TY - GEN
T1 - Predictive-Reactive Rescheduling for New Order Arrivals with Optimal Dynamic Pegging
AU - Moghaddam, Shokraneh K.
AU - Saitou, Kazuhiro
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - 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.
AB - 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.
KW - dynamic pegging
KW - predictive-reactive scheduling
KW - stochastic order arrivals
UR - http://www.scopus.com/inward/record.url?scp=85094116058&partnerID=8YFLogxK
U2 - 10.1109/CASE48305.2020.9216870
DO - 10.1109/CASE48305.2020.9216870
M3 - Conference contribution
AN - SCOPUS:85094116058
T3 - IEEE International Conference on Automation Science and Engineering
SP - 710
EP - 715
BT - 2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020
PB - Institute of Electrical and Electronics Engineers (IEEE)
T2 - 16th IEEE International Conference on Automation Science and Engineering, CASE 2020
Y2 - 20 August 2020 through 21 August 2020
ER -