TY - GEN
T1 - Formulation and solution for the predictive maintenance integrated job shop scheduling problem
AU - Zhai, Simon
AU - Riess, Alexander
AU - Reinhart, Gunther
N1 - Publisher Copyright:
© 2019 IEEE
PY - 2019/6
Y1 - 2019/6
N2 - Predictive Maintenance has gained a lot of attention in recent years due to the development of improved sensors and intelligent algorithms. These allow for monitoring the health condition of production machinery and predict its future deterioration. In order to generate added value for industrial use cases, two more steps are required: considering the machine’s time-varying operational conditions and integrating its dependent deterioration prediction in a holistic scheduling approach. This publication identifies a shortage of deterioration estimation frameworks under time-varying operational conditions as well as a lack of Predictive Maintenance integrated scheduling problems in the literature. Subsequently, a new conceptual framework to model future machine deterioration under time-varying operational conditions and its application in production scheduling is introduced. The Operation Specific Stress Equivalent (OSSE) represents the load of a future production job on the machine and supports a general formulation of the maintenance integrated job shop scheduling problem (MIJSSP). This formulation is presented together with benchmark instances and corresponding sample data.
AB - Predictive Maintenance has gained a lot of attention in recent years due to the development of improved sensors and intelligent algorithms. These allow for monitoring the health condition of production machinery and predict its future deterioration. In order to generate added value for industrial use cases, two more steps are required: considering the machine’s time-varying operational conditions and integrating its dependent deterioration prediction in a holistic scheduling approach. This publication identifies a shortage of deterioration estimation frameworks under time-varying operational conditions as well as a lack of Predictive Maintenance integrated scheduling problems in the literature. Subsequently, a new conceptual framework to model future machine deterioration under time-varying operational conditions and its application in production scheduling is introduced. The Operation Specific Stress Equivalent (OSSE) represents the load of a future production job on the machine and supports a general formulation of the maintenance integrated job shop scheduling problem (MIJSSP). This formulation is presented together with benchmark instances and corresponding sample data.
KW - Decision Support
KW - Integrated Scheduling
KW - Optimization
KW - Predictive Maintenance
UR - http://www.scopus.com/inward/record.url?scp=85072778377&partnerID=8YFLogxK
U2 - 10.1109/ICPHM.2019.8819397
DO - 10.1109/ICPHM.2019.8819397
M3 - Conference contribution
AN - SCOPUS:85072778377
T3 - 2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019
BT - 2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019
Y2 - 17 June 2019 through 20 June 2019
ER -