2026/10/19(MON) [AI-Driven R&D Innovation] Practical Applications of Rapid Design with Creo and Product Reliability Analysis
AI-Driven R&D Innovation: Practical Applications of Rapid Design with Creo and Product Reliability Analysis
As product development timelines shorten and quality expectations rise, how can companies improve R&D efficiency while ensuring product reliability?
ECS-AP (歐亞電腦股份有限公司), National Changhua University of Education, the Taiwan Reliability Technology Development Association (TRTA), and the Industry–Academia Alliance for Reliability Science and Technology Services are jointly organizing this seminar. Combining technical resources from PTC with academic and industry expertise, the event will feature presentations, live demonstrations, and case studies on AI-powered generative design, real-time simulation in Creo, and practical applications of product reliability analysis. Participants will explore ways to optimize R&D workflows and access industry–academia collaboration resources.
Event Highlights
- AI-Powered Generative Design and Structural Optimization: Learn how optimized structures can be generated automatically based on the design space, materials, and loading conditions, with case studies on lightweight component design.
- Real-Time Validation During Design: See Creo Simulation Live in action and learn how engineers can monitor stress and deformation as they modify models, identifying potential design issues early.
- Product Reliability Analysis and Emerging Trends: Explore advanced reliability physics analysis, reliability analysis software, and applications of AI in product reliability design.
- Industry–Academia Exchange and Technical Resources: Discover examples of successful industry adoption, technical support and talent connections available through industry–academia collaboration, followed by a Q&A session.
Event and Registration Information
- Date and Time: Monday, October 19, 2026, 09:00–16:30
- Venue: Computer Classroom E205, 2nd Floor, College of Engineering, National Changhua University of Education
- Admission: Free. Advance registration is required, and places are limited.
- Registration Deadline: Friday, October 16, 2026. Registration will close earlier if all places are filled.
- How to Register: Complete the online registration form, or contact an event coordinator and provide your company name, participant name, job title, telephone number, and email address. Our team will assist with registration.
- Detailed Agenda: View the event agenda
Agenda
| ime | Topic | Speakers / Presenting Organizations |
|---|---|---|
| 09:00–09:30 | Registration and Networking | — |
| 09:30–10:00 | Opening Remarks and Outlook for Industry–Academia Collaboration | University representatives, Prof. 鍾官榮, and senior representatives from PTC / ECS-AP |
| 10:00–10:20 | Break and Networking | — |
| 10:20–12:00 | Emerging Trends in Reliability Engineering | Prof. 陳始明, Prof. 王建智, Prof. 鄭順林, and Prof. 鍾官榮 |
| 12:00–13:30 | Lunch and Networking | — |
| 13:30–14:30 | Keynote: AI-Powered Generative Design in Creo: Transforming Traditional 3D Modeling Efficiency | Prof. 鍾官榮 / NCUE Industry–Academia Team |
| 14:30–14:50 | Break and Networking | — |
| 14:50–15:50 | Technical Session: Design and Validate: Early-Stage Product Reliability and CAE Analysis | Prof. 鍾官榮 / NCUE Industry–Academia Team |
| 15:50–16:15 | Industry–Academia Exchange and Panel Discussion | Project principal investigators / Alliance / Association |
| 16:15–16:30 | Survey, Lucky Draw, and Closing | Organizers |
Contact Information
ECS-AP (歐亞電腦股份有限公司)
李迎巧
Tel: 04-2375-0756
Email: nicole_lee@ecs-ap.com
National Changhua University of Education — Industry–Academia Collaboration Project
汪梓彭
Tel: 04-723-2105, ext. 8108
Email: a0905070457@gmail.com
Taiwan Reliability Technology Development Association (TRTA)
簡郁軒
Tel: 0966-445-369
Email: twrta2023@gmail.com
Industry–Academia Alliance for Reliability Science and Technology Services
簡郁軒
Tel: 02-2908-9899, ext. 3106
Email: kyu0527@mail.mcut.edu.tw
We warmly invite R&D managers and engineers to join us and exchange practical insights into AI-assisted design and product reliability analysis.
