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      다국어 초록 (Multilingual Abstract)

      As products have been more complex and customer’s demands of personalized products are increasing, manufacturing system has been changed from mass production to mass customization production that makes small quantity but different kinds of product. In addition, it becomes important that manufacturers quickly respond to variable customer’s demands and characteristic regulations in each country. Therefore, three prerequisites are essential for manufacturers to response agilely. First, manufacturing data should be monitored in real time, second, information is extracted from the data, and finally, the information is used to make manufacturing strategy. In this paper, the mobile dashboard system is presented. It visualizes manufacturing data on mobile devices, and measures performance of the shop floor through the information. The proposed system is composed of server and client, and is running on the R - the open source software for statistics. Four kinds of template are given for easy visualization through the system.
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      As products have been more complex and customer’s demands of personalized products are increasing, manufacturing system has been changed from mass production to mass customization production that makes small quantity but different kinds of product. ...

      As products have been more complex and customer’s demands of personalized products are increasing, manufacturing system has been changed from mass production to mass customization production that makes small quantity but different kinds of product. In addition, it becomes important that manufacturers quickly respond to variable customer’s demands and characteristic regulations in each country. Therefore, three prerequisites are essential for manufacturers to response agilely. First, manufacturing data should be monitored in real time, second, information is extracted from the data, and finally, the information is used to make manufacturing strategy. In this paper, the mobile dashboard system is presented. It visualizes manufacturing data on mobile devices, and measures performance of the shop floor through the information. The proposed system is composed of server and client, and is running on the R - the open source software for statistics. Four kinds of template are given for easy visualization through the system.

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      참고문헌 (Reference)

      1 Hwang, Y. -D., "The Practices of Integrating Manufacturing Execution Systems and Six Sigma Methodology" 31 (31): 145-154, 2006

      2 Lee, G. -B., "Suggestions for Implementation of the Digital Factory-Based Extended Manufacturing Execution System" 26 (26): 17-23, 2009

      3 Kuo, C. -J., "Manufacturing Intelligence to Exploit the Value of Production and Tool Data to Reduce Cycle Time" 8 (8): 103-111, 2011

      4 Chien, C. -F., "Manufacturing Intelligence for Semiconductor Demand Forecast Based on Technology Diffusion and Product Life Cycle" 128 : 496-509, 2010

      5 Kletti, J., "Manufacturing Execution System - MES" Springer 13-29, 2012

      6 MESA International, "MES Explained: A High Level Vision"

      7 Smith, A., "From EMI to Operations Intelligence, Part 1: Business Leaders Seek Key Performance Drivers"

      8 Ho, C. -J., "Evaluating the Impact of Operating Environments on MRP System Nervousness" 27 (27): 1115-1135, 1989

      9 Barbara Linke, "Establishing Greener Products and Manufacturing Processes" 한국정밀공학회 13 (13): 1029-1036, 2012

      10 Jo, H., "Configuration MES and The Application Methodology" 507-508, 2012

      1 Hwang, Y. -D., "The Practices of Integrating Manufacturing Execution Systems and Six Sigma Methodology" 31 (31): 145-154, 2006

      2 Lee, G. -B., "Suggestions for Implementation of the Digital Factory-Based Extended Manufacturing Execution System" 26 (26): 17-23, 2009

      3 Kuo, C. -J., "Manufacturing Intelligence to Exploit the Value of Production and Tool Data to Reduce Cycle Time" 8 (8): 103-111, 2011

      4 Chien, C. -F., "Manufacturing Intelligence for Semiconductor Demand Forecast Based on Technology Diffusion and Product Life Cycle" 128 : 496-509, 2010

      5 Kletti, J., "Manufacturing Execution System - MES" Springer 13-29, 2012

      6 MESA International, "MES Explained: A High Level Vision"

      7 Smith, A., "From EMI to Operations Intelligence, Part 1: Business Leaders Seek Key Performance Drivers"

      8 Ho, C. -J., "Evaluating the Impact of Operating Environments on MRP System Nervousness" 27 (27): 1115-1135, 1989

      9 Barbara Linke, "Establishing Greener Products and Manufacturing Processes" 한국정밀공학회 13 (13): 1029-1036, 2012

      10 Jo, H., "Configuration MES and The Application Methodology" 507-508, 2012

      11 Venables, W. N., "An Introduction to R"

      12 Unver, H. O., "An ISA-95-based Manufacturing Intelligence System in Support of Lean Initiatives" 65 : 853-866, 2013

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2013-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2008-06-23 학회명변경 영문명 : Korean Society Of Precision Engineering -> Korean Society for Precision Engineering KCI등재
      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2006-07-07 학술지명변경 외국어명 : 미등록 -> Journal of the Korean Society for Precision Engineering KCI등재
      2006-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2004-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2001-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      1998-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.26 0.26 0.26
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.24 0.22 0.449 0.12
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