A Development of the Optimization Model for Reactive Scheduling Considering Equipment Failure

장치이상을 고려한 동적 생산계획 최적화 모델 개발

  • Ha, Jin-Kuk (Department of Chemical & Biochemical Engineering, Dongguk University) ;
  • Lee, Euy Soo (Department of Chemical & Biochemical Engineering, Dongguk University)
  • 하진국 (동국대학교 생명화학공학과) ;
  • 이의수 (동국대학교 생명화학공학과)
  • Received : 2005.08.05
  • Accepted : 2005.09.05
  • Published : 2005.10.31

Abstract

We propose a new optimization framework for the reactive scheduling. The proposed rescheduling scheme is specially focused on how to generate rescheduling results when equipment failure occurs. The approach is based on a continuous-time problem representation that takes into account the schedule in progress, the updated information on the batches still to be processed, the present plant state, the deviations in plant parameters and the time data. To update the predictive scheduling, we used right shift rescheduling and total regeneration when equipment failure occurs. And, a practical solution to the rescheduling problem requires satisfaction of two often confliction measures: the efficiency measure that evaluates the satisfaction of a desired objective function value and the stability measure that evaluates the amount of change between the schedules before and after the disruption. In this paper, the efficiency is measured by the makespan of all jobs in the system. And, the stability is measured by the percentage change in makespan and the modified sequence deviation in the predictive scheduling and rescheduling.

불연속 화학공정은 소비자 수요에 탄력성 있게 대처할 수 있는 장점이 있는 반면에 그 특유의 동특성 때문에 복잡하고, 계획된 조업 시간과 실제 조업 시간 사이에서 외란(disruption) 또는 불확실 변수(uncertainty)에 의한 차이가 자주 발생하는 단점이 있다. 이에, 본 논문에서는 예측 생산계획(predictive scheduling)에 의해 결정된 생산계획에서 미래에 발생하는 공정 변수 값의 변화를 실시간으로 예측 생산계획을 수정, 제시하여 주는 생산 계획 시스템인 동적 생산계획(reactive scheduling) 기법을 개발하였다. 불확실 인자를 고려한 동적 생산계획에서, 본 논문에서는 장치 이상(equipment failure)이 발생하였을 때 공정 운전조건의 변화를 실시간으로 반영하여, 예측 생산계획(predictive scheduling) 모델에 의하여 제시된 전체 생산 계획을 최대한 유지하고 공정 변수의 변화를 실시간으로 반영하기 위하여 right shift rescheduling과 total regeneration 기법을 사용하였다. 또한, 불확실 인자의 발생 전후의 predictive scheduling과 reactive scheduling 간의 변화 정도를 측정하는 수단인 schedule stability 위하여, 본 논문에서는 수정된 sequence deviation과 percentage change in makespan을 사용하여 제안된 동적 생산계획의 안정성을 측정하였다. 본 논문에서 제안한 동적 생산계획 시스템은 기존에 제시되었던 경험 법칙에 의한 결과값에 비해 좋은 결과를 보여주었다.

Keywords

Acknowledgement

Supported by : 한국과학재단

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