Every industry associated with the discipline of PHM is undergoing a digital transformation. This is especially so with the automobile sector, but other, more traditional disciplines are not far behind. Most standard-setting organization have taken cognizance of this shift and are responding to it with new documents outlining their approach to dealing with all the new technology. In the mobility sector, SAE International is constituting a number of technical committees to deal with digital transformation and to develop standards related to different aspects of the phenomenon. Digital communications and interoperability, Blockchain, Model-based design and testing, Artificial intelligence in safety critical systems, etc., are some of the topics being considered. Other organizations such as the A4A, IATA, IEEE, and ASTM are also developing standards in this area. This panel will bring together industry experts to discuss the latest progress in these fields.
1. David Alexander (SAE International)
2. Logen Johnson (SAE International)
3. Ginger Shao (Honeywell Aerospace)
4. Rhonda Walthall (Collins Aerospace)
5. Martin Whitfield (SAP)
6. Mark Roboff (DXC Technology)
7. Steve Holland (Retired - GM Research)
8. Dirk Berlee (KLM/Air France)
Background: Education and professional development are core enablers of the PHM Society to support its principles to: Provide free and unrestricted access to PHM knowledge; Promote interdisciplinary and international collaboration in PHM and Lead the advancement of PHM as an engineering discipline. Previous activities (http://www.phmsociety.org/forum/577) including panels have examined: A compilation of recommended types of PHM professional development in skills and mastery levels defined by the PHM Society Capability Taxonomy (Bird, Madge & Reichard, 2014 http://www.phmsociety.org/references/ijphm-archives), guidelines on quantitative goals for professional development over practical time periods and guidelines for preparing, evaluating and reporting plans and achievements. Last year’s panel identified a number of sources for existing courses including the Defence Acquisitions University.
Objectives: Examine the kinds of education and training available to the PHM community. Identify gaps and opportunities to access content to advance personal and organizational development aims. Prioritize actions for the PHM Society through its Education and Professional Development Committee.
Increasing electric and electronic content in modern day vehicles is bringing value to the customers but also adding to vehicle complexity. US-based OEMs and suppliers collectively paid about 7.4 billion USD in 2016 for warranty claims – with 50% or more related to electric or electronic components. With increasingly tight emission requirements and growing societal pressures, the auto industry is turning toward electric vehicles. More component sensing is possible than ever before, and more vehicles are boasting 4G connectivity that is essential to off-load data for cloud-based analytics. PHM demands a strategic approach aligned not only with company goals and product requirements but also linked into its field service support. This panel will explore the challenges and opportunities posed by the increasingly electrified automotive market and how PHM technologies can help mitigate warranty costs.
1. Pablo Valencia (Tentative), General Motors – Confirmed
2. Dr. Przemyslaw Jakub Gromala (Tentative), Robert Bosch GmbH (Confirmed)
3. Dr. Nilesh Kulkarni, NIO (Confirmed)
4. Aish Dubey, TI Automotive (Tentative)
5. Michael Nowak, Eaton (Tentative)
The future industrial internet of things (IIoT) will realize the connectivity of machine tools and online diagnostics and prognostics for improved product quality and asset utilization. But the question remains: How do we get there? Machine tools are vital for the production of high-value parts, and these machines will still be mechanical in nature, thus subject to wear and performance changes. One vision of IIoT is a future with maintenance systems with self-diagnostic capabilities that enable equipment to achieve and sustain near-zero breakdown performance. Parts should be produced with no unplanned downtime while reducing manufacturing costs and maintaining or increasing part quality. But how to do so? Manufacturers need smart machine tools with online abilities to assess their own health, so that production isn’t halted but enhanced. Through identification of current health and early signs of problems, smart machine tools with prognostic and health management (PHM) systems will give manufacturers the trusted information they need to optimize production. Currently, manufacturers are implementing their own PHM programs based around various sensors including MEMS accelerometers. This panel will bring together a diverse group of speakers from industry and academia to discuss online sensor-based solutions to transform machine tools into smart machine tools for the future IIoT. Discussion will focus around sensor-based PHM solutions for spindles and linear axes, which are the main elements of machine tools that affect part quality. However, another goal of the panel is to spur discussion to explore the potential impact of these relatively new approaches to other industries of interest to the PHM Society, such as transportation vehicles and energy production assets.
1. Jay Lee or Hossein Davari, University of Cincinnati
2. Andreas Archenti, KTH University
3. CahBum Lee, Texas A&M
4. Joel Neidig, ITAMCO
The panel will address PHM and other technologies in the design and operation of unmanned autonomous systems (aerial, ground, sea surface and undersea vehicles). Autonomous systems are attracting the attention of researchers and users in a variety of application domains from Intelligence, Surveillance and Reconnaissance to rescue operations, border patrol, driverless vehicles, driverless air taxis, undersea exploration, among others. It is documented that autonomous systems (UAVs, for example) are failing at alarming rates. PHM and related technologies aim to introduce new tools/methods for their resilient design and safe operation. The panel is inviting the participation of scientists/engineers, students and academics, company personnel, government personnel involved in autonomy and autonomous systems, conference participants interested to learn about the emerging autonomous systems technologies. Panel members and panel participants will discuss current and future technologies for improved system performance. Actual case studies and examples will be used to illustrate the technological innovations.
1. Graham Warwick (Sikorsky)
2. Jeremy Marvel (NIST)
3. Yao Cui (Kuka Robotics)
Several long-term career practitioners in the fields of PHM and CBM+ will share their experiences, observations, and lessons learned as part of this distinguished panel of experts. Much can be learned from the requirements generation, development, Verification and Validation, implementation, maturation, fielded use, fleet support, and enterprise-wide use of real world PHM systems. Just the development of the individual capabilities that make up a comprehensive and fully integrated PHM system; provides many lessons learned - both good and bad. A recently evolving important focused area will also be explored around the question: "just who really owns the data that these systems produce". These issues need to be discussed, documented, and viewed across the many industry sectors that are fielding PHM systems. Short presentations will be given by all panel participants that describe their particular topic area and experiences within the PHM/CBM+ domains. An open panel discussion will follow to explore some of these identified specific issues and concerns.
This session is focused on the development of Theoretical Aspects in Prognostics. In majority of the Prognostic and Health Management applications particle filtering-based algorithms are being implemented as the state-of-the-art. However, PF-based prognosis frameworks have demonstrated their drawbacks when trying to estimate the probability of failure in nonlinear, non-Gaussian systems performing uncertain operating profiles. To overcome this issue, it is first necessary to establish adequate performance metrics for the framework which has been discussed and presented in recent years. It has been observed that not much work has been done on standardizing prognostics definitions as they suffer from ambiguous and inconsistent interpretations.
The session plans to bring together academics and industry experts in the area to discuss about the lack of standards due to varied end-user requirements as well as varying application domains, including aerospace, automotive, nuclear power, electrical etc.
Predictive Health Management (PHM), originally applied in the Aerospace Industry, tries to predict when what part would fail for what reason(s) in order to make (preventive) maintenance more efficient and cost-effective. Over the past several years, PHM has been increasingly infused into the human healthcare, precision medicine, and human performance sectors. This panel discusses contributions in the fields of wearable smart sensors, sensor-data-fusion, machine learning and data mining, prediction and diagnosis, and electronic health records and databases - all in the context of prognostics and health management for human health and performance on Earth and in Space. Moreover, this panel builds on the discussions of the experience and processes encountered/created by the panelists, and highlights specific challenges, needs, and wants with respect to the development and implementation of standards and guidelines pertaining to PHM in the area of human health and performance. This diverse group of panelists will present their perspectives on PHM as it pertains to human assets. Conversations will include PHM's current and future envisioned applications within general healthcare, high stress work environments, sports/athletes, theatre, and space environments, along with how the needs, data stream, and supporting PHM tools, can be better designed, developed, implemented, integrated, verified, and validated to impact the new paradigm of smart healthcare.
The objective of our panel is to showcase the exciting world of Precision Agriculture and specifically the emerging revolution in Data-Driven agriculture.
1. Stan Martin(Mars Agricultural Research Consortium)
2. Dr. Prasad Thenkabail (USGS)
3. Dr. Keely L. Roth (Horticulture, The Climate Corporation, Bayer CropScience)