Ryan FogartyCBM+ and Remote Monitoring

Defense Maintenance Symposium – Mini Summit

Condition Based Maintenance +

SME-Validated Condition Assessment Reports Provided

Weekly to Ship’s Force

Shipboard:Enterprise Remote Monitoring

(eRM)

DoD/DoN GIGPortable Data

TerminalEmbedded Sensors

Data Historian

Notifications/Alerts

Log Sheets

eRM

Shipboard Work Station

Maintenance Scheduler

Shoreside:Consolidated Machinery Assessment System (CMAS)

CMAS

Cloud-basedData Repository

ForensicAnalysis

Trending Analysis

Maintenance & Availability Planning

Customizable Presentation

2-Kilo Generation

Data Consolidation

HealthMonitoring

Condition Based Maintenance +

92Ships

Installed on 92 of 177 surface ships

Collecting 3,000 to 5,000sensors per ship

Digital Twin automates data analysis –Automatically flags deviations for review

System collects machinery condition data that is transmitted for shore analysis and scheduling of condition based maintenance

CBM+ Digital Twin Strategy

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Integration ofNon-Sensor Data

Healthy Equipment Models

Sensor Data Collection

Enables improved condition assessment based on historic fleet-wide equipment operation.

Incorporates historical context and relevant peripheral information to enhance equipment condition assessment.

Digital Twin

Provides situational awareness into equipment operation.

Provides near real-time condition assessment, operational suggestions, and maintenance and supply recommendations through integration of healthy equipment models.

Increasing Visibility intoPerformance to Improve

Reliabilityof Ships on Station

• Since the mid-1990s, the CBM+ES Program has provided SMEs with shipboard sensor data, enabling:– Situational awareness of operational equipment– Distance support through remote monitoring– Detection of anomalies and equipment operational concerns

• Using years of sensor data, in conjunction with data science, the CBM+ES Program has:– Improved data contextualization and analysis techniques– Initiated the development health equipment models for HM&E equipment– Identified data gaps, driving future acquisition enhancements

• CBM+ES Program continues to leverage cloud-based repository to:– Increase access to disparate operational and logistics data– Improve condition assessment capabilities, through integration of telemetry and non-telemetry data

Gas Turbines – Validated Predictive Capability

What the engine shouldbe doing

Measured vibes higher than model but below alarm

64% OF UNSCHEDULED CHANGE-OUTS DETECTABLE BY DIGITAL TWIN

Next Steps – Validate LPD17 Diesel Engine Model

6

Predicts five sensors using a collection of decision trees

Inputs (7)Power command

Fuel Inlet Pressure Fuel Inlet Temperature

Fuel Rack PositionJacket Water Pump Pressure

Generator PositionExhaust Class

Outputs (18)Cylinder Exhaust TemperaturesIntake Air Manifold TemperatureJacket Water TemperaturesExhaust Manifold TemperatureLube Oil TemperaturesT/C SpeedCurrent

Regression Branch

(for Continuous Sensors)

Neural Network with (7, 5, 13) architecture

Classification Branch

(for Discrete Sensors)

Caterpillar 3608

Model triggered on April 15th

Shipboard Alarms on April 29th

CBM+ History and Future Vision

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1998

2005

2012

2015

2016

2019

2021

2026

Enterprise Remote Monitoring (eRM)

Delivered to PMS500

eRM 3.0 developed as data acquisition system to support hull fouling

R&D sensor project

Integration with suite of maintenance and logistics applications

(Navy Common Readiness Model)

eRM 1.0 developed for DDG-1000

eRM 3.1 – first installation of full fleet

implementation version onboard DDG-

102

ICAS sunset from the fleet

ICAS fleet implementation along

with Maintenance Engineering Library Server (MELS) shore side data repository

Best of Breed App Store for AnalyticsOrganic Govt Data Science CapabilityEquipment Subject Matter Expert Analytics

2022Advanced analytics

aboard ship with minimal reach back

to shore

2023

eRM integration with combat systems data and advanced analytics

MELS replaced with Government data

repository Consolidated Machinery Assessment

System

Data Collection & Analytics

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Performing data analytics today..

..that will lead to less expensive and more sustainable platforms tomorrow