• 대한산업공학회지
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• 제26권3호
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• pp.227-237
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• 2000

A workflow management system is a software system to assist designing processes, controlling and managing the execution of the designed processes. One emerging trend in many recent information systems is the provision of process management functions. In this paper, we propose a method of designing processes for automatic process execution directly from process modeling. First of all, the concept of block is presented which is to define a nested process model. A block is the minimum unit that can specify the relationships of process components, i.e., tasks. A general process can be defined by a combination of the blocks defined in this paper. An algorithm is developed to transform a general flat process model into a nested model. We identify basic types of blocks and build ECA (Event-Condition-Action) rules for each of the basic types. This allows us to automate the execution of the process model by using the active features of active databases.

• 산업공학
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• 제20권1호
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• pp.79-86
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• 2007

In B2B e-commerce environments, many initiatives for process modeling have made efforts to design business processes correctly. Especially, Petri nets have been widely used as a good theory to design and verify process models. Therefore, we propose the process modeling method for the B2B e-commerce based on Petri nets. First of all, a B2B process model based on BPSS is represented by the UML activity diagram. Second, the activity diagram is transformed to a Petri net model. For the transformation, well-behaved building blocks/control structures and the modeling rules for inter-organizational workflow processes are proposed. Third, the process is partitioned into sharable processes for individual business partners. Finally, according to needs of individual business partners, the sharable processes are modified by well-structured refinement rules. The whole procedure is explained with the purchase process of an e-bookstore.

• 산업경영시스템학회지
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• 제35권4호
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• pp.118-125
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• 2012

When monitoring an instrumental process, one often collects a host of data such as characteristic signals sent by a sensor in short time intervals. Characteristic data of short time intervals tend to be autocorrelated. In the instrumental processes often the practice of adjusting the setting value simply based on the previous one, so-called 'adjacent point operation', becomes more critical, since in the short run the deviations are harder to detect and in the long run they have amplified consequences. Stochastic modelling using ARIMA or AR models are not readily usable here. Due to the difficulty of dealing with autocorrelated data conventional practice is resorting to choosing the time interval where autocorrelation is weak enough then to using I-MR control chart to judge the process stability. In the autocorrelated instrumental processes it appears that using the Shewhart chart and the time interval data where autocorrelation is relatively not existent turns out to be a rather convenient and very useful practice to determine the process stability. However in the autocorrelated instrumental processes we intend to show that one would presumably do better using the EWMA control chart rather than just using the Shewhart chart along with some arbitrarily intervalled data, since the former is more sensitive to shifts given appropriate weights.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 추계학술대회 논문집 Vol.16
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• pp.42-45
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• 2003

Inorganic polymer based hybrid membranes consisting of zirconium oxide and polydimethylsiloxane (PDMS) have been synthesized by sol-gel processes. The hybrid membranes showed thermal stability and flexibility up to $300^{\circ}C$. The membrane becomes proton conducting polymer electrolyte when added with 12-phosphotungstic acid (PWA). The conductivity of the membranes was measured in the temperature range from room temperature to $150^{\circ}C$ under saturated humidity and a maximum conductivity of $5{\times}10^{-5}\;Sm^{-1}$ was obtained at $150^{\circ}C$.

• 공업화학
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• 제31권5호
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• pp.520-525
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• 2020

본 연구에서는 증류공정의 제품 생산단 온도 예측을 위한 머신러닝 기반 모델을 개발하였다. 증류공정의 제어는 제품 생산단의 온도를 통해 이루어지고 있어 제어를 위해 정확한 온도 예측이 필요하다. 증류공정에서 온도는 다양한 변수들과 복잡한 비선형의 관계를 형성하고 있으며 시계열 데이터의 특성이 있어 이를 예측하기 위해 순환신경망 기반 알고리즘을 이용하였다. 모델 개발 과정에서 적절한 예측 알고리즘을 선정하기 위해 세 가지 순환신경망 기반 알고리즘과 배치 사이즈 조절하여 제품 생산단 온도를 예측하기 위한 가장 적저한 모델을 선정하였다. LSTM₁₂₈ 모델이 제품 생산단 온도를 예측하기 위한 가장 적절한 모델로 선정되었다. 선정된 모델을 활용하여 실제 공정 운전데이터에 적용한 결과 RMSE 0.0791, R² 0.924의 성능을 보였다.

• 전기전자학회논문지
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• 제25권3호
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• pp.548-555
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• 2021

본 논문에서는 산업 공정, 설비 및 모터 드라이브에 적용되는 고장 진단 및 고장 허용 제어 기술의 기본 개념, 접근법과 연구 동향에 대해서 개괄적으로 기술하였다. 산업 공정을 위한 고장 진단의 주요 역할은 공정의 결함 상태를 파악할 수 있는 효과적인 지표를 만든 후 고장이나 위험한 사고에 대해 적절한 조치를 취하는 것이다. 산업 공정에 패턴이 있는지 특정 프로세스 변수가 정상적으로 동작하는지 확인하기 위해 많은 고장 검출 및 진단 기법이 개발되었다. 먼저 본 논문에서는 데이터 기반 기법과 모델 기반 기법에 대하여 살펴본다. 두 번째로 산업 공정을 위한 고장 검출 및 진단 기법을 살펴본다. 세 번째로 수동형 및 능동형 고장 허용 제어 기법을 살펴본다. 마지막으로 AC 모터 드라이브에서 발생하는 주요 고장을 열거, 그 특성을 살펴보고 이를 위한 고장 진단 및 고장 허용 제어 기술을 살펴본다.

• 공업화학
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• 제31권6호
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• pp.660-667
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• 2020

본 연구의 대상은 에폭시 레진 생산 공정으로 155 ℃ 이상의 고온 스팀을 열원으로 사용하고 있으며 공정에서 생성되는 응축수는 전량 버려지고 있다. 공정의 일부는 70 ℃ 이하의 저온으로 운전되므로 버려지는 응축수를 재활용하여 저온 공정의 열원으로 사용한다면 스팀 사용량 저감이 가능하다. 따라서 본 연구에서는 응축수 재활용을 통해 폐열을 회수하여 스팀 사용량을 저감할 수 있는 공정을 제시하고 모델을 개발하였다. 최적의 응축수 재활용 공정을 찾기 위한 사례연구를 진행하였고, 각 사례의 연간 자본 비용 및 스팀 저감 비용을 비교하여 경제성 평가를 실시하였다. 제안된 공정에서 응축수 회수를 통해 저온 공정에 사용하는 스팀 사용량을 연간 최대 67.6%까지 저감하여 최대 연 522.1 백만원의 추가 수익의 확보가 가능함을 확인하였다.

• 신재생에너지
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• 제2권2호
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• pp.102-107
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• 2006

In Japan, research and development were undertaken on gas hydrate-side industrial processes associated with power generation system connections that may particularly be necessary to develop gas hydrated technology-based industrial systems. In so doing, data and engineering technologies useful n formulating guidelines on design of practical process were accumulated. In addition, basic research into theoretical evidence were carried out to promote and support the development of technological elements for those processes. In basic research designed to promote and support the research and development of elemental technologies, microanalyses were conducted to understand the decomposition mechanism of mixed gas hydrate. Moreover, measurement technologies that can be applied in industrial processes, such as numerical analyses and concentration measurement, were examined. Japan has developed a highly efficient gas hydrate formation process using micro-bubbles with a tubular reactor. Higher formation rate over conventional systems has been obtained by the process. As mentioned above, the technical problems were clarified and the economics were studied from a view point of the NGH technology in this study. The results can be applied for utilization and must contribute to popularization of gas hydrate production.

• 산업공학
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• 제18권3호
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• pp.221-233
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• 2005

e-Manufacturing can be referred to as a system methodology enabling the integration of manufacturing operations and IT technologies to achieve objectives of an enterprise. It is recently regarded as a powerful solution to survive in a chaotic marketplace. While conducting an e-Manufacturing project, we first needed to capture collaborative processes conducted by multiple participants in order to define functions of a system supporting them. However, pervasive process modeling techniques including IDEF3, Petri nets, and UML are not sufficient for modeling collaborative processes. Therefore, we first briefly investigate several process modeling methods including aforementioned modeling methods and ARIS focusing on the collaboration point of view. Then, we propose a new modeling method referred to as Collaborative Process Modeling (CPM) to clearly describe collaborative processes. Also, we develop and illustrate a rule for transforming collaborative process models into Marked Graph models to use the analysis power of the Petri nets. Using CPM empowers us to develop collaborative process models with simple notations, understand and facilitate the realization of the collaboration, and verify models before rushing into the development.

• 대한산업공학회지
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• 제41권6호
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• pp.579-587
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• 2015

Semiconductor manufacturing industry is a high density integration industry because it generates a vest number of data that takes about 300~400 processes that is supervised by numerous production parameters. It is asked of engineers to understand the correlation between different stages of the manufacturing process which is crucial in reducing production costs. With complex manufacturing processes, and defect processing time being the main cause. In the past, it was possible to grasp the corelation among manufacturing process stages through the engineer's domain knowledge. However, It is impossible to understand the corelation among manufacturing processes nowadays due to high density integration in current semiconductor manufacturing. in this paper we propose a canonical correlation analysis (CCA) using both wafer test voltage variables and fail bit counts variables. using the method we suggested, we can increase the semiconductor yield which is the result of the package test.