Smart Predictive Maintenance of Mechatronic Systems with Digital Twins

Explore the world of Smart Predictive Maintenance (SPM) for Mechatronic Systems using Smart Big Data (SBD) and Digital Twins (DT). Join the tutorial by YangQuan Chen, Professor at MESA Lab, University of California Merced. Discover the impact of digital transformation, AI, IoT, and more on enhancing control systems' smartness and performance. Don't miss this opportunity to delve into the future of maintenance strategies.

• Predictive Maintenance
• Mechatronic Systems
• Digital Twins
• Smart Big Data
• Control Engineering

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1. MESA LAB Smart Predictive Maintenance (SPM) of Mechatronic Systems Based on Smart Big Data (SBD) and Digital Twins Organized by YangQuan Chen, Professor MESA (Mechatronics Embedded Systems and Automation) Lab Dept. of Mechanical Engineering, University of California Merced E: yqchen@ieee.org, W: http://mechatronics.ucmerced.edu/ Joint 9th IFAC Symposium on Mechatronic Systems and 16th International Conference on Motion and Vibration Control Preconference Workshop https://ifacms-movic2022.seas.ucla.edu/schedule/ and http://mechatronics.ucmerced.edu/ September 6, Tuesday 13:00- 17:00

2. MESA LAB Slide-2/1024 Smart Predictive Maintenance (SPM) of Mechatronic Systems Based on Smart Big Data (SBD) and Digital Twins Part 1: Tutorial Overview http://mechatronics.ucmerced.edu/spm YangQuan Chen, Ph.D. ychen53@ucmerced.edu 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

3. MESA LAB Slide-3/1024 Outline Overview 1 Presenters 2 Schedule 3 Discussions 4 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

4. MESA LAB Slide-4/1024 What and why now? What? Smart Predictive Maintenance (SPM), Digital Twins (DT), Smart Big Data (SBD) Driving forces: digital transformation, sensor rich and actuator rich systems, connectedness, industrial AI, smartness, edge/cloud computing, IoT, AI/ML and big data Why now? storage, embedded hardware and embedded communication are cheaper and cheaper, Industrial 4.0 movement, AI/ML, BD, DT, CC etc. enable smartness ,and smartness enables the profit margin. 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

5. MESA LAB Slide-5/1024 Control 2.0 Classical control => Modern control => ? Control 1.0 How optimal? How robust? Control 2.0 How optimal? How robust? How smart? Classical control => Modern control => Smart control 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

6. MESA LAB Slide-6/1024 Smart control engineering (SCE) SCE: A branch of control engineering that leverage breaking technologies like Edge Computing, IoT, AI, Big Data, Data Analytics to enhance the smartness and performance of a control system 1. System is distributed with multiple agents equipped with breaking technologies 2. Real-time optimization based on a cost function based on system economic, health, or fault conditions. 3. Resilient behavior able to adapt to unknown changes on the system based on developmental controllers 4. Virtual representation of each single element (Digital Twin) 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

7. MESA LAB Slide-7/1024 Smart Predictive Maintenance (SPM) Focus of this 4-hour long tutorial Basics SCE/DT/SOC: Dr Jairo Viola SPM/DT: Furkan Guc Smart Big Data: Prof. Chen Advanced topics Heavytailedness aware: Prof. Pawel Domanski Unbalanced data and learning: Prof. Jing Wang 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

8. MESA LAB Slide-8/1024 Outline Overview 1 Presenters 2 Schedule 3 Discussions 4 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

9. MESA LAB Slide-9/1024 Prof. YangQuan Chen Mechatronics, Embedded Systems and Automation (MESA) LAB, Dept. of Mechanical Engineering, School of Engineering, University of California, Merced, 5200 North Lake Road, Merced, CA95343, USA Emails:yqchen@ieee.org; Phone:(209)228-4672 https://scholar.google.com/citations?user=RDEI RbcAAAAJ&hl=en 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

10. MESA LAB Slide-10/1024 Prof. Dr. Pawe D. Doma ski Warsaw University of Technology Institute of Control and Computation Engineering Nowowiejska 15/19 00-665 Warsaw, Poland Email: p.domanski@ia.pw.edu.pl 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

11. MESA LAB Slide-11/1024 Jairo Viola, Ph.D. Mechatronics, Embedded Systems and Automation (MESA) LAB, Dept. of Mechanical Engineering, School of Engineering University of California, Merced 5200 North Lake Road, Merced, CA95343, USA Emails: jviola@ucmerced.edu 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

12. MESA LAB Slide-12/1024 Furkan Guc, Ph.D. student Mechatronics, Embedded Systems and Automation (MESA) LAB, Dept. of Mechanical Engineering, School of Engineering University of California, Merced 5200 North Lake Road, Merced, CA95343, USA Emails: fguc@ucmerced.edu 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

13. MESA LAB Slide-13/1024 Prof. Jing Wang (PhD) Department of Automation, School of Electrical and Control Engineering, North China University of Technology (NCUT) No.5, Jinyuanzhuang Road, Beijing, China 100144 jwang@ncut.edu.cn 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

14. MESA LAB Slide-14/1024 Outline Overview 1 Presenters 2 Schedule Discussions 3 4 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

15. MESA LAB Slide-15/1024 Schedule (4 hours) 1. 13:00-13:10. Introduction to the Tutorial Workshop program (YangQuan Chen) 2. 13:10-14:00. What is SPM: Smart Predictive Maintenance? A mechatronics testbed for smart predictive maintenance case studies (Furkan Guc) 3. 14:00-14:50. Digital Twins and Digital Twin Enabled Smart Control Engineering (Dr. Jairo Viola) [1] (47 min) https://youtu.be/l5X3niNqC2A 14:50-15:00. Coffee break and free chats. (tbd) 4. 15:00-15:30. Smart big data and complexity-aware advanced analytics (YangQuan Chen) 5. 15:30-16:10 Heavy tailedness-aware control system performance assessment and fault detection(Dr. Pawe D. Doma ski) [2] [3] (40 min https://youtu.be/SI_eNCe_sug ) 6. 16:10-16:50 Learning from imbalanced data and its applications in fault diagnosis (Dr. Jing Wang) [4] 7. 16:50-17:00 Discussions continue to 5-7pm Opening reception https://docs.google.com/document/d/1bsutiiOGxcmQ4WBEv2Wt3rePdyWdc1mWPNwUZzfvv-s/edit 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

16. MESA LAB Slide-16/1024 Outline Overview 1 Presenters 2 Schedule 3 Discussions 4 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

17. MESA LAB Slide-17/1024 Discussions What are missing in Control 1.0 ? LCA: life cycle analysis Health management Control that has self-awareness of health conditions ??? What is publishable and fundable? Health indicator design optimal? Robust? Smart? 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

18. MESA LAB Slide-18/1024 Key references 1. Viola, J and YQ Chen. Digital Twin Enabled Smart Control Engineering - A Framework and Case Studies . A volume in Synthesis Lectures on Engineering, Science, and Technology Springer. 2022. (to appear). (www.TheEdgeAI.com) 2. Pawe D. Doma ski and YangQuan Chen and Maciej awry czuk (2022). Outliers in Control Engineering Fractional Calculus Perspective. March 2022. De Gruyter. Book Series on Fractional calculus and its applications in science and engineering https://doi.org/10.1515/9783110729122 3. Pawe D. Doma ski (2020). Control Performance Assessment: Theoretical Analyses and Industrial Practice, Springer, https://link.springer.com/book/10.1007/978-3-030-23593-2 4. Jing Wang, Jinglin Zhou, Xiaolu Chen (2022). Data-Driven Fault Detection and Reasoning for Industrial Monitoring, Springer, https://link.springer.com/book/10.1007/978-981-16-8044-1 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD

19. MESA LAB Slide-19/1024 Thanks for your attention! For further information, publications, and videos visit: theedgeai.com and http://mechatronics.ucmerced.edu/spm 10/4/2024 Tutorial on Smart Predictive Mantenance (SPM) by DT and SBD