• 제목/요약/키워드: Smart factory level

검색결과 79건 처리시간 0.024초

6-도메인 스마트팩토리 성숙도 평가 모델 기반 도입기업 군집분석 (Cluster analysis of companies introducing smart factory based on 6-domain smart factory maturity assessment model)

  • 정도현;안정현;최상현
    • 한국융합학회논문지
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    • 제11권9호
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    • pp.219-227
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    • 2020
  • 스마트팩토리는 가장 빠르게 발전하고 변화하는 4차 산업혁명 분야 중 하나이다. 스마트팩토리에서 도입정도와 성숙도 수준 평가는 중요한 부분에 해당한다. 본 논문에서는 국내 스마트팩토리를 도입한 중소기업들을 대상으로 설문 조사를 진행한 데이터를 바탕으로 스마트팩토리 도입 현황과 새로운 성숙도 평가 모델 기반 군집분석을 진행하였다. 설문에 응한 스마트팩토리 도입 기업의 약 68% 기업들이 기초수준에 해당하였고, 21% 정도만이 중간1 수준이었다. 대다수 중소기업들이 중간1로 진입하지 못한 가장 큰 이유로 자금부족을 꼽았다. 군집분석 결과, 군집별 패턴은 유사하지만 정도의 차이에 따라 '상, 중, 하' 3개로 군집됨을 확인할 수 있었고, 6 도메인 중 프로세스가 상대적으로 성숙도가 가장 높았고, 데이터가 가장 낮은 수준을 보였다. 이를 통해 6개 도메인 기반 새로운 스마트팩토리 성숙도 평가 모델을 활용하여, 보다 구체적이고 정량적인 성숙도 수준 측정 및 분석이 가능함을 보였다.

인더스트리 4.0시대의 스마트 팩토리 성공 사례 분석: 국내 대·중·소기업을 대상으로 (Analysis on Success Cases of Smart Factory in Korea: Leveraging from Large, Medium, and Small Size Enterprises)

  • 박종필
    • 디지털융복합연구
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    • 제15권5호
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    • pp.107-115
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    • 2017
  • 최근 스마트 팩토리에 대한 관심이 크게 증가하고 있다. 그러나, 이러한 높은 관심에도 불구하고 정작 어떻게 스마트 팩토리를 구축해야 하는지에 대한 구체적인 가이드라인이 없는 실정이다. 또한 기존의 사례들은 주로 독일을 중심으로한 해외 사례로서 국내에 그대로 적용하기에는 다소의 괴리감이 존재한다. 또한 스마트 팩토리는 기업의 규모와 성격에 따라 구축방식이 상이할 수 있다. 이러한 상황에서 본 연구는 국내 대 중 소기업들을 대상으로 스마트 팩토리 성공구축 사례들을 분석 하였다. 사례분석 결과, 대기업의 경우 일부공장을 대상으로 시범적으로 스마트팩토리를 구축한 후 성공적으로 평가될 시 전체공장으로 확대시키는 전략이 효과적이다. 중소기업의 경우, 낮은 수준의 스마트팩토리 구축레벨에서 높은 수준의 구축레벨로 업그레이드하는 것이 효과적이다. 말하자면 본 연구에서 실시한 스마트 팩토리 성공사례 분석을 통해, 기업들에게 성공적 구축을 위한 실제적인 가이드라인을 제공하고자 한다. 아울러, 본 연구를 통해 제시된 구축전략들은 향후 스마트 팩토리 구축을 고려하고 있는 기업과 정부에게 중요한 함의를 제시하고자 한다.

Factors that Drive the Adoption of Smart Factory Solutions by SMEs

  • Namjae Cho;Soo Mi Moon
    • Journal of Information Technology Applications and Management
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    • 제30권5호
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    • pp.41-57
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    • 2023
  • This paper aims to analyse the factors influencing the implementation of smart factories and their performance after implementation, using the grounded theory analysis method based on interview data. The research subjects were 21 companies that were selected by the Smart Manufacturing Innovation Promotion Group under the SME Technology Information Promotion Agency in 2020-2021 as the best case smart factory implementation companies, and introduced the intermediate stage 1 or above. A total of 87 concepts were generated as a result of the analysis. We were able to classify them into 16 detailed categories, and finally derived six broad categories. These six categories are "motivation for adoption", "adoption context", "adoption level", "technology adoption", "usage effect" and "management effect". As a result of the overall structure analysis, it was found that the adoption level of smart factory is determined by the adoption motivation, the IT technology experience affects the adoption level, the adoption level determines the usage and usage satisfaction, internal and external training affects the usage and usage satisfaction, and the performance or results obtained by the usage and usage are reduced defect rate, improved delivery rate and improved productivity. This study was able to derive detailed variables of environmental factors and technical characteristics that affect the adoption of smart factories, and explore the effects on the usage effects and management effects according to the level of adoption. Through this study, it is possible to suggest the direction of adoption according to the characteristics of SMEs that want to adopt smart factories.

스마트 서비스 시스템 기반 스마트 팩토리 아키텍처 설계 (Smart Service System-based Architecture Design of Smart Factory)

  • 이희제;이중윤
    • 시스템엔지니어링학술지
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    • 제13권2호
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    • pp.57-64
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    • 2017
  • A new paradigm based on distributed manufacturing services is emerging. This paradigm shift can be realized by smart functions and smart technologies such as Cyber Physical System (CPS), Artificial Intelligence (AI), and Cloud Computing. Most architectures define stack levels from Level 0 (equipment) to Level 4 (business area) and specify the services to be provided between them. Because of their a rough technical specification, there is a limitation on how to actually utilize a technology to actually implement a smart factory service with this architecture. In this paper, we propose a smart factory architecture that can be utilized directly from the perspective of a smart service system by making the use of System Engineering Process and System Modeling Language (SysML).

The Effect of UTAUT, Dynamic Capabilities, Utilization of Smart Factory on the Intention to Continue Using: Technology Perception Moderating Effect

  • Jin-Kwon KIM;Kyung-Soo LEE
    • 융합경영연구
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    • 제11권6호
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    • pp.43-55
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    • 2023
  • Purpose: The purpose of this study was to identify the relationship between smart factory utilization and continued use intention between UTAUT, dynamic capabilities of smart factory construction companies and present the company's strategic direction. Research design, data, and methodology: In this study, a structured research model was derived to confirm the relationship between UTAUT, dynamic capabilities, smart factory utilization and continued use intention and the difference according to Technology perception. For analysis a total of 223 valid questionnaires from e-commerce users were used. Confirmatory factor analysis, correlation analysis, and structural equations were conducted to verify. Results: Both UTAUT, dynamic capabilities had a significant effect on smart factory utilization as well as continued use intention. It was found that the relationship between UTAUT, dynamic capabilities, smart factory utilization, and continued use intention. differed depending on the technology perception. Conclusions: Organizational members utilize the smart factory in anticipation of effects such as work performance and various improvements. Smart factory data will be used continuously when it is useful for business processes and operations. It is necessary to establish strategies and provide training to improve the technical level and capabilities of organizational members. Through this, a strategy is needed that can be continuously used by utilizing the information obtained through smart factory to improve work efficiency, productivity and efficiency increase is needed

스마트 팩토리의 전략적 활용 연구: 구축 목적 및 내용이 지속적 활용에 미치는 영향 (A Study on Strategic Utilization of Smart Factory: Effects of Building Purposes and Contents on Continuous Utilization)

  • 오주환;김지대
    • 중소기업연구
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    • 제41권4호
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    • pp.1-36
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    • 2019
  • 본 연구의 목적은 스마트 팩토리의 전략적 활용을 위한 스마트 팩토리 구축 목적 - 스마트 팩토리 구축내용 - 스마트 팩토리 지속적 활용 간의 관계를 파악하는 것이다. 구체적으로 본 연구는 스마트 팩토리 구축 목적을 두 가지 요인 - (1) 생산성 향상, (2) 유연성 향상 - 으로 구분하고, 이들 각각이 다음의 3가지 측면의 스마트 팩토리 구축내용 - (1) 자동화 영역(설비 자동화, 업무 자동화), (2) 제조 빅데이터 기술 활용영역(생산 프로세스의 재구축을 위한 제조 빅데이터 활용, 생산 프로세스의 점진적 개선을 위한 제조 빅데이터 활용), 그리고 (3) 가치사슬 통합 범위(내부통합, 외부통합) - 에 미치는 영향을 파악하고, 이어서 본 연구는 스마트 팩토리 구축 내용이 스마트 팩토리 지속적 활용에 미치는 영향을 조사하였다. 또한, 기업규모에 따라 스마트 팩토리 구축 목적 - 스마트 팩토리 구축 내용 - 스마트 팩토리의 지속적 활용 간의 관계가 어떻게 달라지는 지를 살펴보았다. 본 연구의 실증분석은 총 151개의 표본기업들을 대상으로 하였다. 표본기업들의 구성은 중소기업 100개사와 대기업 51개사로 구성되었다. 이의 분석결과는 다음과 같다. 첫째, 생산성 및 유연성 향상이라는 스마트 팩토리 구축 목적은 스마트 팩토리의 모든 구축 내용 변수들에 긍정적 영향을 주었다. 둘째, 스마트 팩토리 구축 내용들로서 설비 자동화, 업무 자동화, 생산 프로세스의 재구축을 위한 제조 빅데이터 활용, 내부 가치사슬 통합, 외부 가치사슬 통합은 스마트 팩토리의 지속적 활용에 긍정적 영향을 주었다. 셋째, 스마트 팩토리 구축 목적이 스마트 팩토리 구축 내용에 미치는 영향은 구축 목적이 생산성 향상이냐 혹은 유연성 향상이냐에 따라 차이가 있음을 확인할 수 있었다. 넷째, 기업규모에 따른 조절효과 분석 결과 기업규모에 따라서 스마트 팩토리의 구축 목적과 구축 내용 간에 차이가 있는 것으로 나타났다.

Promoting Efficient Smart Factories through Analysis and Status of Corporate Infrastructure Configuration

  • Seong-Hoon Lee
    • International Journal of Internet, Broadcasting and Communication
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    • 제16권3호
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    • pp.274-280
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    • 2024
  • The smart factory promotion project is a project that improves the entire management environment system, including the production process, using ICT technology. According to the 2019 Smart Factory Survey and Analysis Research Report of the Ministry of SMEs and Startups, small and medium-sized enterprises that introduced smart factories reported positive effects such as increased productivity, improved quality, and reduced costs on average. On the other hand, the survey results of companies that promoted the project despite positive results showed that there was room for improvement. This study dealt with the contents of the survey conducted on companies by the smart factory promotion agency in 2020 regarding the infrastructure configuration for promoting smart factories. We examined the meaningful contents implied by the data related to the infrastructure configuration. These meaningful survey results can lead to more efficient business promotion in the future when promoting smart factory projects.

스마트 공장 문헌연구 및 향후 추진전략 (Smart Factory Literature Review and Strategies for Korean Small Manufacturing Firms)

  • 이성희;김재영;이원희
    • Journal of Information Technology Applications and Management
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    • 제24권4호
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    • pp.133-152
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    • 2017
  • Smart factory has been regarded as a big opportunity for manufacturing industries. However, little literature has been studied for the current status of Korean smart factory. Our paper tries to find gaps between research and real world by summarizing the recent literature and cases in Korean context. As the present level of smart factory introductions in Korean small manufacturing firms is lower than what a variety of literature says, our study points out that more efforts, investments and government support are required to catch up with the knowhow and technologies of developed countries although real-time control, enhanced productivity have been obtained. In future research, we will continue the smart factory study with the accumulated real data.

대·중소 상생형 스마트공장 구축 지원 사업 도입기업에 대한 성과분석 (Support Project for the Establishment of a Smart Factory for the Win-win between Large and Small Businesses Performance Analysis of the Adopting Company)

  • 서홍일;김태성
    • 대한안전경영과학회지
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    • 제24권2호
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    • pp.135-142
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    • 2022
  • The smart factory is an important system that can reduce defects, maximize productivity, and respond to customer needs, from the labor-intensive era of traditional small and medium-sized manufacturing companies through the automation era to CPS using ICT. However, small and medium-sized manufacturers often fall short of the basic stage due to economic and environmental constraints, and there are many companies that do not even recognize the concept of a smart factory. In this situation, to expand the smart factory of small and medium-sized enterprises, the project to support the establishment of a smart factory for the win-win between large and small enterprises. The win-win smart factory construction support project provides a customized differentiation program support project according to the size and level of the company for all domestic manufacturing SMEs regardless of whether or not they are dealing with Samsung. In this study, we analyze the construction status and introduction performance of companies participating in the win-win smart factory support project to find out whether they have been helpful in management and to find efficient ways to improve support policies, and to suggest the direction of continuous support projects to improve the manufacturing competitiveness of SMEs in the future.

중소기업 스마트 공장 확장성 사례연구 (A Case Study on Smart Factory Extensibility for Small and Medium Enterprises)

  • 김성민;안재경
    • 산업경영시스템학회지
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    • 제44권2호
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    • pp.43-57
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    • 2021
  • Smart factories can be defined as intelligent factories that produce products through IoT-based data. In order to build and operate a smart factory, various new technologies such as CPS, IoT, Big Data, and AI are to be introduced and utilized, while the implementation of a MES system that accurately and quickly collects equipment data and production performance is as important as those new technologies. First of all, it is very essential to build a smart factory appropriate to the current status of the company. In this study, what are the essential prerequisite factors for successfully implementing a smart factory was investigated. A case study has been carried out to illustrate the effect of implementing ERP and MES, and to examine the extensibilities into a smart factory. ERP and MES as an integrated manufacturing information system do not imply a smart factory, however, it has been confirmed that ERP and MES are necessary conditions among many factors for developing into a smart factory. Therefore, the stepwise implementation of intelligent MES through the expansion of MES function was suggested. An intelligent MES that is capable of making various decisions has been investigated as a prototyping system by applying data mining techniques and big data analysis. In the end, in order for small and medium enterprises to implement a low-cost, high-efficiency smart factory, the level and goal of the smart factory must be clearly defined, and the transition to ERP and MES-based intelligent factories could be a potential alternative.