IEEE International Conference on Prognostics and Health Management
Monday, 19 June 2017 | Courtyard Marriott | Allen, Texas
Agenda | Presentation Titles & Abstracts
Presentation Titles & Abstracts
Adam Drobot - OpenTechWorks, Inc.
Title: "The Key to the Internet-of-Things: Conquering Complexity One Step at a Time"
The Internet of Things (IoT) is growing at a vigorous pace and is recognized as an important thrust that will impact almost all segments of the World Economy. The phrase "IoT" evokes many different ideas that vary significantly from vertical to vertical and from market to market. The talk will cover the different views of IoT and identify similarities and differences, and examine the likely paths that the evolution of IoT may take. It will also address the trend of how IoT implementations are increasingly relying on common infrastructure with profound consequences for how we deal with quality, reliability, and security for critical functions.
Keith Gremban - NTIA
Title: "Wireless Communications and the Internet of Things (IoT)"
The Internet of Things (IoT) consists of devices connected to each other and the Internet. Some analysts project as many as 50 billion "things" connected by 2025. Other trends project that as many as 97% of these devices will be connected wirelessly. In this talk, we will discuss the trade between computing and communications in developing the systems architecture for an IoT application. We will also present some of the challenges posed by the scale and density of wireless devices forecast for IoT.
Lee Stogner - Vincula Group
Title: "Aspects of the Internets of Things: A view from different Manufacturing Industries"
The accelerating deployment of IoT in the Industrial landscape has focused on the operational aspects of critical applications. Among these are the use of monitoring of machinery and processes, and the interpretation of data to predict necessary maintenance operations and real time preventive actions. The paradigm is the use of IoT to exercise a control loop - sense-gather data-analyze and predict- decide-take action-repeat. The presentation will cover how this is done in manufacturing industries that have very different needs and require distinct IoT Architecture styles. One important factor is that, what is manufactured and how varies, by production numbers - big complex systems where one builds a limited number per year such as aircraft, ships, trains, the middle ground in the 100,000 - 1,000,000 such as trucks, farm machinery, elevators, and lastly consumer electronic goods and components such as chips, cell phones, tablets and PCs where the numbers are in the 100,000,000 range. The presentation will cover both the economics of IoT application solutions and the technical challenges.
Rick Durham - IBM
Title: IOT Predictive Maintenance: Building Predictive Vibration Analysis Models
The purpose of the “IOT Predictive Maintenance: Building Predictive Vibration Analysis Models” presentation is to present and demonstrate a proposed methodology/practice for predicting bearing failures using predictive models built using FFT data. Such models can be embedded on edge devices or used in on prem or cloud based systems with the simultaneously lowering the amount of data being transmitted across the Network.
Mike Garcia - BNSF
Title: IoT in the Rail Industry'
BNSF Railway operates over 1,200 trains per day across more than 32,000 miles of track in 28 states and three Canadian provinces. BNSF leads the rail industry in technical innovation. Sensor technology monitors locomotives, rail cars, track, and facilities and the information generated from these sensors is captured, analyzed, and acted upon in a timely fashion. BNSF is leveraging industrial scale IoT solutions to improve safety, efficiency, and availability for its employees and customers.
Byung K. Yi - Interdigital
Title: “IoT Network Quality and Reliability”
This presentation will cover general reliability theory, to bring everyone up to the same level of knowledge, based on common “quality and reliability” concepts. The presentation will then address and propose three significant approaches for different aspects of IoT Reliability:
- Inherent Graceful Degradation
- Duty Cycle capabilities for intermittent operations found in many sectors;
- IIoT (Industrial IoT) which requires continuous operation with extremely high reliability.
Voy Grohman - ID Systems
Title: "IoT and Reliability: Practical Examples and Good Practices"
Measures of reliability vary and constantly change in the industry. The talk will start with showcase examples of different product reliability measures currently used by successful companies. It will then focus on ways to more accurately measure and improve product quality using an IoT tool set.
In the end, the talk will attempt to demystify current IoT trends used in reliability measurement and prognostics. Major pitfalls to avoid and main recommendations will be explained.
Tim Finigan - Fluor
Title: "Life Cycle Analysis & Operational Readiness for Capital Projects"
A key question for the Prognostics and Health Management (PHM) community is – how best to initiate PHM applications into plant or business operations? From our experience working with major industrial clients, introduction of PHM methods and technologies is best accomplished in conjunction with major capital projects, but doing so requires involvement of operations management into the capital design process using early business case justification approaches.
Life Cycle Analysis is a key Value Improving Practice used during engineering, procurement and construction (EPC) projects to systematically apply life cycle based value analyses to project design considerations and optimize Total Cost of Ownership (TCO) over an asset life-cycle. The distinguishing characteristic of projects applying Life Cycle Analysis are the structure, consistency and pervasiveness of the application of analytical models for design decisions and the resulting potential for significant PHM applications to enhance process and product reliability and optimize capital and operating costs, energy management, process yield, useful life and plant throughput.
Early Life Cycle Analysis activities and TCO models can clearly define alternatives and support business decisions to apply PHM approaches to select desired options based on operability, maintainability, or reliability functions. Such approaches need the involvement of operations personnel engaged in parallel with the capital program EPC phases from design through production startup and handover. The overall process of analysis, planning, development and execution for operations is often referred to as Operational Readiness and can comprise hundreds of specific analyses, tasks and deliverables to best design and implement a plan for on-going operational excellence.
Based on Fluor’s experience in launching new plants, we have developed an approach to Operational Readiness that we call UpFRONTSM. This methodology is a structured process of life cycle design, operational planning and development of programs, processes and systems that best prepares for operations and reliability excellence and can be used as an optimal entry point for the definition, selection and implementation of PHM applications into an integrated EPC design and startup approach that fulfills the business case requirements of a new capital program.Ashish Jain - GE Ventures
Title: " Mechanizing Industrial Asset Inspections and Integrity Assessments"
Mechanizing industrial asset’s integrity assessments is a very promising use case for the Industrial IoT technologies. Traditional industrial asset inspection requires collection of various data related to asset’s condition and specific analytics for assessing the asset’s integrity. These inspection methods rely on mostly manual processes for data collection, analysis, and reporting. Connected sensors, robotics, and AI technologies are a game changer as they cannot only automate but also improve quality of inspections. I will discuss how Avitas Systems (a GE Venture Company) is leveraging robotics, smart sensing, data fusion, and deep learning technologies to bring intelligent industrial inspection solutions to the marketplace. We will discuss specific visual inspection use cases that can be substantially automated using robots and deep learning approaches.