Condition-Based Maintenance Requires Data Sharing

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What can be done to take the Defense Department’s efforts in predictive maintenance — also known as condition-based maintenance — to the next level?

Condition-based maintenance systems use sensors and other methods to collect data to let mechanics and logisticians know the most efficient and cost-effective time to replace parts or overhaul equipment. It can save both time and money.

Condition-Based Maintenance Plus, or CBM+, is a Defense Department initiative to enhance safety, increase maintenance efficiency, boost equipment availability and improve environmental integrity, according to department documents.

“There is a compelling need for better analytics around CBM+,” Vic Ramdass, deputy assistant secretary of defense for materiel readiness, stated as he addressed a group of professionals from industry, government and academia during a workshop at the National Defense Industrial Association in Arlington, Virginia.

“The DoD has taken several steps to improve CBM+ methodologies over the last 20 years, and predictive maintenance capabilities play a vital role in improving integrated deterrence and providing a tactical and decisive edge to the military services," Ramdass said. The compelling issue, however, is the lack of data sharing.

CBM+ expands on traditional methods by incorporating additional technologies such as prognostics, diagnostics, automatic identification technology and interactive training, as well as additional processes and procedures that enable improved maintenance and logistics practices.

The department generates massive amounts of data that could be applied to CBM+, but often fails to effectively use that data due to it being divided and siloed within agencies, services and contractors without venues to share it openly.

Additionally, there are few incentives for organizations to share data with others, nor is there a set of standards or a framework in place to facilitate downstream analytics. Existing data is often unavailable to the groups where it could be most useful due to a culture of data protection and competitive advantages.

To help the Defense Department take full advantage of the data it already has on system maintenance and sustainment, NDIA’s Logistics Division and the Emerging Technologies Institute convened a workshop to develop the outline for two pilot programs that will focus on efforts to improve the effectiveness and efficiency of data sharing as it relates to condition-based maintenance.

The department is spending an increasing share of its budget on the maintenance of aging infrastructure, weapons systems and other platforms. It has attempted, with mixed success, to increase the use of CBM+ methodologies over the years to reduce program total life cycle costs and improve the readiness of the force by introducing CBM+.

The overall goal for CBM+ is to shift from an unscheduled, reactive maintenance mindset to a more routine, predictive maintenance approach focused on evidence of need before failure occurs. Diagnostic data collected by integrated sensors and processed through supported automated information systems can enable readiness and affordability.

The data output of sensors measuring the state of equipment in real time is most effective when coupled with actual failure and demand data.

These are key components that enable product support managers, system maintainers, product support providers/integrators and depot maintenance activities to better sustain weapon systems.

There are technical issues to overcome — such as data protection and inconsistent data sets and formats — but the key takeaway throughout the discussion was that data sharing is oftentimes a cultural problem.

The workshop consensus was that despite the variation in governance across different sectors and departments, leaders within the military services, government and industry need to enact changes within their own organizations to improve data sharing for predictive maintenance.

Identifying and overcoming these internal and external obstacles will be key to ensuring success.

The group identified multiple methods for implementing predictive maintenance across different services, but each service currently relies on different offices. The lack of a single focal point in the Defense Department to enable data sharing makes coordination difficult.

To address these obstacles, policymakers need to support the development of a data environment that allows for efficient government-industry collaboration. Open lines of communication and collaboration are vital in ensuring the right stakeholders are involved and the right data is being collected and shared.

The working group will also look to identify the required data sets to unpack the ways in which data sets can be used more effectively to reduce operational and sustainment costs and improve readiness.

Significant challenges do exist, such as creating incentives for data owners to participate and share data as well as engaging government and industry leaders to endorse and fund activities within the pilot program.

Despite the challenges, a well-designed CBM+ pilot program would have great benefits by improving the methods in which maintenance data is shared across the department and industry, ultimately leading to preventive and corrective maintenance actions being scheduled more efficiently, increasing system readiness and reducing total ownership costs. ND

Tom Driggers is a participant in the Public-Private Partnership Talent Exchange Program working as a research fellow with the Emerging Technologies Institute. Cari Shearer is an ETI research intern.

For more information on the CBM+ Pilot study, please contact the NDIA Logistics Division or the NDIA Emerging Technologies Institute. To read the full workshop report, please visit https://www.emergingtechnologiesinstitute.org/our-work/workshop-reports.

Topics: Infotech