Jumeau numérique pour la gestion adaptative de la maintenance et de la recharge : approche de synchronisation en temps réel
Bibliographic record
Abstract
RÉSUMÉ: L’intégration des jumeaux numériques (JN) basés sur la simulation à événements discrets (SED) constitue une nouvelle approche pour soutenir la prise de décision en temps réel dans les environnements manufacturiers et logistiques. Ce mémoire présente la conception et la mise en œuvre d’un jumeau numérique à base de SED au sein du Laboratoire des systèmes cyber-physiques intelligents (SCP-I) de Polytechnique Montréal. L’objectif est de développer un mécanisme de synchronisation en temps réel permettant de gérer de manière adaptative les opérations de maintenance et de recharge des robots mobiles autonomes (Autonomous Mobile Robot, ou AMR) dans un entrepôt intelligent. Le cadre proposé combine deux modes de synchronisation complémentaires : la synchronisation périodique (Time-Triggered, ou TT) pour les actions de commande et la synchronisation déclenchée par événement (Event-Triggered, ou ET) pour la surveillance et le suivi des changements d’état. L’architecture, conforme à la norme ISO 23247, intègre un modèle SED servant de noyau décisionnel et assurant la synchronisation en temps réel entre le système physique et sa contrepartie numérique. Les expérimentations menées au SCP-I montrent que le mécanisme de synchronisation sélective réduit la latence de communication entre le système physique et sa contrepartie numérique, améliorant ainsi la continuité opérationnelle. Ce travail propose une démarche méthodique pour la conception de jumeaux numériques à base de SED capables de soutenir la prise de décision en temps réel dans les systèmes industriels. ABSTRACT: real-time decision-making in manufacturing and logistics systems. This master’s thesis presents the design and implementation of a DES-based DT developed within the Intelligent Cyber–Physical Systems (I-CPS) Laboratory at Polytechnique Montréal. The objective is to develop a real-time synchronization mechanism that enables adaptive management of maintenance and charging operations for Autonomous Mobile Robots (AMRs) in a smart warehouse environment. The proposed framework combines two synchronization mechanisms: Time-Triggered (TT) synchronization for control actions and Event-Triggered (ET) synchronization for monitoring and state updates. The architecture, aligned with the ISO 23247 standard, embeds a DES model as the decision-making kernel to maintain temporal consistency between the physical system and its digital counterpart. Experimental results obtained in the I-CPS Laboratory show that the selective synchronization mechanism reduces communication latency between the physical and digital systems, maintaining operational continuity. This work defines a methodology for developing DES-based DT that support real-time operational decision-making in industrial systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".