEM simulation using DEFORM 3D a commercial software was done, and through the model material experiment using Prasticine, the results were compared and reviewed. Flange-upsetting process using rotation die shows reduced forming load compared with process without die rotation and demonstrates uniform distribution of strain. And as for the effect of the reduction of forming load, the less the aspect ratio(h₀/d₀) and the greater friction coefficient, the greater effect is. With increase in die rotation velocity, the effect of forming load reduction also increases little by little, but its effect on forming load reduction is very negligible compared with other forming parameters. Theoretic analysis results and simulation results coincided pretty well. The flange-upsetting process using die rotation are evaluated as useful process that can produce reduction of forming load and uniform strain.

Injection molding is a process widely used across various industries for molding plastics, and it is the most commonly applied process in root industries utilizing molds. Among the different types of injection molding, insert injection molding, where busbars are used as inserts, is increasingly being applied in the electric vehicle industry. However, currently, the insert injection molding process is manually performed, with workers placing insert components by hand before injection molding. This results in issues related to productivity, safety, and quality. Additionally, there is a growing demand for automation of such production lines due to hazardous working conditions, economic difficulties in the manufacturing industry, and the decline in the labor force caused by an aging population. This study focuses on the application of an automated system for the insert injection molding process used in electric vehicles. The development of an automated system for the transport and insertion of insert components, as well as the inspection and stacking processes after injection, has resulted in over a 25% improvement in productivity and more than a 27% reduction in defect rates.

In this study, experimental design methods were used to derive optimal process conditions for improving the thickness uniformity of a 0.40 mm, 3.5 inch light guide panel. Process mapping and expert group analysis were used to identify factors that influence the thickness of injection molded products. The key factors identified were mold temperature, mold temperature, injection speed, packing pressure, packing time, clamp force, and flash time. Considering the resin manufacturer's recommended process conditions and the process conditions for similar light guide plates, a three-level range was selected for the identified influencing factors. L27 orthogonal array process conditions were generated using the Taguchi method. Injection molding was performed using these L27 orthogonal array to mold the 3.5 inch light guide plates. Thickness measurements were then taken, and the results were analyzed using the signal-to-noise ratio to maximize the CpK value, leading to the determination of the optimal process conditions. The thickness uniformity of the product was analyzed by applying the derived optimum process conditions. The results showed a 97.5% improvement in the Cpk value of 3.22 compared to the process conditions used for similar light guide plates.

In this study, a tool was developed for analyzing production lead time in turning operations. It is expected to help to reduce machining time and to identify, for example, tool change intervals. The tool was developed using Visual Basic.Net and features a user-friendly graphical user interface (GUI) that allows users to easily input cutting conditions and calculate the usage time and feeding distance for each cutting tool based on a G-code program. Object-oriented programming techniques were also used to encapsulate and classify complex logic, thereby efficiently organizing and managing the functions and data structures of this analysis tool. The analysis tool provides various outputs. It calculates the use time of each detailed process of the turning operation, the use time of each tool, the use time of each type of feeding, and also generates the data needed for cutting time analysis, which can be visualized in charts. The analysis tool developed in this study is expected to significantly contribute to improving the efficiency of manufacturing processes and increasing productivity, particularly, in the manufacturing of components requiring massive material removal, such as aircraft parts.

In this study, the recyclability of commonly used PP (polypropylene) and ABS (acrylonitrile butadiene styrene) was evaluated by molding test specimens from mixture of virgin and shredded material, followed by measuring their strength properties, Experiments were conducted o two type of PP (transparent and non-transparent) and two types of ABS (white and yellow). Test specimens for each resin were prepared with shredded material ratios ranging from 10% to 50% in 10% increments. Changes in tensile strength, elastic modulus, and elastic limit were analyzed based on the mixing ratio of the shredded material. The experimental results demonstrated that the strength properties of all the resins remained consistent within a certain range, even with increasing proportions of shredded material. For transparent PP, the tensile strength ranged from 30.87± MPa, the elastic modulus from 1.23±0.04 GPa, and the elastic limit from 19.17±0.44%. Non-transparent PP exhibited a tensile strength ranging from 27.71±0.58 MPa, an elastic modulus from 1.03±0.06 GPa, and an elastic limit from 17.35±0.41%. For ABS, white ABS had a tensile strength of 39.42±0.28 MPa, an elastic modulus of 1.94±0.01 GPa, and an elastic limit of 36.76±0.25%. Yellow ABS showed a tensile strength of 39.25±0.78 MPa, an elastic modulus of 1.94±0.01 GPa, and an elastic limit of 37.14±0.23%, with values remaining consistent within this range. Based on these results, it was confirmed that the mechanical properties of the resins used in this study do not change significantly when mixed with recycled shredded material, indicating excellent mechanical recyclability.

The purpose of this paper is to introduce a fusion method that combines the design of experiments (DOE) and machine learning to optimize the bias of plastic products. The study focuses on the plastic motor housing used in automobiles, which is manufactured through plastic injection molding. Achieving optimal molding for the motor housing involves the optimization of various molding conditions, including injection pressure, injection time, holding pressure, mold temperature, and cooling time. Failure to optimize these conditions can lead to increased product deformation. To minimize the deformation of the motor housing, the widely used Taguchi method, which is one of the design of experiment techniques, was employed to identify the injection molding conditions that affect deformation. Machine learning was then applied to various models based on the identified molding conditions. Among the models, the Random Forest model emerged as the most effective in predicting deformation amounts. The validity of the Random Forest model was also confirmed through verification. The verification results demonstrated the excellent prediction accuracy of the trained Random Forest model. By utilizing the validated model, molding conditions that minimize deformation were determined. Implementation of these optimal molding conditions led to a reduction of approximately 5.3% in deformation compared to the conditions before optimization. It is noteworthy that all injection molding outcomes presented in this paper were obtained through robust injection molding simulations, ensuring both research objectivity and speed.