한국산업정보학회논문지 (Journal of Korea Society of Industrial Information Systems)

한국산업정보학회 (Korea Society of Industrial Information Systems)
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DMAIC 방법론의 생산시스템 개발자 과제 최적화 모델링: 배터리 제조 중심으로

Optimization of DMAIC for production system developer task : Focused on Battery Manufacturing

  • 박신철 (아주대학교 과학기술정책학과) ;
  • 이주연 (아주대학교 과학기술정책학과) ;
  • 정명석 (아주대학교 과학기술정책학과)
  • 투고 : 2023.12.15
  • 심사 : 2024.03.30
  • 발행 : 2024.04.30
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초록

DMAIC는 배터리 제조 관련 엔지니어들에게 가장 친숙한 문제해결방법론이나, 배터리 생산시스템 개발자의 다양한 과제에 대한 무분별한 적용으로 과제 지연, 성과 미흡 및 부분 최적화 등 지속적인 문제 발생이 되고 있는 실정이다. 배터리 생산시스템 개발자 과제를 효과적으로 대응할 수 있는"DMAIC 방법론의 최적화 모델"을 확보하고자 3단계 연구모형을 활용하여 생산시스템 개발자 과제 방법론의 요구특성을 도출하고, DMAIC의 적합성을 분석하여 부족한 부분을 보완하여 최적화 모델링을 실시하였다. 본 연구 결과물인 "시스템 구조적 7단계 방법론"을 활용하여 개발자 과제에 적용해 봄으로서 DMAIC 방법론을 보다 적합성을 높일 수 있다는 점을 확인하였다. 하나의 방법론으로 보다 학습이 용이하고 다양한 산업별 특성에 맞춰 차별화 운영을 할 수 있도록 하여 향후 다양한 산업분야에 적용 가능할 것으로 기대된다.

DMAIC is the most familiar problem-solving methodology to battery manufacturing-related engineers, but continuous problems such as task delay, insufficient performance, and partial optimization are occurring due to indiscriminate application to various tasks of battery production system developers. In order to secure an "optimized model for DMAIC methodology" that can effectively respond to battery production system developers' tasks, a three-stage research model was used to derive the required characteristics of the production system developer task methodology, analyze the suitability of DMAIC, and conduct optimization modeling by supplementing the shortcomings. It was confirmed that the DMAIC methodology can be more suitable by applying the "system structural seven-step methodology", which is the result of this study, to developer tasks. It is expected that it will be applied to various industrial fields in the future by making it easier to learn and allowing differentiated operations according to the characteristics of various industries.

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