Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Development of Smart Factory Diagnostic Model Reflecting Manufacturing Characteristics and Customized Application of Small and Medium Enterprises

제조업 특성을 반영한 스마트공장 진단모델 개발 및 중소기업 맞춤형 적용사례

  • 김현득 (동국대학교 융합표준학과) ;
  • 김동민 (인천테크노파크 기업지원센터) ;
  • 이경근 (한국표준협회 품질경영본부) ;
  • 윤제환 (한국표준협회 품질경영본부) ;
  • 염세경 (동국대학교 융합표준학과)
  • Received : 2019.06.10
  • Accepted : 2019.08.30
  • Published : 2019.09.30
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Abstract

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.

Keywords

References

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