• Title/Summary/Keyword: Maturity of Smart Factory Deployment

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

  • Chong, Hye Ran;Bae, Kyoung Han;Lee, Min Koo;Kwon, Hyuck Moo;Hong, Sung Hoon
    • Journal of Korean Society for Quality Management
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    • v.48 no.1
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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.

Quality 4.0: Concept, Elements, Level Evaluation and Deployment Direction (품질 4.0: 개념, 요소, 수준 평가와 전개 방향)

  • Seo, Hojin;Byun, Jai-Hyun;Kim, Dohyun
    • Journal of Korean Society for Quality Management
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    • v.49 no.4
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    • pp.447-466
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    • 2021
  • Purpose: This article aims 1) to propose Quality 4.0 concept through surveying related literature, 2) to suggest key elements of Quality 4.0 by arranging the elements of Quality 4.0 that appeared in the literature, 3) to determine the levels of Quality 4.0, and 4) to suggest ideas for effective deployment of Quality 4.0. Methods: Eleven papers or documents are reviewed for Quality 4.0 concept; two papers and one document are investigated for key element extraction of Quality 4.0; and smart factory roadmap and industry 4.0 maturity model are studied to determine the levels of Quality 4.0. Results: 1) Quality 4.0 definition is proposed. 2) Three key elements are determined: data acquisition and analytics, connection and integration, and leadership and culture. 3) Six Quality 4.0 levels are determined. 4) Some suggestions are addressed for effective deployment of Quality 4.0. Conclusion: 1) Definition, key elements, levels, and some suggestions on effective deployment of Quality 4.0 are addressed. 2) Specific contents of Quality 4.0 education and training courses should be provided in the future. 3) Two future research directions are proposed.

Smart Factory Policy Measures for Promoting Manufacturing Innovation (제조혁신 촉진을 위한 스마트공장 정책방안)

  • Park, Jaesung James;Kang, Jae Won
    • Korean small business review
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    • v.42 no.2
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    • pp.117-137
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    • 2020
  • We examine the current status of smart factory deployment and diffusion programs in Korea, and seek to promote manufacturing innovation from the perspective of SMEs. The main conclusions of this paper are as follows. First, without additional market creation and supply chain improvement, smart factories are unlikely to raise profitability leading to overinvestment. Second, new business models need to connect "manufacturing process efficiency" with "R&D" and "marketing" in value chain in smart factories. Third, when introducing smart factories, we need to focus on the areas where process-embedded technology is directly linked to corporate competitiveness. Based on the modularity-maturity matrix (Pisano and Shih, 2012) and the examples of U.S. Manufacturing Innovation Institute (MII), we establish the new smart factory deployment policy measures as follows. First, we shift our smart factory strategy from quantitative expansion to qualitative upgrading. Second, we promote by each sector the formation of industrial commons that help SMEs to jointly develop R&D, exchange standardized data and practices, and facilitate supplier-led procurement system. Third, to implement new technology and business models, we encourage partnerships, collaborations, and M&As between conventional SMEs and start-ups and business ventures. Fourth, the whole deployment process of smart factories is indexed in detail to identify the problems and provide appropriate solutions.

Analysis of Research Trends of Cyber Physical System(CPS) in the Manufacturing Industry (제조 분야 사이버 물리 시스템(CPS) 연구 동향 분석)

  • Kang, Hyung-Muck;Hwang, Kyung-Tae
    • Informatization Policy
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    • v.25 no.3
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    • pp.3-28
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    • 2018
  • The purpose of this study is to analyze the research trends and present future research directions in the field of Cyber Physical System (CPS), a key element in the 4th Industrial Revolution, Industry 4.0, and Smart Manufacturing that are currently promoted as important innovation agenda both at home and abroad. In this study, (1) the concepts of industry 4.0, smart manufacturing and CPS are summarized; (2) analysis criteria of these fields are established; and 3) analysis results are presented and future research direction is proposed. 74 overseas and 8 domestic literature on manufacturing CPS from 2013 to 2017 are identified through 'Google Scholar Search'. Major results of the analysis are summarized as follows: (1) research on a common methodology and framework for the manufacturing CPS needs to be done based on the analysis of the existing methodologies and frameworks of various perspectives; (2) in order to improve the maturity of the manufacturing CPS, it is necessary to study actual deployment and operations of CPS, including the existing systems; (3) it is necessary to study the diagnostic methodology that can evaluate manufacturing CPS and suggest improvement strategy; and (4) as for the detailed model and tool, it is necessary to reinforce research on SCM production planning and human-machine collaboration while considering the characteristics of CPS.