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Predictive-reactive rescheduling for new order arrivals with optimal dynamic pegging

Moghaddam, S. K ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1109/CASE48305.2020.9216870
  3. Publisher: IEEE Computer Society , 2020
  4. Abstract:
  5. This paper presents a new predictive-reactive rescheduling method for adjusting production schedules in response to the unplanned arrival of new orders in multi-level production. It is based on the concept of dynamic pegging, which enables the reassignment of the Work-In-Progress (WIP) to the existing or newly arrived orders at the time of rescheduling. Extending our previous work on reactive rescheduling with dynamic pegging, the new approach incorporates a probabilistic predictive model of new order arrival in the initial scheduling at the begging of the scheduling horizon. A Mixed Integer Programming (MIP) model is developed for two-phase, predictive-reactive scheduling before and after the arrival of a new order that follows an exponential distribution. The MIP model is solved for two periods. In the predictive phase before the new order arrival, the best schedule is achieved based on the expected arrival time for a new order. In the reactive phase after the new order arrival, the best schedule is created based on the dynamic pegging approach. Using a simple example, the proposed predictive-reactive rescheduling is compared with the reactive-only rescheduling in our previous work, with sampled arrivals of new orders. It is demonstrated the proposed approach performs statistically better than the reactive-only approach, especially during the reacting phase. © 2020 IEEE
  6. Keywords:
  7. Dynamic pegging ; Predictive-reactive scheduling ; Stochastic order arrivals ; Indium compounds ; Integer programming ; Production control ; Scheduling ; Exponential distributions ; Mixed integer programming model ; New approaches ; Optimal dynamics ; Predictive modeling ; Production schedule ; Reactive scheduling ; Work in progress ; Predictive analytics
  8. Source: 16th IEEE International Conference on Automation Science and Engineering, CASE 2020, 20 August 2020 through 21 August 2020 ; Volume 2020-August , 8 October , 2020 , Pages 710-715
  9. URL: https://ieeexplore.ieee.org/document/9216870