• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.171-178
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• 2013

Workers are avoiding production/manufacturing sites due to the poor working environment and concern over safety. Small and medium-sized businesses introduce new equipment to secure safety in the production site or ensure effective process management by introducing the real-time monitoring technique for existing equipment. The importance of real-time monitoring of equipment and process in the production site can also be found in the ANSI/ISA-195 model. Note, however, that most production sites still use paper-based work slip as a process management technique. Data reliability may deteriorate because information on the present condition of the production site cannot be collected/analyzed properly due to manual data writing by the worker. This paper introduces the monitoring and process management technique based on a direct facility interface to secure safety in the field by improving the poor working environment and enhance there liability and real-time characteristics of the production data. Since the data is collected from equipment in real-time directly through the SIB-based interface and PLC-based interface, problems associated with workers' manual data input are expected to be solved; safety can also be improved by enhancing workers' attention to work by minimizing workers' injuries and disruption.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.1-12
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• 2020

Recently, research using machine learning have shown remarkable results in various domains, leading to the fact that leaning-based dispatchers have intrigued interest in both academia and industry. To improve the performance of the dispatcher, each dispatch decision needs to be evaluated in detail. However, existing studies on visualization techniques for manufacturing lines have mainly focused on illustrating the performance indicators or abnormal patterns. In this paper, we propose a monitoring system that displays a variety of information about the manufacturing line along with alternatives at the time of each dispatching decision being made. Furthermore, the proposed system effectively represents the cause of the idle time of resources and the change of the performance index over time.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.19 no.4
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• pp.390-402
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• 2009

This study aimed to examine the general characteristics of individual workers, psychosocial working environment, and ergonomic risk factors which affect the status of musculoskeletal disorders. Self-report was carried out for musculoskeletal symptoms and ergonomic risks in working environment in 856 production workers in 16 small to medium sized manufacturing companies. Musculoskeletal symptoms were examined with a standardized questionnaire, and ergonomic risks were evaluated with a qualitative self-administered instrument for the tasks related to musculoskeletal disorders. Major findings were as follows: 1) Complaint rate for musculoskeletal symptoms was higher in female, aged, married workers with longer working hours, less leisure/hobby activity, longer household working hours and history of disease or accident. 2) Complaint rate for musculoskeletal symptoms was significantly higher in workers with dissatisfaction, difficult tasks, and no self-control at work. 3) Complaint rate for musculoskeletal symptoms was significantly higher in workers involved in tasks with major ergonomic risk factors, and handling heavy equipment. 4) Explanatory power increased the model with the musculoskeletal symptoms as dependent variable and demographic variables, psychosocial working environment and ergonomic risk factors included, and total explanatory power of 18.6% revealed the significant effect. Based on the results, we can conclude that musculoskeletal symptoms in manufacturing workers are associated with individual demographic characteristics, psychosocial working environment and ergonomic risk factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1610-1629
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• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• Clean Technology
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• v.13 no.2
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• pp.109-114
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• 2007

In this study, we performed basic researches to develop wet purification system for improving air qualities of ventilation in semiconductor manufacturing process. Using 0.5 M aqueous solution of $KMnO_4$, 50 ppm of $NH_3$, SOx and NOx were reduced to 99% successfully. However, the removal of $O_3$ was limited to $22{\sim}30%$ for all the tested chemical solutionsincluding $KMnO_4$. Therefore, adoption of a dry ozone filter is necessary to reduce $O_3$ below a satisfactory level. For all the chemical solutions tested, NOx removal efficiency increased as NOx was mixed with $O_3$. As chemical solution was sprayed using water spraying system equipped with air atomizing type nozzle, the removal efficiencies of gaseous pollutants increased due to the increase of gas-liquid interfacial area.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.5
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• pp.447-454
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• 2015

Design and application of hardware-in-the-loop simulation (HILS) for design of CNC-controlled machine tool feed drives is discussed. The CNC machine tool is a complex mechatronics system where the complexity results from the software-based controller composed of a variety of functionalities and advanced control algorithms. Therefore, using a real CNC controller in the control simulation has merits considering the efforts and accuracy of the simulation modeling. In this paper challenges in HILS for a CNC controlled feed drive, such as minimization of time delay and transmission error that are caused by discretization of the feed drive model, is elaborated. Using an experimental HILS setup of a machine tool feed drive applications in controller gain selection and CNC diagnostics are presented.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.314-323
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• 2013

Production simulation technology is beneficial to solve the complicated and fluctuated problems in a shipyard. It takes too much time and effort to build simulation models in the field, though. This research proposes a feasible method to reduce the difficulties related to simulation modeling for the factory or shop capacity analysis. In addition, a proposed neutral data format for production information is efficient to manage information acquisition for simulation modeling automation. A panel block shop model is contributed to comparison between the conventional technique and the automated one. The automation technique is highly recommended to run a rapid simulation in the shipyard problem.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.329-347
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• 2019

The shipbuilding industry is characterized by order production, and various processes are performed simultaneously in the construction of ships. Therefore, effective management of the production process and productivity improvement form important key factors in the industry. For decades, researchers and process managers have attempted to improve processes by using business process analysis (BPA). However, conventional BPA is time-consuming, expensive, and mainly based on subjective results generated by employees, which may not always correspond to the actual conditions. This paper proposes a method to improve the production process of offshore plant modules by analysing the process mining data obtained from the shipbuilding industry. Process mining uses information accumulated from the system-provided event logs to generate a process model and determine the values hidden within the process. The discovered process is visualized as a process model. Subsequently, alternatives are proposed by brainstorming problems (such as bottlenecks or idle time) in the process. The results of this study can aid in productivity improvement (idle time or bottleneck reduction in the production process) in conjunction with a six-sigma technique or ERP system. In future, it is necessary to study the standardization of the module production processes and development of the process monitoring system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.116-128
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• 2020

In the shipbuilding industry, three-dimensional (3D) templates play a key role in the completeness evaluation of shell plates with a large curvature in the shell-plate fabrication process. Currently, the information of 3D templates from a ship computer-aided design system is limited; thus, manufacturers depend on their experience to produce the templates manually. This results in the inaccuracy of templates in addition to increased production time. Therefore, if the pieces of the 3D templates can be produced automatically with accurate information, the lead time of the fabrication process can be reduced. In this study, we define a new type of template piece and develop methods for extending a boundary template and converting manufacturing information into numerical control machine input. In addition, based on the results of the study, we propose a production automation system for 3D template pieces. This system is expected to reduce the lead time of the fabrication process.

• Smart Structures and Systems
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• v.30 no.1
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• pp.35-47
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• 2022

Data-driven engineering is crucial for information delivery between design, fabrication, assembly, and maintenance of prefabricated structures. Design for manufacturing and assembly (DfMA) is a critical methodology for prefabricated bridge structures. In this study, a novel concept of digital engineering model that combined existing knowledge of DfMA with object-oriented parametric modeling technologies was developed. Three-dimensional (3D) geometry models and their data models for each phase of a construction project were defined for information delivery. Digital design models were used for conceptual design, including aesthetic consideration and possible variation during fabrication and assembly. The seismic performance of a bridge pier was evaluated by linking the design parameters to the calculated moment-curvature curves. Control parameters were selected to consider the tolerance control and revision of the digital models. Digitalized fabrication of the prefabricated members was realized using the digital fabrication model with G-code for a concrete printer or a robot. The fabrication error was evaluated and the design digital models were updated. The revised fabrication models were used in the preassembly simulation to guarantee constructability. For the maintenance of the bridge, the as-built information was defined for the prefabricated bridge piers. The results of this process revealed that data-driven information delivery is crucial for lifecycle management of prefabricated bridge piers.