Panel Session Topics

• Smart Manufacturing PHM
• Asset and Operations Management: A Maritime Industry Focus
• Commercial Aerospace PHM/IVHM
• Railway PHM
• Data Analytics in the Era of Industrial IoT

Panel Session Details

Smart Manufacturing PHM
Session Chair: Prof. David He, University of Illinois at Chicago, USA

Description:
As manufacturing environments become more complex, fault and failure opportunities increase throughout the factory. Manufacturing complexity can stem from many factors including greater flexibility and reconfigurability in manufacturing processes (to leverage new technology and/or support product customization. This complexity forces manufacturers to assess and re-assess areas of risk within their manufacturing processes. Those areas of greatest risk often become ideal targets for PHM. Including PHM (i.e., condition monitoring, diagnostics, and prognostics) can increase operational efficiency and decrease downtime. This panel highlights capabilities, best practices, challenges, needs, and wants with respect to the development and implementation condition monitoring, diagnostics, and prognostics to enhance maintenance and control strategies within the manufacturing environment. This diverse group of panelists will present their perspectives on PHM within Smart Manufacturing. Conversations will include PHM's current and envisioned applications within factory environments along with how the needs, data stream, and supporting PHM tools, can be better designed, developed, implemented, verified, and validated to impact smart manufacturing.

Background:
This panel both builds on the discussions of the experience and processes from the PHM16 Manufacturing Panels:
https://www.phmsociety.org/events/conference/phm/16/panel-sessions
A special issue on Smart Manufacturing PHM of the PHM Society's IJPHM is available at:
http://www.phmsociety.org/references/ijphm-archives/2016/Sp5

Possible List of Panelists:

1. Prof. David He, University of Illinois at Chicago, USA
2. Prof. Diego Galar, Luleå University of Technology, Sweden
3. Prof. Sang Won Lee, Sungkyunkwan University, Korea
4. Prof. Qingkai Han, Dalian University of Technology, China

Asset and Operations Management: A Maritime Industry Focus
Session Chair: Andy Hess, President of PHM Society, USA

Description:
Digitalization of the maritime industry is accelerating fast currently, and is likely to have great impact on industry maintenance practices in the years to come. Digitalization is also expected to accelerate prognostics and health management uptake in maritime. The panel session aims at gathering PHM professionals and interested stakeholders from the maritime industry to discuss and learn from each other as well as the wider PHM community. The goal is an increased uptake of PHM technologies in maritime and, in the longer term, for maritime to contribute more to the PHM community than today. PHM uptake in maritime has thus far been small, perhaps due to the isolation of a ship on long voyages. This isolation is now lifted by digitalization and communication technologies, which may change the situation.

Recently, there has been a downturn in the demand for shipping capacity, which has led to overcapacities and low freight rates. In the light of this, there is a great incentive to optimize maintenance and operations, and PHM technologies offer a way towards improved utilization of resources by reducing the amount of preventive maintenance while increasing predictive maintenance and at the same time reducing cost.

The panelists will represent different stakeholders in the maritime industry, and will present their background and experiences. A discussion will follow with viewpoints on how they think PHM technologies might best be implemented and benefitted from in maritime given the market forces and stakeholder structure. The panel will conclude with a discussion about how they see PHM in maritime developing in the near future, and how digitalization can support this.

Background:
This panel both builds on the discussions of the experience and processes from the PHM16 Big Data Analytics and Fielded Systems Panels:
https://www.phmsociety.org/events/conference/phm/16/panel-sessions
A special issue on Big Data and Analytics of the IJPHM is available at:
http://www.phmsociety.org/references/ijphm-archives/2016/Sp6

List of Panelists:

1. Lars-Erik Saarinen, Rolls Royce, Finland
2. Prof. Ian Jennions, Cranfield University, UK
3. Prof. Diego Galar, Luleå University of Technology, Sweden

Commercial Aircraft PHM/IVHM
Session Chair: Kurt Doughty, UTC Aerospace Systems, Singapore

Description:
This panel session will explore the value of commercial integrated vehicle health management for aerospace platforms. Experience in applying PHM and other asset management technologies will be highlighted. Specific goals that will be addressed include implementing IVHM to lower the cost of ownership, to enhance safety, and to generate revenue. Panelist will be encouraged to lead the discussion with specific needs and opportunity challenges for the PHM community

Background:
This panel both builds on the discussions of the experience and processes from the PHM16 Big Data Analytics and Fielded Systems Panels:
https://www.phmsociety.org/events/conference/phm/16/panel-sessions
A special issue on Big Data and Analytics of the IJPHM is available at:
http://www.phmsociety.org/references/ijphm-archives/2016/Sp6

List of Panelists:

1. Lionel Delle Vedove, Airbus, France
2. Torbjörn Fransson, Saab AB, Sweden
3. Masaru Nishiwaki, ANA, Japan

Railway PHM
Session Chair: Parham Shahidi, PARC

Description:
Railroads play an essential role in today's global economy. As the most efficient land-based mode of transport for freight and the most reliable commuting method for passengers, both freight and passenger rail enable economies to operate reliably, safely and cost efficiently. Given the global pervasiveness of the railroads, making this transportation mode even more reliable and efficient is of paramount importance.
Emerging technologies such as Machine Learning and Big Data are promising candidates to unlock greater utilization by changing existing maintenance practices towards condition based maintenance. Both, mechanical assets such a locomotives and railcars as well as infrastructure assets such as tracks will benefit from this change, as maintenance and impending failure become predictable. Successful implementations include monitoring track geometry/rail condition, brake systems, and wheel health to name a few.
While the predictive capabilities are improving, other factors that are integral for the success of Railway PHM still require more attention. These include data acquisition, storage and transmission on unpowered assets such as freight railcars, network infrastructure for monitoring train make up, and lastly, creating appropriate value chains to offset initial investment costs.
The panel is made up of experts from various railroad markets across the globe and will thus offer a well-rounded overview of differing perspectives. The panelists will present their unique backgrounds and discuss their experiences with Railway PHM projects and the impacts PHM has been able to make. The panel will be concluded with a discussion about the future of Railway PHM, where the panelists see the most pressing need for improvements, and where the greatest opportunities are.

List of Panelists:

1. Dr. Raphael Pfaff, FH Aachen, Germany
2. Dr. David Siegel, Predictronics Corporation, USA
3. Dr. Hyun Wook Lee, Korea Railroad Research Institute, Korea

Data Analytics in the Era of Industrial IoT
Session Chair: Dr. Abhinav Saxena, GE Global Research

Description:
As PHM applications become more mature and find their way into fielded systems, the next frontier is to build and deliver PHM at scale. With the advancement in machine learning, AI, and cloud based computing platform technologies, PHM finds itself morphing into one of the key pillars for IoT and industrial internet. While, availability and use of cloud-based analytics platform enables connectivity and myriad of opportunities to deliver PHM to a large number of assets, it also requires PHM to adapt to take advantage of high speed and high volume machine data, which in turn requires new paradigms of how PHM systems are built. On the other hand, PHM also drives requirements for these new age computing platforms to provide suitable connectivity and compute to fit industrial environment, which are often quite different than consumer internet applications.
This panel will explore these various aspect of industrial analytics, including industrial data science and big data analytics. Panelists will discuss current trends, challenges, and requirements posed by enterprise analytics. Concrete cases of implemented approaches in many industry sector applications will be discussed including specific software capabilities and tools from our community of developers, suppliers, and users.

List of Panelists:

1. Dr. Abhinav Saxena, GE Global Research, USA
2. Prof. Seungchul Lee, Ulsan National Institute of Science and Technology, Korea
3. Prof. Diego Galar, Luleå University of Technology, Sweden
4. Prof. Myong-Kee Jeong, Rutgers University, USA