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.

1. 서 론
2. 선행 연구
    2.1 국내․외 스마트공장 추진현황
    2.2 기업규모별 스마트공장 구축
3. 스마트공장 진단모델 개발 및 적용결과
    3.1 스마트공장 진단모델 개발
    3.2 스마트공장 진단모델 적용결과
4. 진단결과
5. 결 론
References

• Hyun-Deuk Kim(Department of Convergence Standard, Dongguk University, Standards Division, Korean Standards Association) | 김현득
• Dong-Min Kim(Corporate Support Center, Incheon Technopark) | 김동민
• Kyung-Geun Lee(Quality Management Division, Korean Standards Association) | 이경근
• Je-Whan Yoon(Quality Management Division, Korean Standards Association) | 윤제환
• Sekyoung Youm(Department of Convergence Standard, Dongguk University) | 염세경 Corresponding Author