• 디지털산업정보학회논문지
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• 제12권1호
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• pp.1-12
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• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• 한국융합학회논문지
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• 제11권3호
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• pp.9-18
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• 2020

최근 4차 산업혁명 이슈가 부상하게 됨에 따라, 정부와 산업계에서는 스마트공장에 대한 관심이 증가하고 있다. 이에 정부에서는 스마트공장에 대한 정책지원을 제공하여 국내 중소·중견기업의 스마트 제조역량 구축을 유도하고 있다. 그러나 이러한 정책적 지원의 효과성이나 기업들의 만족도에 대해서는 거의 알려진 것이 없다. 이에 본 연구에서는 Kano 모델과 고객만족개선지수를 활용하여 스마트공장 지원정책의 요소별 기업들의 만족도를 분석하고 정책지원의 우선순위를 도출하고자 하였다. 연구 결과 총 11개 품질요소 중 8개가 일원적 품질요소, 3개는 매력적 품질요소였다. 또한 자금지원의 우선순위가 가장 높았으며, 외부전문가 파견, 고도화준비 컨설팅, 유지보수 관련 컨설팅 등도 순위가 높았다. 이러한 결과는 기업들이 스마트공장의 도입이나 기초수준 구축 정도의 지원보다는 유지보수와 고도화에 대한 지원을 더 많이 요구하고 있음을 시사한다.

• 한국컴퓨터정보학회논문지
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• 제24권5호
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• pp.49-58
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• 2019

In this paper, we propose an edge cloud platform architecture for implementing smart factory. The edge cloud platform is one of edge computing architecture which is mainly focusing on the efficient computing between IoT devices and central cloud. So far, edge computing has put emphasis on reducing latency, bandwidth and computing cost in areas like smart homes and self-driving cars. On the other hand, in this paper, we suggest not only common functional architecture of edge system but also light weight cloud based architecture to apply to the specialized requirements of smart factory. Cloud based edge architecture has many advantages in terms of scalability and reliability of resources and operation of various independent edge functions compare to typical edge system architecture. To make sure the availability of edge cloud platform in smart factory, we also analyze requirements of smart factory edge. We redefine requirements from a 4M1E(man, machine, material, method, element) perspective which are essentially needed to be digitalized and intelligent for physical operation of smart factory. Based on these requirements, we suggest layered(IoT Gateway, Edge Cloud, Central Cloud) application and data architecture. we also propose edge cloud platform architecture using lightweight container virtualization technology. Finally, we validate its implementation effects with case study. we apply proposed edge cloud architecture to the real manufacturing process and compare to existing equipment engineering system. As a result, we prove that the response performance of the proposed approach was improved by 84 to 92% better than existing method.

• 한국정보통신학회논문지
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• 제25권1호
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• pp.124-133
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• 2021

스마트팩토리는 공장 내 장비에 센서를 부착하여 각종 데이터를 실시간으로 수집, 분석 및 모니터링함으로써 스스로 공정을 제어 및 통제하는 미래형 공장이다. 스마트팩토리에서 장비의 상태 및 이력을 현장에서 실시간으로 조회 및 생성하는 것은 매우 중요한 일이며 다양한 스마트 기기의 등장은 이것을 보다 효율적으로 수행할 수 있게 하고 있다. 본 논문은 실시간으로 장비의 상태 및 이력을 생성, 조회, 삭제 할 수 있는 다중장치 기반 시스템을 제안한다. 제안 시스템은 공장이라는 특수한 환경을 고려하여 안드로이드 시스템과 스마트 글래스 시스템을 동시에 사용한다. 스마트 글래스 시스템은 장비 인식을 위해 QR코드를 이용하였으며 음성 인식 기능을 이용하여 보다 효율적인 작업환경을 제공한다. 다중장치기반 실시간 장비 모니터링을 위한 시스템 구조를 설계하였으며 안드로이드 시스템, 스마트 글래스 시스템 및 웹 애플리케이션 서버를 구현함으로써 실용성을 보이겠다.

• Journal of Information Technology Applications and Management
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• 제28권4호
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• pp.45-57
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• 2021

This research explores how the success of smart factory adoption is influenced by firm's dynamic capability. This research describes the underlying processes on how organizations manipulate or adapt organizational elements harmoniously to implement smart factory successfully. Although understanding of these processes is essential to many researchers and practitioners in the field, the information system research literature contains very few examples of this type. The research is conducted in the following sequence: first, the concept of dynamic capability is presented followed by research methodology; and then the analyses of case data are presented followed by discussions and future directions. The results of this research show that the firms with higher dynamic capability adopted smart factory more easily through alignment of various organizational elements.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1071-1082
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• 2021

Since the smart factory has been recently recognized as an industrial core requirement, various mechanisms to ensure efficient and stable operation have attracted much attention. This attention is based on the fact that in a smart factory environment where operating processes, such as facility control, data collection, and decision making are automated, the disruption of processes due to problems such as facility anomalies causes considerable losses. Although many studies have considered methods to prevent such losses, few have investigated how to effectively apply the solutions. This study proposes a Kubernetes based system applied in a smart factory providing effective operation and facility management. To develop the system, we employed a useful and popular open source project, and adopted deep learning based anomaly detection model for multi-sensor anomaly detection. This can be easily modified without interruption by changing the container image for inference. Through experiments, we have verified that the proposed method can provide system stability through nondisruptive maintenance, monitoring and non-disruptive updates for anomaly detection models.

• 전기학회논문지
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• 제63권12호
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• pp.1627-1636
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• 2014

In real-time electricity price environment, the energy management system can provide the significant advantage to the residential, commercial and industrial customers since it can reduce the electricity charge by controlling the load operation effectively in response to time-varying price. However, the earlier studies for load management mainly focus on the residential and commercial customers except for the industrial customers because most of load operations in industrial sector are intimately related with production schedule. So, it is possible that the inappropriate control of loads in industrial sector causes huge economic loss. In this paper, therefore, we propose load control algorithm for factory energy management system(F-EMS) to achieve not only minimizing the electricity charges but also maintaining production efficiency by considering characteristics of load operation and production schedule. Considering characteristics of load operation and production schedule, the proposed load control algorithm can reflect the various characteristics of specific industrial customer and control their loads within the range that the production efficiency is maintained. Simulation results show that the proposed load control algorithm for F-EMS leads to significant reduction in the electricity charges and peak power in industrial sector.

• Journal of the Korean Data and Information Science Society
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• 제10권1호
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• pp.251-259
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• 1999

본 연구에서는 사출공장의 생산관리를 위한 정보시스템 구축사례를 소개한다. 제품의 효율적인 생산을 위해서는 영업과 수주에서부터 원청업체에 납품할 때까지의 전 생산과정과 관련된 정보를 체계적으로 관리하는 것이 필요하다. 이에 본 연구에서는 사출공장을 대상으로 수주, 생산, 납품, 재고 등과 관련된 전 정보를 체계적으로 관리하여, 생산 계획 및 현황의 관리와 이에 연계된 영업, 구매, 총무, 납품 등의 관리가 원활하고 효율적으로 이루어질 수 있도록 하는 통합 생산정보시스템을 구축한다.

• International Journal of Quality Innovation
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• 제8권1호
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• pp.137-153
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• 2007

Failure mode and effects analysis (FMEA) is a preventive technique in reliability management field. The successful implementation of FMEA technique can avoid or reduce the probability of system failure and achieve good product quality. The FMEA technique had applied in vest scopes which include aerospace, automatic, electronic, mechanic and service industry. The marking process is one of the back ends testing process that is the final process in semiconductor process. The marking process failure can cause bad final product quality and return although is not a primary process. So, how to improve the quality of marking process is one of important production job for semiconductor testing factory. This research firstly implements FMEA technique in laser marking process improvement on semiconductor testing factory and finds out which subsystem has priority failure risk. Secondly, a CCD position solution for priority failure risk subsystem is provided and evaluated. According analysis result, FMEA and CCD position implementation solution for laser marking process improvement can increase yield rate and reduce production cost. Implementation method of this research can provide semiconductor testing factory for reference in laser marking process improvement.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.411-414
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• 2015

The purpose of this study is to conduct a comparative analysis between Korea and the United States of the supply process of unit modular housing at both the factory production phase and the transportation and lifting phase, as part of an attempt to invigorate the unit modular housing market in Korea. Unlike the practice in the United States, one of Korea's unique characteristics is that the floor is constructed with reinforced concrete and hot water heating system. To do this, the wet method in Korea is used that includes concrete placement, curing and constructing hot water floor heating system at the factory production phase, which results in a longer production time and also requires the lifting of heavier loads. In the United States, interior and exterior finishing works of modular housing are performed by different companies, and the distance between the unit module factory and the construction site is quite far. This kind of dualized production structure may cause confusion when it comes to schedule management, procurement management, and stock management. Moreover, problems caused by external environmental factors such as wind and rainfall were reported in the course of long-distance transportation. The results of this case comparison are expected to provide fundamental data that will reduce the amount of trial and error in the unit module production, transportation and lifting work in Korea, which has a comparatively small number of unit modular housing cases.