• Journal of KIBIM
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• v.12 no.4
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• pp.1-18
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• 2022

New Fabrication Facility (FAB) construction is performed with Building Information Modeling (BIM) based design. The BIM design data keep updated during the FAB construction. To improve fast-track construction management, a Fabrication Facility Augmented Reality (FABAR) was developed. This study introduces a FABAR system development process and shows performance evaluation results of the FABAR prototype system. The FABAR is implemented with three major modules: Augmented Reality (AR) visualization unit (Room-box) to transfer big BIM data to AR data, AR registration and tracking unit to match AR with real scape and to keep AR coordination in real, and AR data management unit to enhance usability. The prototype performance results were as follows: visualization of design BIM data via AR within 24 hours, precise AR registration and tracking registration, and appropriate usability to support FAB construction management at site. The results indicate that the FABAR is applicable for FAB construction management. Especially, the BIM data transformation method using Room-box in this study signifies a new construction management approach using fluctuating BIM design data in the fast track construction condition.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.401-406
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• 1988

Various types and huge volume of information such as process instructions, work-in process and parametric data are created in a wafer fabrication process and should be provided to personnels inside or outside the facility. This article describes design criteria and functional description on the information system for small-scale wafer fabrication process to accomplish paperless fab and to support efficient fab management.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.73-80
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• 2016

This study focuses on the formation of input release lots in a semiconductor wafer fabrication facility. After the order-lot pegging process assigns lots in the fab to orders and calculates the required quantity of wafers for each product type to meet customers' orders, the decisions on the formation of input release lots should be made to minimize the production costs of the release lots. Since the number of lots being processed in the wafer fab directly is related to the productivity of the wafer fab, the input lot formation is crucial process to reduce the production costs as well as to improve the efficiency of the wafer fab. Here, the input lot formation occurs before every shift begins in the semiconductor wafer fab. When input quantities (of wafers) for product types are given from results of the order-lot pegging process, lots to be released into the wafer fab should be formed satisfying the lot size requirements. Here, the production cost of a homogeneous lot of the same type of product is less than that of a heterogeneous lot that will be split into the number of lots according to their product types after passing the branch point during the wafer fabrication process. Also, more production cost occurs if a lot becomes more heterogeneous. We developed a multi-dimensional dynamic programming algorithm for the input lot formation problem and showed how to apply the algorithm to solve the problem optimally with an example problem instance. It is necessary to reduce the number of states at each stage in the DP algorithm for practical use. Also, we can apply the proposed DP algorithm together with lot release rules such as CONWIP and UNIFORM.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.137-145
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• 2020

Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.

• Safety and Health at Work
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• v.9 no.3
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• pp.249-256
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• 2018

This article aims to provide a systematic review of the exposure assessment methods used to assign wafer fabrication (fab) workers in epidemiologic cohort studies of mortality from all causes and various cancers. Epidemiologic and exposure-assessment studies of silicon wafer fab operations in the semiconductor industry were collected through an extensive literature review of articles reported until 2017. The studies found various outcomes possibly linked to fab operations, but a clear association with the chemicals in the process was not found, possibly because of exposure assessment methodology. No study used a tiered assessment approach to identify similar exposure groups that incorporated manufacturing era, facility, fab environment, operation, job and level of exposure to individual hazardous agents. Further epidemiologic studies of fab workers are warranted with more refined exposure assessment methods incorporating both operation and job title and hazardous agents to examine the associations with cancer risk or mortality.

• Safety and Health at Work
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• v.15 no.1
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• pp.87-95
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• 2024

Background: This study focuses on assessing occupational risk for the health hazards encountered during maintenance works (MW) in semiconductor fabrication (FAB) facilities. Objectives: The objectives of this study include: 1) identifying the primary health hazards during MW in semiconductor FAB facilities; 2) reviewing the methods used in evaluating the likelihood and severity of health hazards through occupational health risk assessment (OHRA); and 3) suggesting variables for the categorization of likelihood of exposures to health hazards and the severity of health effects associated with MW in FAB facilities. Methods: A literature review was undertaken on OHRA methodology and health hazards resulting from MW in FAB facilities. Based on this review, approaches for categorizing the exposure to health hazards and the severity of health effects related to MW were recommended. Results: Maintenance workers in FAB facilities face exposure to hazards such as debris, machinery entanglement, and airborne particles laden with various chemical components. The level of engineering and administrative control measures is suggested to assess the likelihood of simultaneous chemical and dust exposure. Qualitative key factors for mixed exposure estimation during MW include the presence of safe operational protocols, the use of air-jet machines, the presence and effectiveness of local exhaust ventilation system, chamber post-purge and cooling, and proper respirator use. Using the risk (R) and hazard (H) codes of the Globally Harmonized System alongside carcinogenic, mutagenic, or reprotoxic classifications aid in categorizing health effect severity for OHRA. Conclusion: Further research is needed to apply our proposed variables in OHRA for MW in FAB facilities and subsequently validate the findings.

• Korean Journal of Computational Design and Engineering
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• v.19 no.3
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• pp.214-223
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• 2014

This paper presents a bottleneck detection framework using simulation approach in a wafer FAB (Fabrication). In a semiconductor manufacturing industry, wafer FAB facility contains various equipment and dozens kinds of wafer products. The wafer FAB has many characteristics, such as re-entrant processing flow, batch tools. The performance of a complex manufacturing system (i.e. semiconductor wafer FAB) is mainly decided by a bottleneck. This paper defines the problem of a bottleneck process and propose a simulation based framework for bottleneck detection. The bottleneck is not the viewpoint of a machine, but the viewpoint of a step with the highest WIP in its upstream buffer and severe fluctuation. In this paper, focus on the classification of bottleneck steps and then verify the steps are not in a starvation state in last, regardless of dispatching rules. By the proposed framework of this paper, the performance of a wafer FAB is improved in on-time delivery and the mean of minimum of cycle time.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.27 no.3
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• pp.187-192
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• 2017

Objectives: It is difficult to identify exposure factors in the semiconductor industry due to low exposure levels to hazardous substances and because various processes take place in fabrication (FAB). Furthermore, a single worker often experiences a variety of job histories, so it is difficult to classify similar exposure groups (SEG) in the semiconductor industry. Therefore, we intend to develop a new exposure index, the period of working in FAB, that is applicable to the semiconductor industry. Methods: First, in specifying the classification of jobs, we clearly distinguished whether they were FAB workers or non-FAB workers. We checked FAB working hours per week through questionnaires administered to FAB workers. We derived an exposure index called FAB-Year that can represent the period of working in FAB. FAB-Year is an index that can quantitatively indicate the period of working in FAB, and one FAB-Year is defined as working in FAB for 40 hours per week for one year. Results: A total of 8,453 persons were surveyed, and male engineers and female operators occupied 90% of the total. The average total years of service of the subjects was 9.7 years, and the average FAB-Year value was 6.8. This means that the FAB-working ratio occupies 70% of total years of service. The average FAB-Year value for female operators was 8.4, for male facility engineers it was 7.7, and for male process engineers it was 3.5. A FAB-Year standardization value according to personal information (gender, job group, entry year, retirement year) for the survey subjects can be calculated, and standardized estimation values can be applied to workers who are not participating in the survey, such as retirees and workers on a leave of absence (LOA). Conclusions: This study suggests an alternative method for overcoming the limitations on epidemiological study of the semiconductor industry where it is difficult to classify exposure groups by developing a new exposure index called FAB-Year. Since FAB-Year is a quantitative index, we expect that various approaches will be possible in future epidemiological studies.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.67-74
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• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.2
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• pp.202-210
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• 2015

Objectives: The purpose of this study was to examine clean room(C/R) structure, air conditioning and contamination control systems and to provide basic information for identifying a correlation between the semiconductor work environment and workers' disease. Methods: This study was conducted at 200 mm and 300 mm semiconductor wafer fabrication facilities. The C/R structure and air conditioning method were investigated using basic engineering data from documentation for C/R construction. Furthermore, contamination parameters such as airborne particles, temperature, humidity, acids, ammonia, organic compounds, and vibration in the C/R were based on the International Technology Roadmap for Semiconductors(ITRS). The properties of contamination control systems and the current status of monitoring of various contaminants in the C/R were investigated. Results: 200 mm and 300 mm wafer fabrication facilities were divided into fab(C/R) and sub fab(Plenum), and fab, clean sub fab and facility sub fab, respectively. Fresh air(FA) is supplied in the plenum or clean sub fab by the outdoor air handling unit system which purifies outdoor air. FA supply or contaminated indoor air ventilation rates in the 200 mm and 300 mm wafer fabrication facilities are approximately 10-25%. Furthermore, semiconductor clean rooms strictly controlled airborne particles(${\leq}1,000{\sharp}/ft^3$), temperature($23{\pm}0.5^{\circ}C$), humidity($45{\pm}5%$), air velocity(0.4 m/s), air change(60-80 cycles/hr), vibration(${\leq}1cm/s^2$), and differential pressure(atmospheric pressure$+1.0-2.5mmH_2O$) through air handling and contamination control systems. In addition, acids, alkali and ozone are managed at less than internal criteria by chemical filters. Conclusions: Semiconductor clean rooms can be a pleasant environment for workers as well as semiconductor devices. However, based on the precautionary principle, it may be necessary to continuously improve semiconductor processes and the work environment.