Fabrication 공정에서의 재공 소진 효율화 스케쥴링 규칙에 관한 연구
A Study on Scheduling Rule for Efficient Work-In-Process Control in Fabrication Process
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초록
코로나-19 팬데믹 이후 비대면 활동이 일상화됨에 따라 재택근무, 온라인 학습 등으로 개인용 PC 및 모바일제품의 수요가 늘어 반도체 칩의 사용량 증가 현상이 발생하고 있다. 특히 4차 산업혁명을 이끌 자율주행자동차, Cloud Computing 및 AI(Artificial Intelligence) 등의 디지털 전환이 가속화됨에 따라 반도체 칩 수요가급격하게 증가하고 있으며, 차량용 반도체를 포함한 IT (Information Technology) 제품에 이르기까지 글로벌반도체 공급 부족 현상이 발생하여 반도체를 활용한 산업 전반에 예상치 못한 반도체 수퍼사이클(초호황기)이기대되고 있다. 반도체 생산라인에서 고객 수요 충족을 최대화하기 위해서는 라인 내 재공을 효율적으로 소진하면서 설비의 가동 효율을 극대화함과 동시에 투입량을 적절하게 통제하는 것이 매우 중요하다. 특히 생산공정의 재공 밸런싱을 통해 적절히 재공을 소진하고 수요 충족을 위한 투입량 결정 문제가 전체 매출을 높이기위한 중요한 이슈로 부각되고 있다. 본 논문에서는 생산라인 내 레이어에 존재하는 재공을 고려한 고객 수요만족 측면에서의 역행 전진 소진정책과 웨이퍼 투입량 결정 문제를 제안하였으며, 역행 전진 초기 투입량 산출및 스케쥴링 룰을 검증하기 위해 실제 반도체 생산라인을 단순화하여 모델링하였다. 다양한 데이터 셋을 통해재공 소진 투입 규칙에 대한 결과를 검증하고, 실제 반도체 생산라인에 적용 가능성을 평가하였다.
Abstract
Semiconductor manufacturing has suffered from the complex behavior of the technology oriented control in the production line. While the technological processes are in the charge of the quality the yield of the production, the operational management is also critical for the productivity of the manufacturing line. The semiconductor industry is the most capital-intensive type of manufacturing. The product life cycle time is short while manufacturing cycle time is long. In order to maximize customer demand in the semiconductor production line, it is very important to efficiently consume the work in the manufacturing line. Maximize the operation efficiency of the facility, and control the input amount appropriately. In particular, the problem of properly consuming work-in-process by line balancing for each layer and determining the amount of input to meet demand is very important. In this paper, we propose a backward projection policy and a wafer input amount determining by the scheduling rule in terms of customer demand satisfaction considering the work-in-progress. simplify the actual semiconductor production line to verify the initial input amount calculation and scheduling rules was modeled. The results of the work-in-process consuming input rule were verified through various data sets, and the applicability to actual semiconductor production lines was evaluated.
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