PHM19 Technology Demonstration
Technology Demonstration Description and Proposal
The PHM Society invites our conference sponsors to show off their diagnostic and prognostic engineering approaches through PHM Technology Demonstrations. The concept of the demonstrations is to offer a true “hands-on” learning experience for attendees. Multiple demonstrations will be given as brief tutorials to small groups. Each demo will last 30 to 60 minutes, where attendees will be encouraged to actively participate.
All Tech Demo presenters also have the option to submit a 1-page flyer/brochure to be included on the conference website, as well as additional recognition in the printed conference program. The single page on the website will be in the company’s desired format.
Please submit proposals and questions to the chairpersons listed below by May 27, 2019 August 23, 2019.
Click here to learn more about these funding opportunities.
Interested parties should submit a brief proposal of their PHM technology demonstration, including:
- Demonstration description
- Methods of attendee interaction planned (the more, the better)
- Educational value
- Display requirements (tables, projector/screen, audio, etc.)
- Storage and transportation needs
NOTE: Demonstration content (hardware, software, concepts, material, and data) must be cleared for public release.
Technology Demonstration Attendance Sign-Up Process
All conference participants are invited to attend the interactive, “hands-on” technology demonstrations. There are multiple demonstrations from which to choose (see below for details). Due to limited space, attendees must sign-up in advance at the demo conference rooms. Time slots are allotted to attendees on a first-come-first-serve basis on the sign-up sheet.
Technology Demonstration Topics and Presenters:
- Tech Demo 1: Condition Indicator Design & RUL Estimation using MATLAB (Rachel Johnson and Sudheer Nuggehalli, MathWorks)
- Tech Demo 2: Connected Ecosystem for Aerospace Intelligence and PHM (Kurt Doughty and Dave Larsen, Collins Aerospace)
- Tech Demo 3: Honeywell Forge Platform (Ginger Shao, Honeywell)
- Tech Demo 4: Industrial AI Paving the Path for Digital Transformation (Piyush Modi, NVIDIA)
- Tech Demo 5: Testability Engineering And Maintenance System (TEAMS) Toolset (Deepak Haste and Sudipto Ghoshal, QSI)
- Tech Demo 6: Asset Answers Make Work History Work for You (Mark Hu, GE Digital)
- Tech Demo 7: Health-Ready Components and Systems / ExchangeWell Digital Data Marketplace (Ben Towne, Steve Holland, Leon Gommans, and Drasko Draskovic, SAE Industry Technologies Consortia)
Technology Demonstration Schedule
|9:00 – 10:30||Tech Demo 1: Condition Indicator Design & RUL Estimation using MATLAB||Rachel Johnson and Sudheer Nuggehalli, MathWorks|
|10:45 – 12:15||Tech Demo 2: Connected Ecosystem for Aerospace Intelligence and PHM||Kurt Doughty and Dave Larsen, Collins Aerospace|
|1:30 – 3:00||Tech Demo 3: Honeywell Forge Platform||Ginger Shao, Honeywell|
|3:15 – 4:45||Tech Demo 4: Industrial AI Paving the Path for Digital Transformation||Piyush Modi, NVIDIA|
|10:45 – 12:15||Tech Demo 5: Testability Engineering And Maintenance System (TEAMS) Toolset||Deepak Haste and Sudipto Ghoshal, QSI|
|1:30 – 3:00||Tech Demo 6: Asset Answers Make Work History Work for You||Mark Hu, GE Digital|
|3:15 – 3:45||Tech Demo 7a: Health-Ready Components and Systems||Ben Towne, Steve Holland, Leon Gommans, and Drasko Draskovic, SAE Industry Technologies Consortia|
|3:45 – 4:45||Tech Demo 7b: ExchangeWell Digital Data Marketplace|
Technology Demonstration Summaries
|Tech Demo 1: Condition Indicator Design & RUL Estimation using MATLAB
Presenter: Rachel Johnson and Sudheer Nuggehalli, MathWorks
|This session will show how you can use signal processing and machine learning, and dynamic modeling techniques in the Diagnostic Feature Designer App to design condition indicators that can monitor the health of a machine without writing any MATLAB code. You can then estimate its Remaining Useful Life (RUL) or analyze the root cause of a fault using machine learning models for classification and regression. The demo will also show how these condition indicators can be deployed to embedded devices such as PLCs or IT systems and cloud platforms.
Capabilities demonstrated will be from the new Predictive Maintenance Toolbox in MATLAB.
Attendees will be able to interact with the presenters and see how they can evaluate different techniques and modeling methods for developing their algorithms. If possible, we will try and bring a small hardware setup with a servo motor that can be placed under different fault conditions. The data from these faulty conditions can then be analyzed in MATLAB.
|Tech Demo 2: Connected Ecosystem for Aerospace Intelligence and PHM
Presenter: Kurt Doughty and Dave Larsen, Collins Aerospace
|Collins Aerospace will demonstrate portions of its aircraft health network, including wireless routers/sensors and Collins Aircraft Interface Device (AID). The AID is integrated with services and software to create a complete, ready-to-use solution designed from the ground up with connectivity and cybersecurity in mind. In addition to on-aircraft applications, the demonstrated hardware enables transfer of aircraft data to ground stations and Ascentia®, Collins cloud-based advanced prognostics and health management (PHM) solution. Ascentia aggregates various data sets and utilizes powerful visualization tools to provide customized, predictive and actionable information that enables airlines to make strategic service decisions. Collins’ PHM analytics transform data into actionable information to ensure more timely and effective aircraft maintenance. Ascentia will be demonstrated and available for conference attendees.|
|Tech Demo 3: Honeywell Forge Platform
Presenter: Ginger Shao, Honeywell
|Honeywell Forge is a powerful analytics software solution that provides real-time data and visual intelligence. Connectivity is based on an extensible platform that is portable for deployment in any cloud or data center environment. It provides an enterprise-wide, top to bottom view, displaying the status of process, assets, people, and safety. Applications to connected aero and plants will be demoed.|
|Tech Demo 4: Industrial AI Paving the Path for Digital Transformation
Presenter: Piyush Modi, NVIDIA
|As recent data has shown we have created 90% of the world’s data in the past two years, research is also showing that most advanced industrial sectors are harness less than 5% of the data they have access to !!
Most industrial digital transformation investments have given us connected assets , cloud hosted platforms, agile DevOps and transformed work culture , yet it is far from realizing the promise of zero unplanned downtime and promised 1% efficiency, reliability and safety improvement related economic benefits. In the post Moore’s law era,. we are seeing Industrial AI powered by GPU Accelerated compute is delivering the outcomes not seen before by harnessing data produced by connected assets and complex processes. In this Demo Showcase talk we will provide use cases from various industrial segments (e.g. manufacturing, semiconductor, aerospace, energy and transportation) and related technology and outcomes that is enabling reliable, efficient and safer operations and processes. Through live demonstration, we will share details of NVIDIA’s edge (EGX) to cloud Industrial AI platform and related ecosystem that is powering a continuously learning industrial grade AI powered Predictive Maintenance, Inspection and Logistics solutions.
|Tech Demo 5: Testability Engineering And Maintenance System (TEAMS) Toolset
Presenter: Deepak Haste and Sudipto Ghoshal, QSI
|QSI’s Technology Demonstration will show how one can use the Integrated Diagnostic and Prognostic capabilities of Qualtech Systems Inc. (QSI)’s TEAMS (Testability Engineering And Maintenance System) Toolset to guide technicians and customers through the process of diagnosing and troubleshooting a broad range of complex electro-mechanical equipment and systems.
The demo will begin with the explanation of QSI’s multi-signal modeling concept, the core of QSI’s Model Based Systems Engineering (MBSE) approach towards Field Maintenance and Remote Support. QSI will demonstrate its graphical modeling tool, TEAMS-Designer, and show how a cause-effect model of a system is used to improve overall reliability and generate optimal diagnostic strategies. Various analysis capabilities such as Testability Analysis, FMECA (Failure Mode, Effects and Criticality Analysis), FTA (Fault Tree Analysis), etc. will be shown.
Next, we will be showing how the same TEAMS model of the system can be used to conduct Real-time Health Monitoring and Guided Troubleshooting through the use of QSI’s enterprise-grade software, TEAMS-RDS (Remote Diagnosis Server).
The tech demo will familiarize users with multi-signal modeling fundamentals, and show how they can create system representations from an MBSE perspective. Additionally, by utilizing features such as “Design For Testability (DFT)” and “Test Recommendations”, we will demonstrate how to improve the “testability” related qualities of the model.
The tech demo will also provide background information about maintenance concepts such as Diagnose Before Dispatch (DBD), Condition Based Maintenance (CBM) – and how it differs from Reactive/Unscheduled Maintenance.
|Tech Demo 6: Asset Answers Make Work History Work for You
Presenter: Mark Hu, GE Digital
|Many industrial companies would like to take advantage of their volumes of data in order to incorporate data-driven decision making into their business processes, but how? There are many recommended work processes out there for improving reliability and maximizing maintenance – how do we integrate data into these processes? Often in industry there is a gap between raw collected data and actionable insights – how do we fill this gap and integrate such insights into our business?
Asset Answers helps answer many of these questions. GE Asset Answers aggregates millions of work history and equipment records from the CMMS/EAM (Computerized Maintenance Management Systems/Enterprise Asset Management) from industrial facilities around the world. There are millions of historical maintenance activities recorded on millions of assets across different verticals in the Asset Answers database, which can be used to characterize different maintenance strategies, different commonly occurring failures, and characterize failure patterns and their cost. This data is anonymized and made available to subscribers who can compare themselves against peer data. Reliability engineers can dispense with spending a bulk of their time on data processing and aggregation, and have data at their finger-tips, ready for analysis as soon as they login to Asset Answers. By incorporating data into decision making, AA along with APM, enables an organization to go from reactive (fire-fighting) to proactive (predicting and preventing failures).
|Tech Demo 7: Health-Ready Components and Systems / ExchangeWell Digital Data Marketplace
Presenter: Ben Towne, Steve Holland, Leon Gommans, and Drasko Draskovic, SAE Industry Technologies Consortia
|SAE Industry Technologies Consortia (ITC) announces the launch of a new Health-Ready Components & Systems Strategy Group consortium, to accelerate adoption of “health-ready” components & systems that are capable of reporting on their own health status to support diagnostic and/or prognostic capabilities, allowing for more accurate proactive scheduled maintenance and fewer costly breakdowns. This presentation describes a brand-new blockchain-backed registry of component capabilities and endorsements from integrators indicating availability of more detailed technical information, intended to promote the more rapid development of a market in which health-ready features (as discussed in SAE’s JA6268 standard) are valued and easier to find.
The availability of more data is an enabler for the data scientist that allows new approaches when constructing AI based algorithms or, during the training phase, achieve higher accuracy. Challenges arise when such data is found across multiple organizations when access and usage needs to be arranged. The Digital Data Marketplace is an approach where organizations, as members of a consortium, recognize a common benefit to make their data available to enable development and training of algorithms, however access and usage needs to be arranged in a trusted, fair and economic way. In our Tech Demo, we will show how the SAE ITC ExchangeWell consortium initiative can facilitate organizations that like to achieve common benefits no single organization could achieve on its own, whilst addressing member concerns regarding data value, confidentiality, intellectual property, and more in a trusted way. We will demonstrate how a consortium driven marketplace operates, where data owners and algorithm developers register their assets and subsequently negotiate visibility, access and usage of their data assets. Novel data science processing concepts, such as Federated Analytics using a consortium infrastructure helps protect data assets. We will explain how blockchain and smart contracts is a key enabler for the underlying operation and orchestration of data science workflows resulting from supply and demand – members negotiations.