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Condition Based Maintenance+Implementation

DOD Maintenance SymposiumSpokane, WA

12 Dec 2019

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CBM+ Vision

Performed reactively when there are failures

Maintenance based on time

Diagnostics data stuck at weapon system, cannot be offboarded

Limited, manual failure analysis capabilities

Unpredictable future operational availability

Current Maintenance Posture

Performed proactively, based on predicting remaining useful life

Maintenance based on anticipated events, performed only as needed

Diagnostics successfully offboarded, centralized, and analyzed

Failure analysis performed in an automated manner

Data-driven insight on future operational availability

Future Maintenance Posture

CBM+ is a shift in maintenance behavior and practices enabled by technology

Con

ditio

n B

ased

Mai

nten

ance

+Technology

Business (Processes)Strategic Guidance

MCO 4151.22CBA Review

Force Dev System

Maintenance Practices

Tech Manual / Maint Practice

Changes

Programmatics

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33

Strategic Guidance

“Marine Corps efforts to maintain and manage trustworthy data will continue building on the need for new capabilities

to generate or collect appropriate data…Capabilities development must include sensors, data, and network

capabilities. Logistics information technology systems must be developed/modified to leverage accumulated “big data” to assist initiatives like Condition Based Maintenance-

Plus and improved accurate readiness reporting.”

Sustaining the Force in the 21st Century, 2019

“We will make strategic investments in data science, machine learning, and artificial intelligence. Initial

investments will focus on challenges we are confronting in talent management, predictive maintenance, logistics

intelligence, and training…The Marine Corps can no longer accept the inefficiencies inherent in antiquated legacy

systems that put an unnecessary burden on the warfighters.”

General Berger, Commandant’s Planning Guidance, 2019

Commandant’s Planning Guidance

(2019)

Nat’l Defense Strategy (2018)

DoDI 4151.22 (2012)

H.R. 2500 – FY20 NDAA (2019)

Sustaining the Force (2019)

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Getting To PredictiveCBM+ Aware to CBM+ Ready to CBM+ Implemented

CBM+ Aware

Proving CBM+ with current data by conducting continuous reliability engineering (RCM),

publishing policies, and developing a CBM enrollment

methodology that is defendable, repeatable, and

validated.

CBM+ Ready

Finding, assessing, and fixing failures quickly and accurately,

and beginning to predict unplanned equipment failures.

Integration of CBM+ data systems to improve data

quality and condition trends that feed enterprise decision-

support systems.

CBM+ Implemented

Building a holistic view of equipment condition -automated condition

monitoring.

Achieves accuracy in failure prediction by incorporating the operational environment and

mission factors into customized failure models for

individual systems.

Reducing Cost & Increasing Operational Availability – by minimizing the amount of repair parts on hand, maximizing throughput, and using sophisticated assessment software to optimize operations and

supportability of major systems.

Current State Future State

Not Realized Partially Realized Fully Realized

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Concept of Operations

JLTV MTVR

Minimum Viable Program

FY20

Build a full-spectrum, tightly scoped CBM+

minimum viable program (MVP)

• Enable a total of 10 JLTVs and 10 MTVRs

• Partner with 1 CONUS unit • Leverage initial learnings

from existing pilot efforts• Synchronize efforts across

spectrum of stakeholders

Proposed MVP Expansion

FY21

Evaluate and expand MVP to additional weapon systems,

FMF units

• Grow JLTV/MTVR MVP to 4+ units, including each MEF

• Expand MVP architecture / process to include 4+ new weapon systems

• Measure impacts on supply chain efficiency, readiness, and decision support

FY22-26

Scale aggressively to all FMF units, legacy

weapon systems, and new acquisitions

with POM-22 FYDP

• Enroll remaining applicable weapon systems / units in CBM+ program

• Deploy mature AI and cloud infrastructure at scale

• Reshape training, education, supply, and policy to revolve around CBM+

Scaling CBM+ Fleetwide

ATLaS MHE

Up to FY19

Conduct pilots on individual weapon

systems and gather initial learnings

• Gauged impact from use of sensors and changes to scheduled maintenance

• Conduct 7 total CBM+ related pilots

• Focus on individual stages of CBM+ (collect, transmit, store, analyze, act)

Individualized Pilots

LAV M777 M88 EFAS ACVComms ROGUE Fires

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Extended Service LifeExpected end of service life 2042+

New PlatformCurrently fielding and capturing configuration data for CBM+ initiativesEquipped with CAN bus

Industry standard SAE J1939/J1708 protocol can be leveraged for diagnosis

and prognosis

Common Engine PlatformMTVRs in most motor pools and other

TAMCNs use same CAT Engine

Embedded DiagnosticsCBM+ enabled with on-system health monitoring

Future Operational DemandSupport vehicle of choice in future operating environment

Ready Historical DataData can be used today for probabilistic

modeling and enhancing maintenance decisions

MTVRLegacy Program

JLTVNew Acquisition

CBM+ applications on both platforms are readily scalable across the Fleet

Marine Force

CBM enabling methods and lessons learned can be exported and scaled across a variety of Marine Corps

equipment

Minimal Viable ProductMTVR and JLTV

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MVP ArchitectureData Transfer From Platform To Enterprise Level

(1) Parametric Data(2) Diagnostic Data(3) Configuration Data(4) Proprietary Data

Data Types

Platform Level Unit Level Enterprise Level

Wired Data Transfer(1), (2), (3), (4) EMSS

Marine maintainer equipped with EMSS

Wireless Data Transfer: Wi-Fi with RFID Verification

(1), (2), (3)

Local Unit Server(Portable Server or

Edge Server)

Equipment with Digital Source

Collector Wi-Fi + RFID Gateway

Enterprise Cloud Server

Health and usage information will be provided to the unit

FRONT-ENDMAINTENANCE APP

(Web-based Information Portal)Enterprise Data Analyst Center

EACBNTRIDENT

ENTERPRISESERVER

Options Include:(1) JAIC Server(2) MLS2 Server(3) Army Data

Analysis Server

Enterprise-level trend analysis

< - JAIC preferred

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Synchronized Approach for CBM+

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Access to Technical Infrastructure

Critical Dependencies

Successful implementation of CBM+ requires resolving 3 critical dependencies:

• Insufficient wireless network access, critical for automated data collection

• Solution: Scaled wireless access (Wifi, Bluetooth, etc.)

• No existing storage capability compatible with WiFi and MCEN

• Solution: ATO-approved option for local data storage and upload

Data Science Expertise

Processes

• Insufficient analytics capacity across the enterprise

• Lack of technical expertise

• Solution: Investments in hiring or training organic analytical capabilities

• Distributed pockets of data science talent

• Limited institutional knowledge for best data science practices

• Solution: Established data science structure, roles, and responsibilities

People

Unified Approach

Wireless Access

Local Data Storage

• Current approach lacks unity of effort, siloedactors advance CBM+ in varied, stovepiped ways

• Fails to fully leverage enterprise resources in the most efficient way

• Solution: A unified, synchronized approach to promote an organized and sustained CBM+ effort among stakeholders

Leadership

1010

Way Ahead & Near Term Targets

“Whole-of-HQMC” Effort • I&L will lead (coordinate and synchronize), and stakeholders will

support, CBM+ implementation via:o Minimum viable product (MVP) in FY20o Expand the MVP in FY21o Scale to the enterprise in FY22 and beyond

Working Groups• Wireless• Server• Vehicle configuration

Coordination• Data file conversion• Digital source collector refresh

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Questions