제조업 특성을 반영한 스마트공장 진단모델 개발 및 중소기업 맞춤형 적용사례

• 영문명: Development of Smart Factory Diagnostic Model Reflecting Manufacturing Characteristics and Customized Application of Small and Medium Enterprises
• 발행기관: 한국산업경영시스템학회
• 저자명: 김현득(Hyun-Deuk Kim) 김동민(Dong-Min Kim) 이경근(Kyung-Geun Lee) 윤제환(Je-Whan Yoon) 염세경(Sekyoung Youm)
• 간행물 정보: 『산업경영시스템학회지』제42권 제3호, 25~38쪽, 전체 14쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2019.09.30

영문 초록

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.

목차

1. 서 론

2. 선행 연구

3. 스마트공장 진단모델 개발 및 적용결과

4. 진단결과

5. 결 론

키워드

Smart Factory Diagnostic Model SMEs Value Chain Process Innovation1)