CBM Program for US Army Aircraft

A former Rochester, NY consultant, Carl Byington emphasizes data and analytics-based approaches at PHM Design, LLC in Atlanta, GA. He works with clients to implement predictive analytics to maximize operational and maintenance efficiency. Well published in his field, Carl Byington presented the condition-based maintenance (CBM) of the United States Army aircraft systems at an American Helicopter Society (AHS) specialists’ meeting.

A CBM program involves moving from part replacements performed at defined intervals to maintenance performed upon “evidence of need". With the context of the Army’s CBM+ plan, this requires a move away from “time before overhaul” (TBO) protocol that traditionally defines schedules for military vehicle component maintenance. It also suggests an ability to move away from dedicated inspection and test flight maintenance events.

According to the paper, major obstacles in CBM adoption include the limited ability of digital source collectors (DSC) and health and usage monitoring systems (HUMS) to diagnose component faults early. Issues include condition indicators and sensors’ sensitivity to operating/environmental conditions, observability of specific failure modes, and inherent signal to noise ratio. Fleet-wide diagnostic thresholds to action are also difficult to implement, with uncertainties arising in detecting existing and progressive damage or wear among individual aircraft variations of use. Implementing prognostics on faulty or degrading components is inherently a significant endeavor, with validating and verifying such systems a remaining challenge.

The paper presents tools that can improve data monitoring, boost diagnostics, and enable prognostics to be implemented in ways that support a better transition to CBM. The realizable benefits are substantial. Detection of faults in their early stages provides an opportunity to order parts, schedule personnel, shutdown the equipment before serious damage occurs, and minimize the disruption to production and missions. Furthermore, insight gained from better diagnostics reduces uncertainty regarding the “health” of critical internal drivetrain components and allows for the safe reduction of some preventive maintenance and inspections. In other words, maintenance is performed only when necessary. As we extend such capability into predictive prognostics technology, often enabled now by machine learning (ML) and artificial intelligence (AI) techniques, we can realize even greater maintenance and logistics benefits.

Advanced Wind Turbine Health Management

 

Experienced entrepreneur and engineer Carl Byington worked for Impact Technologies, Sikorsky Aircraft, and Lockheed Martin for many of his professional years. In these roles, Carl Byington became an expert in prognostics and health management (PHM) technologies and next-generation condition-based maintenance plus (CBM+) solutions. He currently consults in these technical areas at his PHM Design company, located in the Atlanta, GA area.

 

Rotorcraft and wind turbines are both susceptible to critical drive train failure modes involving bearings and gears. The helicopter community has developed sophisticated health and usage monitoring systems (HUMS) to track damage accumulation on critical components and detect incipient faults. Health and usage monitoring systems typically consist of a variety of onboard sensors, data acquisition systems, and signal processing and analysis algorithms.  The acquired data may be processed onboard the rotorcraft or on a ground station (or a combination of both) providing the means to measure against defined criteria and generate instructions for the maintenance staff and/or flight crew for intervention. Application of HUMS technology to wind turbine drive trains has the potential to significantly reduce maintenance costs and increase turbine availability by enabling condition-based maintenance (CBM).

 

The wind turbine industry has experienced an array of drivetrain failures including spalled bearings and fractured gear teeth. Some of these failure modes are largely attributable to unexpected and/or excessive loading conditions. Such drivetrain failures often entail expensive repairs and can have catastrophic consequences for the turbine. The helicopter community faces many of the same challenges from uncertain loads and dire consequences associated with drivetrain failures. Thee helicopter community addressed these risks through the use of drivetrain health and usage monitoring systems (HUMS). Such HUMS oil debris and advanced gear/bearing vibration technologies can be used to help the wind turbine industry.

 

Information from HUMS enables implementation of a new maintenance paradigm that can improve reliability, availability, and maintainability of wind turbines while simultaneously reducing maintenance costs. Under the simplest maintenance paradigm, reactive maintenance, equipment is allowed to run until it fails without maintenance intervention. Reactive maintenance yields low reliability and high costs due to missed opportunities to detect and repair faults, secondary damage (progression of failure to a severe state), large logistics footprint (parts and labor) to cope with unexpected failures, and lost production while equipment awaits repair.

 

Preventive maintenance can improve equipment reliability (number of failures) by periodically overhauling equipment before it wears out. To avoid unexpected failures in equipment that has an uncertain service life, preventive maintenance must be performed well in advance of the mean time to failure. Consequently, preventive maintenance achieves high reliability at the cost of performing premature maintenance which includes frequent interruption of production for planned maintenance, high labor costs, and high parts usage.

 

Condition-based maintenance (CBM), on the other hand, enables high equipment reliability and low maintenance costs by eliminating the need for unnecessary overhaul activities while simultaneously allowing repairs to be performed on a planned basis. Condition monitoring provides insight into the “health” of individual pieces of equipment so that maintenance decisions can be made on a case-by-case basis rather than on fleet wide averages. Detection of faults in their early stages provides an opportunity to order parts, schedule personnel, shutdown the equipment before serious damage occurs, and minimize the disruption of production. Furthermore, insight gained from equipment condition monitoring reduces uncertainty regarding the “health” of critical internal drivetrain components and therefore eliminates the need for preventive maintenance. In other words, maintenance is performed only when necessary. 

The value proposition for wind turbines and specific technologies involved is summarized in a paper by Carl Byington, et al. It is available for download here:

 

https://www.researchgate.net/publication/253354657_Advanced_Vibration_Monitoring_for_Wind_Turbine_Health_Management

 

Carl Byington may be contacted for specific consulting engagements at:

https://phmdesign.com/contact-us/

 

 

Carl Byington at The PHM Society

“Professional Engineer Carl Byington became president and chief officer of PHM Design, LLC after working as a principal investigator at Sikorsky Aircraft. Carl Byington has made many contributions to the engineering industry as part of the American Society of Mechanical Engineers (ASME), SAE International (formerly the Society of Automotive Engineers), Machinery Failure Prevention Technology (MFPT), and more significantly the Prognostics and Health Management Society (PHM Society). Carl Byington served numerous roles in the PHM Society over the last decade including Tutorials Development, Technical Program Chair, General Conference Chair for multiple years, and on the Board of Directors.

The PHM Society is a non-profit organization dedicated to the advancement of PHM as an engineering discipline using a unique approach. As provided on their website, the PHM Society is founded on three basic principles:

To provide free and unrestricted access to PHM knowledge;
To promote interdisciplinary and international collaboration in PHM;
To lead the advancement of PHM as an engineering discipline.
In order to accomplish these principles, the Society has adopted a Creative Commons license policy that allows authors to retain copyright while allowing the Society to distribute their work broadly through modern media. This solution provides timely and free dissemination of research results, articles, opinions, news, and notices pertaining to PHM research and applications.

The flagship publication of the PHM Society is an open online journal entitled the International Journal of Prognostics and Health Management (IJPHM). The Journal has established a fast-paced, yet rigorous peer-review policy, which provides scientific journal-level quality to the publication. The Journal publishes online and at a cadence much faster (and environmentally friendly) than what is achieved with traditional printed journals.

The PHM Society accomplishes its interdisciplinary collaboration through its Annual Conference, typically in held various locations in the USA, Europe, and in some years the Asia-Pacific region. In this time of Covid-19 concerns though, the Society is evaluating virtual and better socially distanced ways of achieving its interactive mission.

While this situation will likely continue to be a challenge for all-conference organizing societies, the PHM Society web site still provides industry-leading capabilities for community collaboration through forums, wikis, blogs, and other Web 2.0 capabilities. This website is accessible to its entire user base without restrictions, fees, or membership requirements.”

Reference link:

https://www.phmsociety.org/