Considering the difficulties of the manufacturing industry by improving production efficiency in the era of high wages and aging in domestic automation facilities, automation facilities are considered an irreversible trend, but many serious related disasters are occurring due to the problems of increasing automation facilities due to the enlargement of manufacturing processes, line-up, and automation. The purpose of this study is to review the usage conditions and safety measures for industrial robots that are experiencing serious industrial accidents and are expected to continue to increase in facilities among automation facilities at the automation industrial site and propose ways to ensure the fundamental safety of the facilities at all times The suggestions are as follows. The purpose is to prevent safety accidents in advance by applying safety door aids to industrial sites and installing additional safety devices in safety slide door lock systems applied to safety fence doors of new and already installed facilities to detach safety keys and ensure that workers carry them at all times.

This study selected two labor-intensive processes in harsh environments among domestic food production processes. It analyzed their improvement effectiveness using 3-dimensional (3D) simulation. The selected processes were the “frozen storage source transfer and dismantling process” (Case 1) and the “heavily loaded box transfer process” (Case 2). The layout, process sequence, man-hours, and output of each process were measured during a visit to a real food manufacturing factory. Based on the data measured, the 3D simulation model was visually analyzed to evaluate the operational processes. The number of workers, work rate, and throughput were also used as comparison and verification indicators before and after the improvement. The throughput of Case 1 and Case 2 increased by 44.8% and 69.7%, respectively, compared to the previous one, while the utilization rate showed high values despite the decrease, confirming that the actual selected process alone is a high-fatigue and high-risk process for workers. As a result of this study, it was determined that 3D simulation can provide a visual comparison to assess whether the actual process improvement has been accurately designed and implemented. Additionally, it was confirmed that preliminary verification of the process improvement is achievable.

This paper describes the development and operation of an autonomous robotic system designed for pyroprocess automation. The unique challenges of pyroprocess automation, such as the need for a highly dry atmosphere to handle materials like chloride, are addressed through this system. For the experiments, a specialized dehumidifier and dry mock-up facility were designed to produce dry air condition. Performances of dry air conditioning for the various simulated situations were evaluated, including assessing worker access within a mock-up to determine the system’s feasibility. To enable automation, containers used for processing materials were modified to fit the gripper system of the gantry robot. The loading and unloading of materials in each equipment were automated to connect them with the robotic system. This gantry robot primarily utilized macro motions to approach waypoints containing process materials, reducing the need for precise approach motions. Its tapered jaw design allowed it to grip target objects even with imperfect positioning. The robot’s motions were programmed initially using a robot simulator for positioning and motion planning, and real-world accuracy was tested in a dry mock-up facility using the OPC platform. Finally, the paper discusses the potential application of XR (eXtended Reality) technology in this context, which could enhance the robot’s operation and provide valuable insights into the automation process. Further analysis of XR technology’s feasibility and benefits for this specific pyroprocess automation system are presented.

Recently, in the case of the root industry, although it is a basic industry that forms the basis of manufacturing competitiveness, there continues to be a shortage of manpower due to reasons such as dangerous working environments, industrial economic difficulties, and low wage systems. In addition, the demand for automation of production lines using robots is increasing due to a shrinking labor market due to a decrease in the working population due to aging, higher wages, shorter working hours, and limitations of foreign workers. In this study, a system was developed to automate the injection molding process for producing ball valves for automobiles by applying robot system. The applied process flow consists of alignment and insertion of insert parts, and removal, transfer, and loading of the product after injection molding, which is currently performed manually. Through the application of the developed robot automation system, the cycle time was improved by more than 30% and the defect rate was reduced by more than 70%.

Technological breakthroughs, combined with the demographic challenges of an aging population and the aftermath of the COVID-19 pandemic, spur new business opportunities in the service robot industry. From a management perspective, these technologies are positively evaluated in terms of increasing productivity, new business opportunities, and financial benefits (Belanche et al., 2020). However, although automation and robotics have already gained attention in the tourism and hospitality industry, research on their use in restaurants and the customer's attitude toward these new service solutions is still limited (Berezina et al., 2019; Ivanov et al., 2019; Kuo et al., 2017).

Radioactive waste can be classified according to the concentration level for radionuclides, and the disposal method is different through the level. Gamma analysis is inevitably performed to determine the concentration of radioactive waste, and when a large amount of radioactive waste is generated, such as decommissioning nuclear facilities, it takes a lot of time to analyze samples. The performance of a lot of analysis can cause human errors and workload. In general, gamma analysis is performed using by HPGe detector. Recently, for convenience of analysis, commercial automatic sample changers applicable to the HPGe detectors were developed. The automatic sample changers generate individual analysis reports for each sample. In this study, gamma analysis procedure was improved using the application of the automatic sample changer and the automated data parsing using by Python. The application of automatic sample changers and data parsing technique can solve the problems. The human errors were reduced to 0% compared to the previous method by improving the gamma analysis procedure, and working time were also dramatically reduced. This automation of analysis procedure will contribute to reducing the burden of analysis work and reducing human errors through various improvements.

Concrete radioactive waste is divided into surface-contaminated concrete and activated concrete, and although the generation rate varies depending on the operating conditions of the nuclear power plant, it is reported that the amount of surface-contaminated concrete generated is greater. It is reported in the ‘US-NRC Inventory Report’ that 99% of radionuclides in surface-contaminated concrete are distributed within 1 mm of the surface. Since concrete radioactive waste accounts for a large amount of generation after metal radioactive waste, it is necessary to reduce the amount of radioactive waste disposal by applying appropriate treatment techniques to surface-contaminated concrete. In this study, a similar contamination environment work space with the size of 5.4 (W) × 3.6 (L) × 2.5 (H) [m] in which concrete specimens can be fixed on the wall and floor was established. And an integrated decontamination equipment was verified the automation performance for ‘location accuracy’, ‘radioactive contamination level measurement’ and ‘concrete surface laser scabbling’. It was confirmed that the average was 8.3 [mm] in the evaluation of the ‘location accuracy’ for the remote control and movement of the integrated decontamination equipment. For performance verification of ‘radioactive contamination level measurement’ and ‘laser scabbling’, it were used that size of 30×30×8 [cm] ordinary concrete specimens and concrete radioactively contaminated with Co-60 below the regulatory exemption concentration. ‘Radioactive contamination level measurement’ is measured as much as the set range, divied and display the measured values in different colors on the map of the control program. Ordinary concrete specimens are 0.066~0.089 μ Sv/hr, and contaminated concrete specimens are 0.107~0.121 μ Sv/hr, and it was confirmed that they are expressed in different colors on the map. For ‘laser scabbling’, the performance according to the laser scabbling speed and reproducibility with ordinary concrete specimens was verified. As a result, a weight change of up to 1.48 kg was confirmed. Contaminated concrete specimens were subjected to a direct method using a surface contamination detector and an indirect method using a smear paper to measure surface contamination before and after scabbling, and the debris generated after scabbling was analyzed using HPGe.

Recently, the development of computer vision with deep learning has made object detection using images applicable to diverse fields, such as medical care, manufacturing, and transportation. The manufacturing industry is saving time and money by applying computer vision technology to detect defects or issues that may occur during the manufacturing and inspection process. Annotations of collected images and their location information are required for computer vision technology. However, manually labeling large amounts of images is time-consuming, expensive, and can vary among workers, which may affect annotation quality and cause inaccurate performance. This paper proposes a process that can automatically collect annotations and location information for images using eXplainable AI, without manual annotation. If applied to the manufacturing industry, this process is thought to save the time and cost required for image annotation collection and collect relatively high-quality annotation information.

Thin-film shape technology is recognized for its core technology to enhance the technology of LCD, PDP, semiconductor manufacturing processes, hard disks and optical disks, and is widely used to form coated thin films of products. In addition, resistance (electron beam filament) technology for heating is used to manufacture filament for ion implants used in semiconductor manufacturing processes. By establishing an electronic beam filament production system and developing seven specifications of electronic beam filament, it is contributing to improving trade dynamics and increasing exports to Japan through localized media of theoretical imports to domestic companies. In this study, CAE analysis was performed after setting electron beam filament specification and development objectives, facilities and fabrication for electron beam filament production, electron beam filament JIG & fixture design and fabrication followed by electron beam filament prototype. Then, the automation and complete inspection equipment of the previously developed electronic beam filament manufacturing facilities was developed and researched to mass-produce them, to analyze and modify prototypes, design and manufacture automation facilities, and finally, to design and manufacture the complete inspection equipment. In this paper, design and manufacture of electronic beam filament automation facilities for mass production were dealted with.

During the decommissioning of nuclear facilities, 3D digital model that precisely describes the work environment can expedite the accomplishment of the work. Thus, the workers’ exposure to radiation is minimized and the safety risk to the workers is reduced, while precluding inadvertent effects on the environment. However, it is common that the 3D model does not exist for legacy nuclear facilities as most of the initial design drawings are 2D drawings and even some of the 2D drawings are missing. Even in the case that all of the 2D drawings are intact, these initial design drawings need to be updated using asbuilt data because facilities get modified through years of operation. In those cases, 3D scanning can be a good option to quickly and accurately generate a structure’s actual 3D geometric information. 3D scanning is a technique used to capture the shape of an object in the form of point cloud. Point cloud is a collection of large number of points on the external surfaces of objects measured by 3D scanners. The conversion of point cloud to 3D digital model is a labor-intensive process as a human worker needs to recognize objects in the point cloud and convert the objects into 3D model, even though some of the conversion process can be automated by using commercial software packages. With the aim of full automation of scan-to-3D-model process, deep learning techniques that take point cloud as input and generate corresponding 3D model have been studies recently. This paper introduces an efficient scan simulation method. The simulator generates synthetic point cloud data used to train deep learning models for classifying reactor parts in robotic nuclear decommissioning system. The simulator is built by implementing a ray-casting mechanism using a python library called ‘Pycaster’. In order to improve the speed of simulation, multiprocessing is applied. This paper describes the ray casting simulation mechanism and compares the in-house scan simulator with an open source sensor simulation package called Blensor.

This thesis relates to developing an index drilling automation system that quickly and efficiently processes a hole in a product by a rotating robot arm and transfer devices. Static structural analysis was performed using the ANSYS Mechanical program to evaluate the structural stability of the system. According to the research, the equivalent stress value is low overall, and the minimum safety factor is 4.42, so it seems structurally safe. This system will significantly help improve productivity through unmanned work as it can control and set the drill and index simultaneously on the control panel in conjunction with the training.

Interest in the rammed construction method using eco-friendly materials is increasing in modern architecture. However, the work of construction is not convenient and will require a lot of manpower and time. This study proposes an automation compactor consisting of a compactor frame, crank arm, servo motor, wire, and a compactor hammer. The compactor hammer is fixed on the wire to achieve up-down movement by servo motor. And the state of up-down movement of the proposed compactor in 4 steps was had a dynamic analyzed. Through the actual compression experiment, the reliability of the proposed compactor is verified and is expected to be used in rammed earth construction.

현재 교량과 같은 토목구조물의 설계프로세스는 1차 설계 후 구조 검토를 수행하여 기준에 부적합할 경우 재설계하는 과정을 반복 하여 최종적인 성과품을 만드는 것이 일반적이다. 이러한 반복 과정은 설계에 소요되는 기간을 연장시키는 원인이 되며, 보다 수준 높 은 설계를 위해 투입되어야 할 고급 엔지니어링 인력을 기계적인 단순 반복 작업에 소모하고 있다. 이러한 문제는 설계 과정 자동화를 통하여 해결할 수 있으나, 설계 과정에서 사용되는 해석프로그램은 이러한 자동화에 가장 큰 장애요인이 되어 왔다. 본 연구에서는 기 존 설계 과정 중 반복작업을 대체하고자 강화학습 알고리즘과 외부 해석프로그램을 함께 제어할 수 있는 인터페이스를 포함한 교량 설계 프로세스에 대한 AI기반 자동화 시스템을 구축하였다. 이 연구를 통하여 구축된 시스템의 프로토타입은 2경간 RC라멘교를 대 상으로 제작하였다. 개발된 인터페이스 체계는 향후 최신 AI 및 타 형식의 교량설계 간 연계를 위한 기초기술로써 활용될 수 있을 것 으로 판단된다..