Title:
Delivery: In-person
Time: Full day (with coffee/tea breaks and lunch break)
Class: Mix of theory + live exercises
Instructors: Dr Eric Bechhoefer, Peeyush Pankaj
Registration fee: Please refer to Registration page for more information
Abstract:
Prognostics and Health Management (PHM) and Health and Usage Monitoring Systems (HUMS) are transforming how engineered systems are monitored, maintained, and sustained. This short course provides engineers and technical managers with a practical, application-oriented introduction to the core concepts, tools, and workflows behind PHM and HUMS.
Through a combination of foundational theory and real-world case studies—including a detailed look at helicopter systems—participants will explore sensor integration, condition indicators, signal processing, machine learning, and deep learning techniques for diagnostics and prognostics. The course also covers low-code methods and automation for accelerating development, along with best practices for deployment. Whether you're building, analyzing, or deploying PHM/HUMS systems, or just getting started, this course will give you a solid foundation to begin or advance your work.
Course Outline: Click here to view.
Instructor Bio:
Eric Bechhoefer, Ph.D. is the founder of Green Power Monitoring Systems (GPMS) and a pioneering figure in the field of condition-based maintenance (CBM) and Health and Usage Monitoring Systems (HUMS). An accomplished researcher and inventor, Eric has authored over 200 technical papers and holds 64 patents in the areas of machine diagnostics, condition monitoring, and prognostics. His academic and professional credentials include a Ph.D. in Engineering, and he is a Senior Member of IEEE, as well as a Fellow of both the Prognostics and Health Management (PHM) Society and the Machinery Failure Prevention Technology (MFPT) Society. He serves on the Vertical Flight Society’s HUMS Technical Committee, the SAE committee for Integrated Vehicle Health Monitoring, and is a member of the Rotorcraft Maintenance Program Industry Group (RMPIWG). A retired U.S. Naval Flight Officer, Eric brings over a 25 years of focused innovation in aviation safety, diagnostics, and predictive maintenance technologies. Through his work at the intersection of signal processing, systems engineering, and aviation operations, Eric continues to lead the industry toward safer, smarter, and more cost-effective flight.
Peeyush Pankaj is a Principal Application Engineer at MathWorks, where he collaborates with engineering teams across the Automotive, Aerospace, and Industrial Automation (IAM) sectors to develop and deploy AI-powered solutions for complex system challenges. Prior to MathWorks, he was at GE Aviation, working on the design, testing, and certification of aircraft engines and holds 25 patents in jet propulsion technologies and prognostic health monitoring. Peeyush holds a Master’s degree in Advanced Mechanical Engineering from the University of Sussex, UK.
Title:
Delivery: In-person
Time: Full day (with coffee/tea breaks and lunch break)
Class: Mix of theory + live exercises
Instructors: Prof. Li Xiaoli
Registration fee: Please refer to Registration page for more information
Abstract:
With the rapid rise of Generative AI, there is an urgent need to accelerate its adoption in industrial applications. This course provides essential insights into applying AI for key areas such as Quality Assurance, Predictive Maintenance, and Industrial Automation. Participants will gain exposure to practical use cases, understand the current limitations of Generative AI, and explore its transformative potential for manufacturing. The course also addresses the unique challenges of working with domain-specific data, ranging from images and text to the more complex realm of time-series data, while introducing specialized techniques designed to overcome these hurdles.
Through hands-on sessions, attendees will work with open-source Gen-AI tools, learn how to develop custom AI models using proprietary data, and envision the future of AI-driven manufacturing. By blending demonstrations, tutorials, and collaborative workshops, the course equips participants with actionable insights and practical skills to drive innovation, enhance productivity, and strengthen competitiveness within their organizations.
Who Should Attend
This training is specifically designed for CEOs, CTOs, technical leaders, engineering managers, supervisors, product managers, system designers, design engineers, R&D engineers, application engineers,, inspection and vision technicians, and new hires from various manufacturing sectors.
Instructor Bio:
Xiaolli is Head of the ISTD Pillar at SUTD, and an IEEE and AAIA Fellow. As the former Head of A*STAR’s Machine Intellection Department, he led Singapore’s largest AI and data science research group. With over 380 publications, 30,000 citations, and an h-index of 84, he is recognized among the world’s top 2% scientists for his contributions to AI. He has also driven over 10 major R&D collaborations with industry leaders such as DBS, Singtel, and KPMG, delivering innovative AI solutions across multiple sectors.