The Journey to Predictive Maintenance

The Journey to PredictiveMaintenance

CONDITION-BASED MAINTENANCE PLUS (CBM+)

Greg Kilchenstein

Director, Enterprise Maintenance Technology

Office of the Deputy Assistant Secretary of Defense for Material Readiness

Today’s Agenda

1:00 pm ET Welcome and Intros1:10 pm ET Service Presentations2:05 pm ET Q&A2:15 pm ET Closing Remarks

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WHAT IS PREDICTIVE MAINTENANCE (PMx)

Predictive Maintenance is Condition-Based Maintenance Plus

• Condition-Based Maintenance is maintenance based on the “evidence of need”

• Evidence may indicate:

• An immediate event (Legacy Mx)

• An impending event (RCM/CBM)

• An event further on the horizon (CBM+/PMx)

• CBM+ relies on the ability to analyze all relevant data sets to discover

the “evidence” using Artificial Intelligence, Machine Learning, Algorithms

and Advanced Analytics, Digital Twins, Physics of Failure, Digital

Simulation

• CBM populates these data sets with data from digital source collectors,

usage data, maintenance and supply data and operational context

• RCM forms the foundation where component analysis, R&M data design,

FMECA data, and maintenance plans inform candidate components for

CBM

•Predictive Maintenance•Forecast remaining equipment life & future condition•Need projected as probable within mission time•Leverages AI and Machine Learning •On and off system real time trend analysis

CBM+Predictive

•Condition-Based Maintenance•Based on current condition of asset •Scheduled based on evidence of need•Continuous sensor data collection •Near-real time trend analysis

CBMCondition-Based

•Preventive Maintenance (Scheduled)• Fleet-based fixed time schedule•Prevent failure via replacement

or overhaulRCMCorrective / Preventive

•Corrective Maintenance (Unscheduled)•Fix when broken

Data LayerMaintenance / Supply / Operational

THE CBM+/PMX JOURNEY

EON is further refined by on-board sensors and advanced diagnostics

Condition Monitoring(impending events)

Evidence of Need (EON) provided by design reliability analysis & testing

Condition Conjecture

EON greatly enhanced through usage and maintenance data

Condition Projection Refined (immediate events)

EON is predictive and applies the most advanced analyticsCondition Insight

(events further on the horizon)

WHY IS THIS IMPORTANT?

• Outcomes• Affordable combat power – Available weapon systems

• Reliability at reduced cost – Mission assurance

• High-performing, integrated sustainment enterprise

• Goals • Proactive data/metrics-based execution of maintenance

• Eliminate unscheduled maintenance

• Integrate sustainment functions to optimize effectiveness and efficiency

• Objective• RCM*-based maintenance executed on evidence of need

• Create insight about materiel condition at all levels of Mx

• Integrate and use all data as the basis for sustainment decisions

Maintenance requirements drive availability and cost – CBM+ is DoD’s key strategy for producing availability and leveraging technology at best cost

LTC James A. BarberDivision Chief, DCS, G-44 Maintenance Headquarters United States Army, G4

Predictive & Prognostic Maintenance

(PPMx) The Progression of CBM+

LTC James Barber, Division Chief, DCS, G-44 Maintenance

09 March 2021

9


Army leveraged CBM+ processes for 12+ years• Advances in both Aviation and tactical wheeled vehicle (TWV) platforms

Army Senior Leadership (ASL) are planning for future conflicts involving operating environments comprised of existing near-peer threats in multiple domains.

• Recognizing the need to reform and shift maintenance focus• Prioritize modernization• Retain sustained readiness• Maintain the competitive advantage

PPMX is the application and integration of appropriate processes, technologies, and knowledge-based capabilities to use authoritative and emerging data to achieve foresight in combat system health management and health management response:

MDO Operational Environment

The Progression of Maintenance….

Corrective Maintenance

Preventative Maintenance

Predicting failure & Avoiding it

- Excessive downtime

- More reactionary

+ Maintenance is managed

+ Fewer catastrophic failures

+ Unexpected failures reduced

+ Inventory demand based

- “Unscheduled” breakdowns still occur

+ Maintenance performed asmed whenrequired

+ Improved equipment reliability

+ Catastrophic failures become predictable

+ More aware of safety incidents

+ Inventory demand based

+Equipment life is extended

+ Overall maintenance costs reduced

+Utilizing AI

- Higher investment costs

The use of data in the evaluation of a materiel for determining the potential for impending failures.

Maintenance performed to prevent failure through

systematic inspection, detection, and prevention.

Maintenance performed as a result of failure.

“Unscheduled Maintenance”

“Scheduled maintenance”


Today

Future

Operator / Maintainer MaintenanceOfficer Commander

Store

PPMx Decision Support Concept“Unity of Effort across all Echelons”

Strategic

Operational

Tactical

Platform

Enterprise

Organizational

Unit

Technical

12

What's Next………

1) Multiple Pilots ongoing across the Service….

2) HQDA EXORD (Implementation of PPMx)

3) PPMX Requirements Document in development

4) PPMX Demonstrations Planned

5) Development of the PPMx Strategic Framework

Ryan FogartyTWH for Condition-Based Maintenance and Remote Monitoring

Naval Sea Systems Command, 05Z

Ryan FogartyCBM+ and Remote Monitoring

CBM+ Overview Brief

CBM+ is the confluence between the maintenance tasks that RCM tells us to do and cost-effective enabling technologies that assist in evaluating system and equipment performance.

RCM is the Basis for NAVSEA CBM+

NAVSEA uses MIL-STD-3034A RCM analysis to determine which failure modes and parameters should be monitored on critical equipment

These technologies that drive a closed-loop process that connects data collection and analysis with actionable feedback, resulting in improved readiness at best cost

Condition Based Maintenance+ In Practice

94Ships

Installed on 94 of 177 surface ships

Collecting 3,000 to 5,000 sensors per ship

Digital Twin automates data analysis –Automatically flags deviations for

review

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

Condition Based Maintenance+ In Practice

MLP Neural Network regression andDecision Tree classification models

The approach uses a Random Forest Regression Modelconsisting of an average of 15 Decision Trees

York 200 Ton HFC134a Marine AC Plant

Caterpillar 3608 Diesel GeneratorAllison 501K34 Gas Turbine GeneratorMLP Neural Network regression and

identifies deviations from fleet behavior

Hybrid model combines insights fromData-driven Regression and

Physics-based Models

Calendar Based Maintenance

Hybrid – Algorithm triggered and Calendar Triggered

Algorithm triggered maintenance

CBM+ Implementation

Nick SmithCondition-Based Maintenance Division Lead

Commander, Fleet Readiness Center (COMFRC) Headquarters, Patuxent River, MD

20Distribution Statement A: Approved for public release; distribution is unlimited. As submitted under NAVAIR Public Release Authorization 2021-XXX

Condition Based

Maintenance Plus (CBM+)

Journey to Predictive

Maintenance Nick Smith

CBM/CBM+ Division Lead9 Mar 2021

Distribution Statement A- Distribution is unlimited under NAVAIR Public Release Authorization 2021-135


Agenda

• The End State • Foundational Elements • Operational View • Support Structure • Benefits of Predictive Maintenance (PdM) • Summary • Current Focus



The End State

Establish an environment “where reactive, unscheduled maintenance can be replaced with predictive maintenance (PdM) executed at the most opportune time and location with the right people, parts, and tools.”

Outcomes: • Less Reactive Maintenance • Less Overall Maintenance• More Proactive Maintenance• Higher asset availability and

operational readiness• Reduced life-cycle costs

Change the Maintenance Ratio Mix

Notional Data



Foundational Elements

Produces models based on actual usage and parametric data

Produces proactive component removals based on statistical analysis

Produces proactive maintenance alerts

based on sensor based algorithms

Condition Based Maintenance Plus (CBM+) CBM+ is the application and integration of appropriate processes, technologies, and knowledge-based capabilities to improve the reliability and maintenance effectiveness of DoD systems and components. At its core, CBM+ is maintenance performed based on evidence of need.

• CBM+ builds upon RCM and CBM to enhance safety, increase maintenance efficiency, and improve availability.

• CBM+ diminishes life-cycle costs by reducing unscheduled maintenance and enabling predictive maintenance.

• CBM+ turns rich data into information about component, weapon system, and fleet conditions to more accurately forecast maintenance requirements and future weapon system readiness to drive process cost efficiencies and enterprise activity outcomes.

Reliability-Center Maintenance

(RCM)

Condition Based Maintenance

(CBM)

PdM

Predictive MaintenanceThe ability to predict failure and schedule

maintenance prior to failure in order to maximize weapon system availability

Enterprise Processes, Technologies, & Knowledge-

based Capabilities



Operational View

A/C – AircraftAI – Artificial IntelligenceBIT – Built in TestFST – Fleet Support TeamHM – Health ManagementHMS – Health Monitoring SystemIDE – Integrated Data EnvironmentMx - MaintenanceMAF – Maintenance Action FormPdM – Predictive MaintenancePMA – Program Manager, AirRUL – Remaining Useful LifeSME – Subject Matter ExpertsWS – Weapon System

PMA/FST FleetData Analytics

Maintenance Control

• Fix it When it Breaks• Fly-to-Failure• Too Much Unscheduled Maintenance• Static Scheduled Maintenance Tasks• Ignoring A/C System Upgrade Alerts and BIT Data

• Active Use of BIT Data• Integrated Diagnostics to Identify Impending Failures• Use of Maintenance Aids• Automated Data Downloading• Fault Forwarding

• Automated Inspections• HM Data Used Across all Levels of Mx to include component repairs

• Data Analytics/AI• Life Extensions based on Actual Load/Usage• Removing components Prior to Failure

and Forecasting RUL

• Fleet MAF Data • Repair/Test Results Data • System/Subsystem Alerts• BIT Reports• Maintenance Drivers• Performance Analysis

Automated/Manual Data Download

Maximize the use of A/C HMS to:• Maintain the health of the WS • Forecast the need for Mx• Remove components prior to failure• Realize Mx efficiencies

Condition-directed Mx Tasks

Health Condition Data

Fly to Failure

Predictive

Preventive

• Sensor and Mx Data Collection• Enterprise Infrastructure• Enterprise Access to Data and

Analytics• Enterprise Wide Alerts

Notifications/Monitoring / Feedback

• Policy, Metrics, and Tools

Enterprise IDE

Predictive Maintenance (PdM)

Trained Workforce

PdM Reduces Unscheduled Maintenance and can Change the Maintenance Ratio Mix



Support Structure

CBM+ 10 Year Roadmap

Policy SME Development

ToolsKnowledge

Management

CBM+ OV-1

CBM+ Community of Practice (CoP)

Charter

NAVAIRINST5400.162A

TA Policy

• Collaborate with program teams on their CBM+ technical solutions

• Major Functions:o Policyo SMEso Toolso Knowledge

Management

• Align mission/efforts and expectations of stakeholders

• Focus resources on execution of CBM+ capabilities

• Standardize policy, requirements, processes, terminology, training, and metrics

• Assist POs achieve their CBM+ goals

• Monitor the health of CBM+ within the Enterprise

• Instruction • CoP Charter • SWPs• Management

Guide• Released

NAMP Change requiring full utilization of aircraft HMS data

• SSP • CBM+

Training Continuum

• Training

• Enterprise Solutions

• Aligned with LOG IT Modernization Initiatives

• PMA Unique Tools

• Conduct Reviews• Support Acquisition

Programs establish CBM+ requirements

• Collect Lessons Learned from Sustainment Platforms

DODI 4151.22DOD CBM+ Guide

Guidance CoP Structure

Community of Practice (CoP) Framework

Advance the Implementation of CBM+



Support Structure – Top Tier

Common Integrated Data Environment (IDE) and Analytic Tools

Standard DataRepository (SDR) Tools & Analytics

Aircraft HMS Data

EnterpriseCommon

Portal

MRO O/I/D,Supply &

Other Data

Curated Dataand Analytic

Results

Trained Workforce

DECKPLATE

• KC-130J• V-22 (All Variants)• VH-92

• F/A-18, EA-18• E-2D• F-35 (All Variants)• MH-60R, MH-60S• CH-53E, MH-53E• AH-1Z, UH-1Y• MQ-4C• P-8A



DASHBOARD WARNINGS, CAUTIONS, ADVISORIES

TILED LOBBIES

ROTOR TRACK/BALANCE

PLANESIDE AND EDGE ANALYTICS

IETM VIEWER (S1000D)

BUILT FOR SAILORS, MARINES & CIVILIANS

PLATFORM AGNOSTIC ANDPROVIDES AMESTANDARDIZATION

UNIVERSAL, EXTENSIBLEAND CONFIGURABLE

NSIV IS THE LOG-IT AUTHORITATIVEIETM VIEWER ACCESSEDTHROUGH MEGA

Support Structure – Edge

Common Maintenance Engineering Ground Station for Aviation (MEGA)



Benefits of Performing PdM

• Reduction in unscheduled maintenance events and MMHRs

• The ability to perform maintenance during periods of “opportunities” and align PdM with other scheduled maintenance (i.e. Phase, etc.)

• The ability to avoid cascading component failures, that typically cost more in repair costs and turn-around time (TAT)

• Better forecasting of WRAs and consumables to include less demand

• Safety

Improved Availability

Cost Avoidances

Enhanced Safety

Less Unscheduled Maintenance

Increased Maintenance Efficiencies



Summary

Effective Policy

Active Usage of HMS

Active RCM

Program

Active CBM

Program

Using Standard Data

Environment

Using Integrated

Common ALE Solutions

OPERATIONAL SCHEDULED MX OPERATIONALUNSCHEDULED MXOPERATIONALPREVENTIVE

As Is

To-Be

REACTIVE

PLANNED DOWNTIME UNPLANNED DOWNTIME

PMR&M

EngineerRCM

EngineerPHM

Engineer Logistician AnalystData

Scientist

Cross Domain SMEs that Understand Interdependencies

Reduce/drive Efficiencies to both Scheduled and Unscheduled Maintenance and Increase the use of PdM

Condition detected prior to failure occurring: • Required parts ordered• Mx performed when

convenient for the Fleet• HM data used to assist in

component repairs

PdM

Produces PdM



• Collect lessons learned and refine CBM+ Community of Practice (CoP)

• Developed CBM+ Fundamentals training and SME certification process. Intermediate and Advanced training will be developed in FY21

• Continue to integrate Health Monitoring System (HMS) data into enterprise business processes

• Refine sustainment processes to manage components removed prior to failure

• Released 8 standard work packages (SWPs) with 6 additional SWPs to be written in FY21

• Transition programs from unique enabling tools to common enterprise tools

Current Focus


Lt Col Yogi LebbyChief, Advanced Concepts Team, Aircraft Maintenance Division

Headquarters United States Air Force, Logistics Directorate

I n t e g r i t y - S e r v i c e - E x c e l l e n c e

Headquarters U.S. Air Force

Predictive Maintenance

AF/A4L9 March 2021


Overview

Air Force (AF) Conditions Based Maintenance Plus (CBM+) 2030 Vision

Predictive Maintenance (CBM+)

CBM+ Current State

Implementing CBM+ Vision


AF CBM+ 2030 Vision


Predictive Maintenance (CBM+)

CBM+ is a mx concept that will decrease USM events enabling maintenance production leadership the opportunity to determine when and where mx should be performed, optimizing resources and aircraft availability.

For predictive mx to be successful CBM+ utilizes two types of analytics: Sensor Based Algorithms (SBA), uses on board aircraft sensors and

algorithms to identify degraded components or systems. Enhanced Reliability Centered Maintenance (eRCM), is a technique that takes

aircraft mx data, supply data, and aircraft usage data to determine the best time to remove components before failure while maximizing the life cycle of the component.

Predictive MX has the potential to help reduce USM actions, reduce break rates, air aborts, and manpower constraints, mx recovery teams.


CBM+ Current State

C-5 and B-1 started CBM+ in Oct 18. Over the course of FY21 focus on eRCM moving from 16 platforms to 22 by end of the fiscal year.

Developed a CBM+ Strategic Implementation Plan in order to address implementation of the process in conjunction with RSO.


Implementing CBM+ Vision

Strategic Sustainment Framework effort – heavily focused on CBM+ Deliver CBM+ Implementation Plan to MAJCOMs

Governance council to work “All-In” platform initiative for KC-135 RSO Enterprise Integration Plan Increased focus on data analytics and importance of collecting clean

data, using data to make decisions Long-term vision: Predictive neural network that allows predictive

programmed depot maintenance packages by tail Changing to North Star with health-based metrics (15 days of health)

Leveraging commercial best practices Fleet management approach Focus on changing inspection packages to synchronize and

standardize inspections (regional)

Lt Col Chris CannonDeputy Director, Logistics Information Technology Branch

Headquarters Marine Corps, Installation & Logistics Department

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)

CMC White Letter 2-20, Achieving

Condition Based Maintenance

Sustaining the Force (2019)

DoDI 4151.22 – Is DoD Policy that CBM+ shall be Implemented

MCO 4151.22Condition Based Maintenance Plus

Order

USMC CBM+ Vision

Limited ability to conduct just 2 condition monitoring elements (inspections and repair history data)

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

Full use of all 5 elements of condition monitoring (fluid analysis, repair history, inspections, electronic data, and site conditions)

Performed proactively, based onpredicting remaining useful life

Maintenance based on anticipated events, performed only as needed

Diagnostics successfully offboarded, centralized, and analyzed

Failure analysis performed in anautomated manner

Data-driven insight on futureoperational availability

Future Maintenance Posture

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

Con

ditio

nB

ased

Mai

nten

ance

+Technology

Strategic Guidance

MCO 4151.22CBA Review

Force Dev System

Business (Processes)Maintenance

Practices

Tech Manual / Maint Practice

Changes

Programmatics

Concept of Operations

JLTV MTVR

• 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

Minimum Viable Program

FY20

Build a full-spectrum, tightly scoped CBM+

minimum viable program (MVP)

MVP Expansion to MLGs

FY21

Evaluate and expand MVP to MLG units

JLTV MTVR

• Grow JLTV/MTVR MVP to all MLGs across multiple units

• Establish a CBM+ Cloud solution within the JAIC/Cloud One

• Measure impacts on supplychain 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 revolvearound CBM+

Scaling CBM+ Fleetwide

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 Comms ROGUE Fires ACV

CBM+ MVP Started CBM+ Current State

QUESTION AND ANSWER

Closing Remarks

Dr. Vic RamdassDeputy Assistant Secretary of Defense for Material Readiness Office of the Assistant Secretary of Defense for Sustainment

The Journey to Predictive Maintenance

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