In continuous-process systems, failures of rolling-element bearings typically cause accidents, reduced productivity, and production-related financial losses. Therefore, predicting both the lifespan of rolling-element bearings and their replacement time is crucial for preventing machine system failures. Accordingly, numerous studies have reported various machine and deep learning classifiers for predicting the lifespan of bearings. However, these studies did not consider degradation trends of bearings. Thus, this study aimed to develop an algorithm to predict the lifespan of a bearing by considering its degradation trend. A vibration dataset of bearings was obtained at low and high speeds. Using a second-order curve-fitting model, various degradation patterns in the dataset were classified. Appropriate time-domain or frequency-domain feature variables applicable to the design of a classifier were determined according to classified patterns. In addition, the classifier was trained using multiple bidirectional long short-term memories. Finally, the performance of the developed classifier was verified experimentally.

Directed energy deposition (DED) additive manufacturing technology enhances the functionality of existing or damaged parts by adding metallic materials to the surfaces. Blown-powder DED technology utilizes a focused, high-energy source to fuse the part’s surface with the supplied metal powder. Maintaining a constant stand-off distance (SOD), the distance between the deposition head and the workpiece, is a key factor in ensuring deposition quality, as variations in SOD will change the powder focus position and the laser spot size on the surface. Therefore, traditional additive manufacturing systems require CAD or pre-scanned surface data. In this study, we proposed auto-surface tracking technology. No workpiece CAD data or pre-scanned surface data are required, and in-situ measurement and feedback control can automatically consider the deposition height differences that cause a change in SOD when depositing the next layer. The accuracy of the SOD measurements and feedback control error was verified using a step height sample. The mean SOD measurement error was 4.7 ㎛ with a standard deviation of 42 ㎛ (reference SOD, 14 ㎜). The feasibility of the autosurface tracking technology was confirmed through the additive manufacturing processes of the gear and an actual blanking mold applied in the defense and industrial fields.

Tool condition monitoring is one of the key issues in mechanical machining for efficient manufacturing of the parts in several industries. In this study, a tool condition monitoring system for milling was developed using a tri-axial accelerometer, a data acquisition, and signal processing module, and an alexnet as deep learning. Milling experiments were conducted on an aluminum 6061 workpiece. A three-axis accelerometer was installed on a spindle to collect vibration signals in three directions during milling. The image using time-domain, CWT, STFT represented the change in tool wear of X, Y axis directions. Alexnet was modified to learn images of the two directional vibration signals, to predict the tool condition. From an analysis of the results of learning based on the experimental data, the performance of the monitoring system could be significantly improved by the suitable selection of the data image method.

Slot-die coating technique has become a subject of interest owing to its mass and large area production characteristics. To date, numerous research on the fluid dynamics of coated solution and experimental decision of the coating conditions to improve quality of coated layer have been conducted. However, few studies have been done on the optimization of slot-die coater geometry owing to the high cost associated with its fabrication. In this study, we optimize the geometry of the slotdie coater using computational fluid dynamics. We used a statistical optimization technique (Box-Behnken design). In the optimization process, we determined the significant factors that affect the velocity variation of coated fluid in the transverse direction. An optimal geometry was derived using a desirability test which is generally used to evaluate the suitability of a selected geometry value based on the maximization of the velocity uniformity. Experimental results presenting the uniformity of the coated layer in the transverse direction improved from 4.7% to 1.4%.

In modern society, industries are being upgraded in various fields. In particular, the defense industry has developed numerous technologies, such as the localization of core military technologies. The defense industry is actively studying technologies in areas such as in helicopters and tanks. In the case of radars, research on the radar itself is very active as is the research on the components that make up the radar. In this study, the temperature distribution of the two types of evacuation centers that make up the radar were analyzed using Computer Fluid Dynamics (CFD) to identify the temperature distribution based on the internal structure of the shelter. The two types of shelters have different heating values in different arrangements in the shelter provided they have the same size of heat source. Simulation results showed that the average temperature at the KA LNA shelter was different. In this study, we analyzed the effects of internal structure on the temperature and confirmed that the internal temperature may be decreased by changing the structure without using an external cooling element.

With the advent of high-tech products, the need for ultra-precision machining has become increasingly necessary, along with the need for a jig center machining center capable of precision machining. A jig center maintains the accuracy of a jig borer, and also has an automatic tool changer like that of a machining center. It performs various machining functions in addition to hole machining and is the most precise and rigid machine tool. Various control methods and analytical techniques to improve machining accuracy are currently being developed in the field of ultra-precise large-scale machine tools. One relevant finding is that the degree of deformation varies depending on the weight of the machine tool as well as the ground conditions. It is therefore necessary to optimize ground conditions before installing the machine tools so as to improve the machining accuracy. The depth of concrete as well as the depth and diameter of grout were selected as variables. We developed the simulation case through structural analysis to consider the position of columns and tables. As a result of optimizing the foundation condition, it was found that the relative displacement error was reduced by up to 98% compared to the rigid foundation condition.

Recent manufacturing methods for fabricating flexible devices have attracted a keen interest, with a strong demand by industrial manufactures. For thin film application on flexible devices, slot-die coating was found to be the most suitable method having excellent uniformity. Optimization of the reservoir of slot-die coater should be prioritized, since it is an important parameter affecting the uniformity of the final outcome of the coated layer. However, the numerous designs of reservoir makes prototyping difficult, and also results in high manufacturing cost. This study analyzed the velocity deviation of the slot-die coater outlet using CFD analysis, and shape optimization was performed by contour map. We introduce a facile and low-cost fabrication method for a slot-die coater, using polydimethylsiloxane materials and three-dimensional printing technique. The fabricated polymer slot-die coater was further evaluated by the leakage test of solution.

This study proposes a method for identifying correlations between tension and drop height for sessile droplets in a roll-toroll processing system. The effect of tension and drop height on the contact angle of a sessile droplet is presented. Design of experiment (DOE) methodology and statistical analysis are used to define a correlation between the process parameters. The contact angle is decreased while increasing tension and drop height. The influence of the tension is less significant on the contact angle compared with the effect of the drop height. However, tension should be considered as a major parameter because it is not easy to fix with roll eccentricity and compensating speed of the driven roll. The results of this study show that the effect of tension on the contact angle of a sessile droplet is more important than drop height because the drop height is fixed when the process systems are determined.

Bearings have various uses in industrial equipment. The lifetime of bearings is often lesser than anticipated at the time of purchase, due to environmental wear, processing, and machining errors. Bearing conditions are important, since defects and damage can lead to significant issues in production processes. In this study, we developed a method to diagnose faults in the bearing conditions. The faults were determined using kurtosis, average, and standard deviation. An intrinsic mode function for the data from the selected axis was extracted using empirical mode decomposition. The intrinsic mode function was obtained based on the frequency, and the learning data of ANN (Artificial Neural Network) was concluded, following which the normal and fault conditions of the bearing were classified.

Computational fluid dynamic simulation based on the ABAQUS software was conducted to observe the inside flow of slot-die nozzle. The slot-die nozzle was modeled as 3-dimensional structure and three significant parameters were determined: inlet velocity of fluid, reservoir angles, number of strips none of which have been mentioned previously in the literature. The design of experiment, full factorial analysis was performed within determined design and process levels. The simulation result shows the inlet fluid velocity is most significant factor for the flows of inside nozzle. As an interaction effect, reservoir angle is closely related with number of strip that should address when the nozzle is designed. Moreover, the optimized values of each determined parameter were obtained as 35 mm/s of inlet velocity, 3 of strip numbers, and 22° of reservoir angles. Based on these parameters, the outlet velocity was obtained as 0.53% of outlet uniformity which is improved from 8.67% of nominal results.

Winding is one of the major processes in roll-to-roll systems. Taper tension profile in a winding determines the distribution of stress in the radial direction, i.e., the radial stress in the wound rolls. Maximum radial stress is major cause of material defect, and this study has been actively proceeded. Traditional models of radial stress model were focused on flexible and light substrate. In this study, we developed an advanced radial stress model including effects of both these parameters(weight and stiffness) on the radial stress. The accuracy of the developed model was verified through FEM(Finite Element Method) analysis. FEM result of maximum radial stress value corresponds to 99 % in comparison to result with the model. From this study, the material defects does not occur when the steel winding. And steel industry can be applied to improve the winding process.

In a roll-to-roll continuous system, winding is one of the most important processes since it determines the quality of the final manufactured products such as flexible film and printed electronic devices. Since an adequate winding tension can reduce the incidence of the defects that are derived from the inner stress of the wound roll such as starring and telescoping, it is necessary to determine the optimal taper-tension profile. In this study, an algorithm for the setting of an optimal taper-tension profile in consideration of the residual stress in the wound roll is suggested; furthermore, the algorithm was adjusted for the determination of an optimal tapertension profile regarding the winding process of 10 ㎛ polypropylene (PP) film. As a result of the algorithm-generated, optimal taper-tension profile, the residual stress and radial stress in a PP wound roll were decreased to 27.37 % and 40.05 % (mean value), respectively.

A roll-to-roll (R2R) continuous manufacturing system for a carbon-nanotube (CNT)-/silvernanowire (AgNW)- based large-area transparent conductive film was introduced in this study. The systemic guidelines of the R2R slot-die coating process including roll eccentricity, wrap angle, pump accuracy, and blower influence were discussed. To simulate the coating phenomenon, we investigated the governing parameters of the coating process by incorporating the estimated relative thickness that was defined by combining the viscocapillary model and volume model. By using experimental and mathematical approaches, an excellent transparent conductive layer with a 40 Ω/□ sheet resistance and 88 % transmittance was obtained; moreover, a dimensionless number identifies the correlation between the transparent conductive film and the anti-reflection film.

Slot-die coating is well known technique to guarantee a uniformly coated layer and is compatible with roll-to-roll process. In actual roll-to-roll slot-die coating process, the lateral difference of coated layer thickness is observed. An experimental study was performed to improve the coating quality. Coating speed and coating gap were selected as the experimental factors. A full factorial, statistical method was conducted to optimize the process conditions. Based on the results of repeated experiment, the lowest deviation of lateral thickness (700 nm, <10%) was achieved at 10 m/min coating speed and 300 μm coating gap. This result has significance because such optimized process guideline can be utilized with all process improvement in various coating applications.