• 제목/요약/키워드: Smart Factory Quality Characteristics

검색결과 12건 처리시간 0.022초

Effects of Smart Factory Quality Characteristics & Innovative Activities on Business Performance : Mediating Effect of Using Smart Factory

  • CHO, Ik-Jun;KIM, Jin-Kwon;AHN, Tony-DongHui;YANG, Hoe-Chang
    • 융합경영연구
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    • 제8권3호
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    • pp.23-36
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    • 2020
  • Purpose: The purpose of this study is to identify the strategic direction of organizations and their employees to efficiently utilize smart factories and enhance business performance among Korean manufacturing companies. Research design, data, and methodology: We derived a structured research model to check the mediated effect of utilization of smart factory between the characteristics of smart factory and the innovation activities. Results: Quality characteristics of smart factory and Innovation activities were all found to have a statistically significant effect on utilization of smart factory, utilization of smart factory was found to have a statistically significant effect on the business performance. And it has been shown that the utilization of smart factory is partially mediated relative to the quality characteristics of smart factory and business performance and relative to innovation activities and business performance. Conclusions: Smart factory builders can reflect the areas that affect utilization of the smart factory in their strategies by considering the quality characteristics of the smart factory and innovation Activities. Therefore, smart factory builders can identify the quality characteristics of smart factory and reflect them in the process and analyze active utilize measures through the innovative activities of the employees of the organization, thereby influencing business performance.

Effects of Smart Factory Quality Characteristics and Dynamic Capabilities on Business Performance: Mediating Effect of Recognition Response

  • CHO, Ik-Jun;KIM, Jin-Kwon;YANG, Hoe-Chang;AHN, Tony-DongHui
    • 산경연구논집
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    • 제11권12호
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    • pp.17-28
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    • 2020
  • Purpose: The purpose of this study is to confirm the strategic direction of the firm regarding the capabilities of the organization and its employees in order to increase the utilization and business performance of employees by that introduce smart factories in the domestic manufacturing industry. Research design, data, and methodology: This study derived a structured research model to confirm the mediating effect of recognition responses between the quality characteristics of smart factories and dynamic capabilities. For the analysis, a total of 143 valid questionnaires were used for 200 companies that introduced smart factories from domestic SME's. Results: Quality Characteristics of Smart Factory and Dynamic Capabilities had a statistically significant effect on Usefulness. Recognition Response had a statistically mediating on the relationship between quality characteristics of smart factory and business performance. Recognition Response had a statistically significant effect on business performance. Conclusions: It suggests that firms introducing smart factory reflect them in their empowerment strategic because the recognition responses of its employees differ according to the quality characteristics and dynamic capabilities of smart factories. It also means that the information derived from the smart factory system is useful and effective to business performance and employees.

제조업 특성을 반영한 스마트공장 진단모델 개발 및 중소기업 맞춤형 적용사례 (Development of Smart Factory Diagnostic Model Reflecting Manufacturing Characteristics and Customized Application of Small and Medium Enterprises)

  • 김현득;김동민;이경근;윤제환;염세경
    • 산업경영시스템학회지
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    • 제42권3호
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    • pp.25-38
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    • 2019
  • This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

4차 산업혁명시대의 스마트 팩토리 구축을 위한 품질전략 (Quality Strategy for Building a Smart Factory in the Fourth Industrial Revolution)

  • 정혜란;배경한;이민구;권혁무;홍성훈
    • 품질경영학회지
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    • 제48권1호
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    • pp.87-105
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    • 2020
  • Purpose: This paper aims to propose a practical strategy for smart factories and a step-by-step quality strategy according to the maturity of smart factory construction. Methods: The characteristics, compositional requirements, and diagnosis system are examined for smart factories through theoretical considerations. Several cases of implementing smart factory are studied considering the company maturity level from the aspect of the smartness concept. And specific quality techniques and innovation activities are carefully reviewed. Results: The maturity level of smart factory was classified into five phases: 1) ICT non-application, 2) basic, 3) intermediate 1, 4) intermediate 2, 5) advanced level. A five-step quality strategy was established on the basis of case studies; identify, measure, analyze, optimize, and customize. Some quality techniques are introduced for step-by-step implementation of quality strategies. Conclusion: To build a successful smart factory, it is necessary to establish a quality strategy that suits the culture and size of the company. The quality management strategy proposed in this paper is expected to contribute to the establishment of appropriate strategies for the size and purpose of the company.

4차 산업혁명시대 지역 중소기업의 제조혁신 한계와 스마트공장 정책 방향성 연구: 포항지역 중소기업의 스마트공장 조사를 중심으로 (A Study on the Limits of Manufacturing Innovation and Policy Direction of SMEs in the 4th Industrial Revolution : Focusing on the Limitations and Examples of Pohang SME's Smart Factory Introduction)

  • 김은영;박문수
    • 과학기술학연구
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    • 제18권2호
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    • pp.269-306
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    • 2018
  • 포항시는 철강업 등의 일부 제조업에 영향을 크게 받는 우리나라의 대표적인 기업도시이다. 이러한 대기업 중심 기업도시의 모델은 우리나라 제조업 발전의 중요한 바로미터가 되어 왔다. 하지만 최근 경기침체와 위기가 확대되고 있는 상황에서 제조 한계 극복의 방안으로 논의되고 있는 보급 상황과 방향에 대한 포항 차원의 논의를 진행해 보고자 한다. 본 연구를 통해 첫째 현재의 스마트 공장 구축의 현황과 포항지역의 산업적 여건 그리고 추진 분야에 대한 검토 두 번째, 지역 기업들의 설문 자료를 통해 산업구조 고도화와 효율성을 위한 함의점과 차세대 생산혁명에 대비한 지역차원의 준비와 산업적 측면에서의 변화를 준비하고자 한다. 이러한 현황 분석과 기업 조사를 통해 다음과 같은 포항 지역 스마트공장 지원의 정책 대안을 새롭게 제시하고자 한다. 첫째, 포항시가 경북도 등 광역지자체와 협력하여 지역 특화형 스마트공장 지원 플랜을 구축할 필요가 있다. 둘째, 포항시 기업협의체, 업종별 협동조합 등 기업 중간조직이 업종별 특성에 맞는 스마트공장을 업계 자발적으로 개발하고 이를 보급하는 방식으로 전환할 필요가 있다. 셋째, 스마트공장 보급에서 가장 중요한 행위자는 스마트공장 IT 솔루션 공급사로 지역 중소기업간 연계 및 협력 강화가 중요하다. 현재의 포항 지역의 산업특성상 대기업과의 협력을 통한 공급가치사슬을 고려한 스마트공장 지원 프로그램의 마련이 구체화되어야 한다.

의류기업의 품질 개선 방안 연구: Quality 4.0 매트릭스를 활용한 쿠트스마트 사례 (A Study on Improving the Quality of Clothing Companies: Focusing on Kutesmart using Quality 4.0 Matrix)

  • 장진명;서승주;이윤아;김연성
    • 품질경영학회지
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    • 제47권1호
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    • pp.199-211
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    • 2019
  • Purpose: The concept of quality is changing in the quality 4.0 era with the fourth industrial revolution in the world. This research aims to understand the characteristics of well-adapted companies against the quality 4.0 era and to improve the quality of clothing companies. Methods: We analyzed companies that responded well to the quality 4.0 era, especially Kutesmart using Quality 4.0 Matrix. We focused on the service process of Kutesmart and we suggested modified service process to improve quality. We also interviewed an expert to verify this process is valid. Results: We found that two types are classified of well-adapted companies against the quality 4.0 era. Especially, Kutesmart has built a smart factory and introduced new technologies like 3D scanner and big data analysis. However, Kutesmart has a weakness in post-purchase process like other clothing companies. Kutesmart could solve this problem with modular production method for damaged part of customer. Conclusion: This research can be used for better understanding of the characteristics of well-adapted companies against the quality 4.0 era and service process of Kutesmart that is custom clothing company for providing information for benchmarking in this industry. This study suggests that further empirical researches on the costs and the efficiencies of applying the new technologies are necessary.

임시교실용 모듈러 건축물의 품질기준 마련을 위한 특성비교 (Comparison of Characteristics for Establishing Quality Standards of Modular Buildings for Temporary Classrooms)

  • 이종성;박재웅;임군수;김종;한민철;한천구
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2023년도 봄 학술논문 발표대회
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    • pp.83-84
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    • 2023
  • Wall structure smart modular is a building construction method where modules are manufactured in a factory and assembled on-site. This method is gaining popularity in the construction industry as it reduces construction time and mitigates risks such as material supply and labor costs. Wall structure smart modular is necessary as it provides comfortable temporary classroom space during renovation and remodeling of aging school buildings. The structure and characteristics of each type of temporary classroom modular were compared, and wall structure modular showed superior performance in terms of height and weight competitiveness compared to mixed structures. With these advantages, wall structure modular can ensure economic efficiency and recyclability as a temporary classroom. In the future, we aim to compare and analyze the standards such as inter-floor noise and heat transfer coefficient for wall structure and mixed structures.

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질화포텐셜 제어 가스질화로 개발(I) : 제어질화 및 국내 기술 현황 (Development of Controlled Gas Nitriding Furnace : Controlled Gas Nitriding Technology and Present Situation in Korea)

  • 이원범;손석원
    • 열처리공학회지
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    • 제36권1호
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    • pp.40-46
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    • 2023
  • Controlled nitriding is a technology that controls the nitriding potential based on the gas partial pressure received through an IOT-based sensor. Controlled nitriding is characterized by easy control of the phase of the nitride compound and excellent reproducibility of quality. In particular, it is possible to form a compound layer of excellent quality with fewer pores on the surface. However, despite these advantages, the application of controlled nitriding still needs to be improved in Korea. This paper explains the characteristics of controlled nitriding and describes the future direction and the problems of controlled nitriding in Korea.

연결형 산업단지(CIPs): 한국의 스마트공장 구축을 위한 연결형 산업단지 아키텍처 (Connected-IPs: A Novel Connected Industrial Parks Architecture for Building Smart Factory in Korea)

  • 양영철;정종필
    • 한국인터넷방송통신학회논문지
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    • 제18권4호
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    • pp.131-142
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    • 2018
  • 한국에서 지난 50여년간 산업단지는 국가주력산업의 집적지로 경제성장에 있어 중요한 역할을 담당하였으나 이러한 노후산업단지가 가지고 있는 다양한 문제점으로 인하여 경쟁력 약화 요인으로 작용하고 있다 산업단지 유형 특성별 발전계획, 관리계획, 지원계획 등으로 구분하여 융복합 첨단산업단지로의 관리 육성을 위한 모델로 전환될 필요가 있다 이를 위하여 IoT를 기반으로 하는 클라우드 컴퓨팅, RFID, WSN, CPS, 빅데이터 분석 등의 신기술을 활용한 CIPs(Connected-Industrial parks)를 제안한다 이것은 각 CIP가 연결되어 확장된 개념으로서 물리적 자산을 소유, 운용하면서 운송, 창고, 제조 영역에서 다양한 서비스를 지원하는 허브라고 할 수 있다 이러한 CIPs를 통해서 네트워크형 협업 제조가 가능하고 지능형 물류 혁신으로 원가 절감, 납기단축, 품질향상 등을 달성하여 국가경쟁력의 혁신을 이룰 수 있을 것이다.

Deep Learning-based Rheometer Quality Inspection Model Using Temporal and Spatial Characteristics

  • Jaehyun Park;Yonghun Jang;Bok-Dong Lee;Myung-Sub Lee
    • 한국컴퓨터정보학회논문지
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    • 제28권11호
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    • pp.43-52
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    • 2023
  • 고무생산업체에서 생산된 고무는 레오미터 측정을 통해 품질 적합성 검사가 이루어진 후, 자동차 부품을 위한 2차 가공으로 이어진다. 그러나 레오미터 검사는 인간에 의해 진행되고 있으며, 숙련된 작업자에게 매우 의존적이라는 단점이 존재한다. 이러한 문제점을 해결하기 위해 본 논문에서는 딥러닝 기반 레오미터 품질 검사 시스템을 제안한다. 제안된 시스템은 레오미터의 시간적, 공간적 특성을 활용하기 위해 LSTM과 CNN을 조합하였고, 각 고무의 배합재료를 보조(Auxiliary) 데이터 입력으로 사용해 하나의 모델에서 다양한 고무 제품의 품질 적합성 검사가 가능하도록 구현하였다. 제안된 기법은 30,000개의 데이터셋으로 그 성능을 학습 및 검사하였으며, 평균 f1-점수를 0.9942 달성하여 그 우수성을 증명하였다.