• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.199-206
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• 2022

A malfunction or breakdown of a manufacturing facility leads to product defects and the suspension of production lines, resulting in huge financial losses for manufacturers. Due to the spread of smart factory services, a large amount of data is being collected in factories, and AI-based research is being conducted to predict and diagnose manufacturing facility breakdowns or manufacturing site efficiency. However, because of the characteristics of manufacturing data, such as a severe class imbalance about abnormalities and ambiguous label information that distinguishes abnormalities, developing classification or anomaly detection models is highly difficult. In this paper, we present an deep learning algorithm for anomaly detection of a manufacturing facility using reconstruction loss of CNN-based model and ananlyze its performance. The algorithm detects anomalies by relying solely on normal data from the facility's manufacturing data in the exclusion of abnormal data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.334-338
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• 2000

One of the major drawbacks of the existing facility layout methods is that most of them were developed based on pre-defined cost functions, and therefore fail to cope with the dynamic aspects of modern manufacturing systems. Another drawback is that due to the poor representation capability of the block diagrams, they are not able to convey the sufficient information needed by facility designers. In this paper, a system for solving facility layout problem considering these matters in cellular manufacturing environment is proposed and implemented using GA approach with embedded simulation module and virtual reality technologies.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.84-90
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• 2000

The importance of Virtual Manufacturing System is increasing in the area of developing new manufacturing processes, implementing automated workcells, designing plant facility layouts and workplace ergonomics. Virtual manufacturing system is a computer system that can generate the same information about manufacturing system structure, states, and behaviors as is observed in a real manufacturing. In this research, a virtual manufacturing system for flexible manufacturing cells (VFMC), (which is a useful tool for building Computer Integrated Manufacturing (CIM), has been developed using object-oriented paradigm, and implemented with software QUEST/IGRIP. Three object models used in the system are the product model, the facility model, and the process model. The concrete behaviors of a flexible manufacturing cell are re[presented by the task-oriented description diagram, TIC. An example simulation is executed to evaluate applicability of the developed models, and to prove the potential value of virtual manufacturing paradigm.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.71-81
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• 2010

Today's fierce competition and global economic recession make most of manufacturing companies in the world difficult to gain a profit. In order to survive such a environment and increase competitiveness, manufacturing companies have to continuously eliminate their wasteful factors through an efficient process analysis, improve quality of products, increase the flexibility of manufacturing processes. In this paper, we consider a case study for the Shanghai New Auto which is a subcontractor of MOBIS in China, to improve productivity by using therblig method, one of the motion analysis, to minimize the work-in-process inventories and to shorten the manufacturing cycle times. We also try to relocate the facility layout to increase the efficiency and flexibility of manufacturing processes.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.224-228
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• 1999

When we construct a manufacturing plant, optimal design is very important. This paper is to simulate an engine manufacturing flow line for commercial vehicle. The parameters we consider in simulation include facility downtime, tool change time, buffer size between consecutive stations, and time to repair the facility. We use AutoMod to compare the alternatives. The objective is to minimize the total cost. Simulation results provide significant cost saving by improving the current design and policy.

• Journal of Environmental Health Sciences
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• v.47 no.3
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• pp.267-278
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• 2021

Objectives: Using atmospheric dispersion representative models (AERMOD and CALPUFF), the emissions characteristics of each model were compared and analyzed in ready-mixed concrete manufacturing facilities that generate a large amount of particulate matter (PM-10, PM-2.5). Methods: The target facilities were the ready-mixed concrete manufacturing facilities (Siheung RMC, Goyang RMC, Ganggin RMC) and modeling for each facility was performed by dividing it into construction and operation times. The predicted points for each target facility were selected as 8-12ea (Siheung RMC 10, Goyang RMC 8, and Gangjin RMC 12ea) based on an area within a two-kilometer radius of each project district. The terrain input data was SRTM-3 (January-December 2019). The meteorological input data was divided into surface weather and upper layer weather data, and weather data near the same facility as the target facility was used. The predicted results were presented as a 24-hour average concentration and an annual average concentration. Results: First, overall, CALPUFF showed a tendency to predict higher concentrations than AERMOD. Second, there was almost no difference in the concentration between the two models in non-complex terrain such as in mountainous areas, but in complex terrain, CALPUFF predicted higher concentrations than AERMOD. This is believed to be because CALPUFF better reflected topographic characteristics. Third, both CALPUFF and AERMOD predicted lower concentrations during operation (85.2-99.7%) than during construction, and annual average concentrations (76.4-99.9%) lower than those at 24 hours. Fourth, in the ready-mixed concrete manufacturing facility, PM-10 concentration (about 40 ㎍/m³) was predicted to be higher than PM-2.5 (about 24 ㎍/m³). Conclusions: In complex terrain such as mountainous areas, CALPUFF predicted higher concentrations than AERMOD, which is thought to be because CALPUFF better reflected topographic characteristics. In the future, it is recommended that CALPUFF be used in complex terrain and AERMOD be used in other areas to save modeling time. In a ready-mixed concrete facility, PM-10, which has a relatively large particle size, is generated more than PM-2.5 due to the raw materials used and manufacturing characteristics.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.453-467
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• 2020

This study aimed to inventory the water pollutant discharge of wastewater from two facilities, one primary steel manufacturing facility and one petroleum refinery, both of which are located in Korea, and to identify ways to improve the wastewater treatment process through field investigation. Probability evaluation was used to inventory the substances in polluted water. The samples collected in this study included original wastewater, on processing wastewater, and treated water. The general description of wastewater occurrence, major sources, and treatment facilities were also investigated to obtain an integrated database of the pollutants created by different industrial categories. Based on our analysis of raw wastewater and final effluent, the detected pollutants were confirmed by analyzing their presence in the raw or supplemental materials, the potential of formation as byproducts, and the possibility of inclusion as impurities. The compounds detected for each category were screened via investigation of their possible sources and confirmed as the final water pollutant inventories. Thirty kinds of water pollutants were emitted by the primary steel manufacturing facility (reference in case A), including 14 specified hazardous water pollutants. The petroleum refinery (reference in case B) emitted 36 water pollutants, including 16 specified hazardous water pollutants.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.35-41
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• 1998

The workplace noise environment is composed of three basic elements : manufacturing (in a generic sense) facilities, office areas, and the community around the facility. Work must be done by all employees , and this involves communication within a variety of locations within the facility ; areas may be extremely noisy, moderately noisy, or quiet, such as an office. At the same time, the facility should not be annoying to the community. In this paper, the workplace environmental noise of office areas in power plant are studied. Turbine generator in power plant generates the noise of 90∼95 dB(A) in the frequency range of 1 kHz, which may cause occupational hearing loss. By abatement method which are made of isolation material and distance damping effect, about 29.5 dB(A) reduction has been obtained in office areas of the Power Plant . But, the workplace environmental noise of office areas in the power plant is not suited to office's purpose.

• Korean Journal of Organic Agriculture
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• v.21 no.3
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• pp.305-319
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• 2013

In this study, it is intended that utilize the LCA (Life Cycle Assessment) method, to evaluate the environmental impact of wood pellet manufacturing facility. As mentioned above, wood pellet manufacturing facility of 20 has produced wood pellets as a raw material sawdust and wood in our country. In this study, in order to feature manufacturing process of wood pellets that resemble almost necessary to analyze evenly size and characteristics of various equipment whether these reasonable, the characteristics of the equipment may be different, the production of 20 places I surveyed the facility one central timber distribution center one large scale most of the equipment.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.82-93
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• 2005

Facility layout problems (FLP) are usually treated as design problems. Lack of systematic and objective tools to compare design alternatives results in decision-making to be dominated by the experiences or preferences of designers or managers. To increase objectivity and effectiveness of decision-making in facility layout selections, a decision support model is necessary. We proposed a decision model, which regards the FLP as a multi-attribute decision making (MADM) problem. We identify sets of attributes crucial to layout selections, quantitative indices for attributes, and methods of ranking alternatives. For a requested facility layout design, many alternatives could be developed. The enormous alternatives, various attributes, and comparison of assigned qualitative values to each attribute, form a complicated decision problem. To treat facility layout selection problems as a MADM problem, we used the linear assignment method to rank before selecting those high ranks as candidates. We modelled the application of the Nemawashi process to simulate the group decision-making procedure and help efficiently achieve agreement. The electronics manufacturing service (EMS) industry has frequent and costly facility layout modifications. Our models are helpful to them. We use an electronics manufacturing service company to illustrate the decision-making process of our models.