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FOM을 활용한 자동차 부품 공정의 생산성 및 생산계획 정확도 향상에 관한 연구
Abstract
This study aims to improve productivity by analyzing manufacturing-process data and deriving problems using a FOM system. Additionally, an accurate demandforecast production plan is established to increase manufacturing competitiveness. As a case study, MES data are analyzed using an FOM assistant for Company I, which is an automobile parts manufacturer, and the correlation among man, machine, material, and method is identified. The production plan fluctuated significantly and the productivity declined owing to the inactivity time (equipment waiting, mold setting, etc.). The method of converting to external preparation by dividing internal and external preparations, standardizing the mold setup, and using data is presented.
In addition, the importance and evaluation method of establishing a high-accuracy production plan were presented, and the introduction of APS was proposed to increase the accuracy of the production plan by predicting, revising, and supplementing demand by period, customer, and product through accumulated data analysis.
Keywords:
FOM(smart-factory operation management), 4M data analysis, APS(advanced production scheduling), ProductivityReferences
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Graduate Student in Department of AI Smart Factory Convergence Engineering, Hoseo University. His research interest is FOM (smart-Factory Operation Management) with AI.
E-mail: ksnam20@hanmail.net
Invited Professor in Smart Material Component Engineering of Manufacturing Innovation School, Inha University. His research interest is smart Factory Operation Management and Manufacturing Innovation with AI.
E-mail: sangsoh@inha.ac.kr
Professor in Department of AI Smart Factory Convergence Engineering, Hoseo University. His research interest is Applications of FOMs (smart-Factory Operation Managements).
E-mail: df2030@hoseo.edu