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.

Technology Demonstration Chairs:
James Larkin,
Laurel Frediani,
Derek DeVries,

Click here (coming soon) to learn more about these funding opportunities.

Some potential demonstration topics include, but are not limited to:

  • Certification and Validation Techniques for Health Management Applications
  • Fielded Prognostic or Advanced Diagnostic Systems
  • Innovative System Maintenance Approaches
  • Rapid Aging Testing and Analysis Techniques
  • Sensors and Sensor Integration for Health Management
  • System Identification Processes to Support Health Management Goals

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:

  • Condition Indicator Design & RUL Estimation using MATLAB (Rachel Johnson and Sudheer Nuggehalli, MathWorks)
  • Connected Ecosystem for Aerospace Intelligence and PHM (Kurt Doughty and Dave Larsen, Collins Aerospace)
  • TBD3 (Ginger Shao, Honeywell)
  • TBD4 (Justinian Rosca, Siemens)
  • Testability Engineering And Maintenance System (TEAMS) Toolset (Deepak Haste and Sudipto Ghoshal, QSI)
  • AI Assisted Borescope Inspections (Abhinav Saxena, GE)
  • 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

Tuesday, September 24, 2019

Time Topic Presenter
9:00 – 10:30 Condition Indicator Design & RUL Estimation using MATLAB Rachel Johnson and Sudheer Nuggehalli, MathWorks
10:45 – 12:15 Connected Ecosystem for Aerospace Intelligence and PHM Kurt Doughty and Dave Larsen, Collins Aerospace
1:30 – 3:00 TBD3 Ginger Shao, Honeywell
3:15 – 4:45 TBD4 Justinian Rosca, Siemens

Wednesday, September 25, 2019

Time Topic Presenter
10:45 – 12:15 Testability Engineering And Maintenance System (TEAMS) Toolset Deepak Haste and Sudipto Ghoshal, QSI
1:30 – 3:00 AI Assisted Borescope Inspections Abhinav Saxena, GE
3:15 – 3:45 Health-Ready Components and Systems Ben Towne, Steve Holland, Leon Gommans, and Drasko Draskovic, SAE Industry Technologies Consortia
3:45 – 4:45 ExchangeWell Digital Data Marketplace


Technology Demonstration Summaries

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.


Connected Ecosystem for Aerospace Intelligence and PHM
Presenter: Kurt Doughty and Dave Larsen, Collins Aerospace

Coming soon


Presenter: Ginger Shao, Honeywell

Coming soon


Presenter: Justinian Rosca, Siemens

Coming soon


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.


AI Assisted Borescope Inspections
Presenter: Abhinav Saxena, GE

Coming soon


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.


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