Nuclear power has the potential to provide safe, reliable, and highly available electricity with a low carbon footprint. Interest in nuclear power has grown in recent years, due in large part to the energy needs of advancing data centers, machine learning, and AI. Recent decades saw the premature closure of several plants due to economic challenges in the face of cheap natural gas. Operations and maintenance (O&M) represents the largest controllable day-to-day cost of producing nuclear power, and PHM provides an avenue to manage these costs. As we look to continue operation of our 94 operating plants, recommission previously shuttered plants, and build new reactors, there is a significant role for PHM to support the nuclear power industry. This panel will discuss current research and future trends for PHM in nuclear power applications.

• Stylianos Chatzidakis, Assistant Professor, Purdue University
• Sarah Creasman, Postdoctoral Researcher, Idaho National Laboratory
• Chris Poresky, Senior Manager Cyber-Physical Systems, Kairos Power
• Hao Huang, Senior AI scientist, GE Vernova

In an era defined by technology acceleration, many organizations still rely heavily on aging legacy systems, systems not originally designed for today’s connected, data-driven environments. The challenge? Sustain these critical assets while minimizing costs, avoiding unplanned downtime, and improving mission readiness.

This panel explores how organizations are transforming this disadvantage into a competitive edge by leveraging Digital RAMS Twin technology powered by sensor data. These digital replicas offer more than just monitoring, they offer Causation-based FDI (Causation-based AI) that can rapidly enable predictive maintenance, real-time risk assessment, and intelligent decision-making for sustainment activities. We’ll dive into how a Digital Risk Twin framework, like that offered by PHM Technology’s MADE platform, can seamlessly integrate with existing legacy infrastructure to deliver powerful insights across reliability, availability, maintainability, and safety (RAMS).

Attendees will hear real-world insights on:

• How to retrofit legacy assets with sensors to enable digital twin capabilities
• Using sensor-fed digital twins to automate diagnostics, predict failures, and extend system life
• Creating a closed-loop between field data and engineering to continuously improve sustainment strategies
• Case studies showcasing lifecycle cost reductions and improved availability

This is not about replacing legacy systems, it’s about empowering them. Learn how forward thinking organizations are turning lemons into lemonade by extracting new value from old assets using next-gen model-based RAMS tools and Digital RAMS Twins.

Join us and explore how to bridge the gap between yesterday’s hardware and tomorrow’s performance.

• Chris Stecki (CEO PHM Technology – Global)
• Amanda Haffey (Chief Reliability Engineering, Skypath Analytics)
• Kenney Crooks (Northrop Grumman Fellow, RM &T and Lifecycle Model based Sustainment)
• Robert Marsden (Product Manager – PHM Technology)

Predictive maintenance has moved far beyond theory. Today, it’s an operational reality supported by OEMs, airlines, and third-party providers worldwide. But where do we go from here?

This panel will bring together leaders who are shaping the future of prognostics and health management (PHM). We’ll explore the successes that have brought predictive maintenance to its current state, and tackle key questions about its evolution, such as:

• How can we “professionalize” predictive maintenance and ensure it is recognized as an essential capability rather than “recreational maintenance”?
• What steps are needed to move beyond a “cottage industry” to a mature, standardized practice?
• What lessons and breakthroughs can propel us to the next level?

Join us for an unflinching look at the opportunities and challenges ahead, and discover how industry pioneers are turning predictive maintenance into a strategic advantage.

• Alice Belcher (Delta Air Lines)
• Deepak Parameswaran (United Airlines)
• Justin Sindewald (Boeing)
• Nana Noel (GE Aerospace)

It has now been more than 1000 days since ChatGPT entered our lives, transforming how we write, research, query, retrieve information, and even code. What does this mean for the Prognostics and Health Management (PHM) community?

This panel will examine the growing impact of large language models (LLMs) on our daily work as PHM practitioners and their influence on PHM in practice. Based on a noticeable surge in PHM-related submissions referencing LLMs in the past year, the trend is clear: LLMs are becoming part of the PHM toolbox. The panel will ask and debate: what does the future of PHM look like in an LLM-augmented world?

The panel will cover topics including:

• Generative AI in practice: opportunities, limitations, and lessons learned from real-world use.
• Implications for PHM: how LLMs can support practitioners, bridge expertise gaps, and shape future methods.
• Looking ahead: what does the next 1000 days of LLMs in PHM look like?

• David He, University of Illinois at Chicago
• Oguz Bektas, University of Luxemborg

In the rapidly evolving field of PHM, career paths are as diverse as the technologies and applications that define the discipline. This panel brings together accomplished professionals from across the PHM ecosystem—ranging from academia and large corporations to small businesses and entrepreneurial ventures—to share the real stories behind their professional journeys.
Through open and candid discussion, panelists will reflect on the milestones that shaped their careers, including both major successes and the setbacks that tested their resolve. Attendees will gain insights into how these experts navigated critical decision points, adapted to change, built resilience, and found purpose in different roles and sectors.
Whether you are an early-career professional exploring options, a mid-career practitioner seeking direction, or a student envisioning your future, this session offers valuable lessons in career advancement, leadership, innovation, and perseverance in PHM.

• Cees Taal, SKF
• Ryan Aalund, Colorado State University, Samsara
• Juliana Vazquez, GE Aerospace/KBR
• Nana Noel, GE Aerospace
• Peter Sandborn, University of Maryland

This panel is made up of several “seasoned” experts who have been developing and implementing PHM related capabilities and technologies for a great number of years. This panel will use their experiences and stories to explore the issues, barriers, and lessons learned that have evolved across the many eras of PHM related activities including: requirements generation, capability benefits, ROI, justifications; development; validation & verification; policies; expanding applications; integration: implementation; operations, sustainment; enterprise-wide perspectives

• Kai Goebel, Fragum Global
• David He, University of Illinois at Chicago

As the automotive industry evolves toward electrification, autonomy, and software-defined architectures, Vehicle Health Management (VHM) must become more intelligent, scalable, and integrated across the full vehicle system. Current diagnostic and prognostic tools, while effective in specific subsystems, fall short of supporting the complex, connected, and evolving architectures of future vehicles. The next generation of VHM systems will need to operate across diverse platforms and evolving hardware/software stacks while maintaining performance, adaptability, and low development effort. This panel brings together experts from automotive , aerospace and AI domains  to define a research roadmap toward production-ready intelligent VHM systems in 2035+ vehicles. The panel will address how to advance diagnostics and prognostics across full-vehicle systems, and build robust, data-efficient health management systems capable of detecting complex, emerging, and rare issues across domains. In addition, it will explore how Generative AI (GenAI) and future AGI-like technologies might support in accelerating diagnostics and prognostics algorithm developments, system reasoning, model transferability and knowledge reuse.

• Xinyu Du, Tech Fellow, GM R&D
• Neil Eklund, Founder/Principal, Oak Grove Analytics, LLC
• Anuradha Kodali, Senior Manager, AI/ML Team, Lucid Motors
• Gary Larivee, Senior Engineer, Reliability and Maintainability, General Dynamics Land Systems
• Abhinav Saxena, Principal Scientist, AI and Computer Vision, GE Aerospace Research
• Peter Schmitt, Software Product Line Executive Director, Nexteer Automotive

The PHM Society works to advance PHM as an engineering discipline including through its Educational and Professional Development Committee. A Society hallmark is the synergy among industry, academia and public sector PHMers. What is exciting and satisfying about this domain are its diverse career opportunities (see the society’s evolving taxonomy of skills- Towards a Capabilities Taxonomy for Prognostics and Health Management | International Journal of Prognostics and Health Management (phmsociety.org). These panels at our last two conferences challenged some topics for discussion and identified opportunities for the Society AND you! We curating some prioritized discussion questions like:

• What are the key skills and competencies needed to excel in a PHM career?
• What else would industry supervisors wish that new grads arrived with?
• What are the opportunities and needs for industry to give back to academia?

• Harry Julijanto, Rolls Royce
• Ed Baumann, Trident Systems
• Huan Huang, Emerson

Previous standards panels and debates have identified strong opinions about the 100+ PHM standards:
https://phm2024.phmsociety.org/wp-content/uploads/sites/14/2024/12/Panel-05-PHM-2024-standards-debate-with-results.pdf 

It’s time for you to hear about the latest PHM-related standards from the main standards developing organizations (SDOs). And it’s an opportunity for “consumers” of standards to ask questions and learn how standards can better benefit their work and research… and to learn how standards can benefit from “consumers” experiences, too!

The aim of this panel is to learn about published PHM-related standards and those in development as well as experiences, results, gaps, and opportunities for standards to better serve the PHM community. As we prepare for the panel, please let us know what you most want to hear about including AI/ML, ROI, data sharing/governance, cyber, consortia, synergy across sectors/domains, etc.

Fun is encouraged. A vote on issues to pursue and minutes will be recorded.

Please come, contribute and enjoy!

• Abhinav Saxena, Principal Scientist, GE Aerospace
• Dave Larsen, Senior Technical Fellow, Collins Aerospace
• Ed Manns, Managing Director, External Relations, International Society for Automation (ISA)
• Justin Cassamassino, S&C Project Engineering Advisor, ASME
• Mark Walker, Director of AI, Autonomous Systems, E3S

Building on the insights from our first panel on maximizing existing capabilities, this session takes the discussion a step further: What if predictive maintenance was built into platforms from the very start?

With a global shortage of skilled maintainers and increasingly stretched supply chains, the stakes are high. This panel will explore what’s needed to overcome these challenges and seize the opportunities ahead.

Industry leaders and innovators will discuss subjects such as:

• How to integrate health management into the initial design of new platforms
• The requirements, technologies, and strategies needed to make predictive maintenance a core capability from day one
• How designing for maintenance can drive resilience, efficiency, and operational readiness at scale.

Join us to discover how the next generation of platforms can embed PHM as a foundation — not an afterthought.

• Sudipto Ghoshal, QSI
• Rhonda Walthall, Collins Aerospace
• Dave Larsen, Collins Aerospace
• Brian Shaflik, Boeing