Photo Courtesy of Visit Detroit

Program Schedule
Technical Program:

Title: Fail-safe and fault tolerant designs: Methodologies and examples in transportation
Panel sponsor: IEEE Transportation Electrification Community
Panel organizer and moderator: Dr. Bruno Lequesne, E-Motors Consulting, and IEEE TEC Chair
Designs of automotive systems have increasingly taken failure modes into consideration, as part of a broad view of functional safety. For automakers, this is a matter of brand image, avoidance of warranty cost, and for some subsystems (such as steering or brakes), a matter of actual safety. In this panel, we will look at the philosophy and approaches behind such designs, focusing on examples around electric motor drives (used for traction or steering) and software (used ubiquitously around the vehicle). A fail-safe /fault tolerant design means the ability to drive home safely, or at the very least “limp home”. Some approaches have to do with the design itself, and other aspects include the detection of incipient faults, all with careful attention to getting the best results at a minimum cost.
Dr. Brian Murray, Senior Director Product Safety and Cybersecurity, Luminar Technologies. Dr. Brian Murray is Senior Director of System Safety and Cybersecurity at Luminar. Previously, he led System Safety and Product Cybersecurity at ZF. Brian has been active in system and functional safety for over 25 years and in cybersecurity for 10 years. He has also led functional groups and project teams in advanced embedded systems, including aerospace and commercial building technologies as well as automotive systems. Brian received his Ph.D. in Computer Engineering from The University of Michigan, his master's degree in Electrical Engineering from Duke University and a bachelor's degree in physics and mathematics from Albion College. He has published over 60 technical papers and has 10 US patents.
Dr. Raja Ramakrishnan, Chief Scientist, Halla Mechatronics. Dr. Ramakrishnan Raja received B.Sc. degree from Amrita Institute of technology, India in 2003 and Master’s Degree in electrical engineering from New Jersey Institute of Technology, in 2005. He received his Ph.D. degree in automotive system engineering from University of Michigan-Dearborn, MI. From 2004-2013 he has been working for Delphi steering and Nexteer automotive as Senior Electrical Engineer. Currently he is working at Halla mechatronics as Chief Scientist-Controls. He is responsible for motor drive /Vehicle Dynamics control for various automotive applications. His research interest includes electrical machines and variable speed drives including sensorless motor control drives. His recent works includes developing redundant motor drive architecture (for steering) with complete redundancy such that there is no reduction in system performance after a single point failure. He is presently the Associate Editor for Industrial Drives Committee and Transportation System Committee.
Prof. Shanelle Foster, Michigan State University. Prof. Shanelle N. Foster received B.S., M.S., and Ph.D. degrees in electrical engineering from Michigan State University, East Lansing, MI, USA, in 1996, 1998 and 2013, respectively. She is currently an Assistant Professor in the Department of Electrical and Computer Engineering at her alma mater, where she co-directs the Electrical Machines and Power Electronics Research (EMPowER) Laboratory. Her research interests include analysis, control, reliability, and manufacturability of rotating and linear electrical machines and drives

Title: PHM Standard
Panel organizer and moderator: Mr. Lou Gullo, IEEE RS VP of Technical Activities (TA) and the Chair of the IEEE Reliability Society Standards Committee (IEEE RS SC).
The panel will discuss their involvement in developing standards for PHM, such as IEEE 1856, the Standard Framework for Prognostics and Health Management of Electronic Systems, and the potential to develop future standards that align with IEEE 1856, such as proposed standard, IEEE P1856.1, a guideline or recommended practice for PHM systems. This panel will be a continuation of the topic discussed in the Tutorial session on IEEE PHM Standards at the conference prior to this panel session. The panel will describe how IEEE 1856 is a normative framework for classifying PHM capability and for planning the development of PHM for an electronic system or product. The panel will explore areas in IEEE 1856 that may be improved and expanded for a future revision. The panel will present various aspects of PHM designs in electronic systems, including definitions, approaches, Machine Learning (ML) data driven methods and algorithms, physics-based models, condition or health monitoring equipment, sensors and sensor selection, sensor and diagnostic data collection, data storage and analysis, decision and response effectiveness, life cycle cost benefits, and Return on Investment (ROI). The panel will also discuss the potential to create new standards that are derived and support IEEE 1856.
Mr. Leopoldo Mayoral graduated from the University of Texas in 1974, received a commission in the U.S. Navy, was designated a Naval Flight Officer and served in various positions of increasing responsibility aboard four aircraft carriers and two operational staffs as Electronic Warfare Officer. Commander Mayoral earned a Master’s Degree and Degree of Engineer in 1980 and 1981 respectively from the Naval Postgraduate School in Monterey, CA, graduated from the National War College with a specialization Space Studies in 1992 and later earned a Masters in Applied and Computational Mathematics from Johns Hopkins University in 2011. Mr. Mayoral served with the National Reconnaissance Office assigned as a program manager for a national intelligence program of greatest national importance. Retiring from the U.S. Navy after 26 years of active duty, Mr. Mayoral established a consulting business, Mayoral Systems Analytics, providing systems engineering technical services in the areas of space-based intelligence systems to the Missile Defense Agency for the Ground-based Missile Defense program and other defense programs. In 2008, Mr. Mayoral accepted a position with the Johns Hopkins University Applied Physics Laboratory (JHU APL) and has made significant technical contributions on intelligence, aircraft and missile defense programs in addition to his technical contributions to the IEEE PHM Standard. Commander Mayoral is highly decorated for his achievements in military acquisition and operational accomplishments during his military career. He holds a Program Management DAWIA Level III Certification (1995) and has his EIT license, Washington, DC (April 1994).
Mr. Rex Sallade is a retired engineer who spent 37 years designing, developing and testing diagnostics, prognostics, and health management systems and related technologies. Rex worked for Texas Instruments and while there designed and implemented testability hardware and diagnostic software in a wide variety of systems. Rex became the manager of the Diagnostic Test Group at TI and led that group in developing testability at all levels of design, from the implementation of hardware testability features in integrated circuits to the development of diagnostic and prognostic hardware and software at the system level. That included such systems as the Javelin shoulder fired anti tank missile and launcher, the GPS 4100 navigation system, and the M1 A2 tank Hull and Turret Electronic Units. Rex worked to support the development and ultimately the adoption of IEEE 1149.1 Test Bus Standard which is now implemented in virtually every system, small and large. After leaving TI, Rex joined Northrop Grumman where he worked for seven years, supported the development of IEEE 1856 and eventually becoming the Chief Systems Engineer for PHM on the F35, Joint Strike Fighter. After leaving Northrop, Rex went to Sikorsky Aircraft where worked for 7 years and led the development of PHM in the CH-53 K, the new US Marine Corps heavy lift helicopter. In his last years there, he managed the diagnostics group which implemented PHM on a number of other new helicopters. Rex now enjoys spending more time with his wife Argentina, their sons and daughters and their 7 grandsons. He also enjoys woodworking and building and racing cars, including one 4th place finish in the annual Big Bend Open Road Race.
Mr. Lou Gullo. Over 35 years of experience in system, hardware, and software reliability, maintainability, testability, prognostics, safety, security, and fault management for the military, space, telecom, and commercial electronics industries. Awarded a US Patent in January 2004 for Reliability Assessment Program (RAP). Editor/author of 3 books. Leads the Condition-Based Maintenance Plus (CBM+) Prognostics and Health Management (PHM) team on the Ground Based Strategic Deterrent (GBSD) Program at Northrop Grumman. Also leads Design for Testability (DfT) and Software Reliability functions on the program. Senior member of IEEE, chair of the IEEE RS Standards Committee, and IEEE RS VP of Technical Activities. Founder of the IEEE RS Arizona (AZ) Chapter. Retired Lieutenant Colonel, US Army, Signal Corps. IEEE Reliability Engineer of the Year award in 2016.
Mr. Brad Cline is the Manager of the AI & Analytics team in the Solutions Consulting group at PTC. The team is responsible for guiding Industrial organizations in applying Advanced Analytics including Machine Learning to Manufacturing and Product Service use cases. Earlier in his 11+ years at PTC, Brad was the Global Quality Practice Lead responsible for implementation of Quality and Reliability Engineering systems. This role was a continuation of his work as Professional Services Manager at Relex Software. While at Relex, Brad was an ASQ Certified Reliability Engineer and participated in the update of the MIL-HDBK-217 standard. He has contributed to and presented multiple papers and tutorials at RAMS symposiums over the last 15 years. Brad has a BS in Applied Mathematics (Operations Research) and Industrial Management from Carnegie Mellon University and an MBA from the University of Pittsburgh.

Special Session:

Intelligent Monitoring and Optimization for Smart Manufacturing System

Simulated Data for Prognostics and Health Management