LCS CBM

+ Program Implementation

The LCS Ship design Objectives

• High level of ship mission availability while performing any one of the three reconfigurable mission capabilities:

– Anti Submarine Warfare

– Mine Warfare

– Surface Warfare

• Aggressive Total Ownership Cost (TOC)

• LCS crew of 40 will be approximately 33% the size of that found aboard comparably sized vessels

Critical Requirements to Address LCS Sustainment Challenges

• Failure Prevention During Mission Periods– Continuous equipment condition and system risk visibility– Early detection of machinery condition and predicted risk change– Failure Risk prediction accounting for planned operating tempo

• Advance Planning & Scheduling of Pre-Planned Work to be Performed During In-Port Periods– Define what (specific work action) needs to be done with at least an 80%

confidence factor– Define when ( which availability or period of convenience) the work needs to

be done– Define why (equipment risk to mission) the scope needs to be done

• Limited Ship-board Operators and Maintainers– Failure prevention and reaction during mission periods

• OPNAV Newly Defined LCS Specific Metrics – Materiel Reliability– Materiel Availability– Mean Down Time– TOC

LCS Sustainment Initiative: Reliability Engineering Based CBM

+

– The required engineering and information infrastructure to allow execution of LCS Sustainment CONOPS within a unit level Reliability

Engineering Based CBM + Process that will also:

• Conform to the published CBM +

Policies and the SURFOR CBM Top Level Requirements

• Take advantage of Programs of Record developments related to next generation ICAS and MELS

• Take advantage of available GOTS and COTS technologies supporting the implementation of CBM

+

• Take advantage of the Distance Support infrastructure

LCS CBM + Approach: Machinery Reliability

Management Systems (MRMS)

• MRMS is an integration of Navy program of record and COTS technology in order to:

– Continuously acquire machinery operating and event data

– Continuously assess the current condition of critical equipment

– Estimate the probability of future failure risk, when operated within a planned operating profile

– Provide the machinery current condition, predicted failure risk probability, to the LCS Reliability Engineer for maintenance decision management support

– Receive conditions found and work accomplished information related to the recommended maintenance action to validate risk models

– Compute Sustainment Process Metrics relative to the selected critical ship-board systems

Continuous Reliability ManagementContinuous Reliability Management

MRMS Equipment Reliability Information Flow

DQECollects & Processes Data

MELSMRRs

Formats &Presents Reports

TO USS NEVER SAILFROM SWRMC

SUBJECT: IPAR REPORT

1. RMC REPS HAVE COMPLETED REVIEW OF IPAR BASED ON ICAS DATA2. DATA INDICATES PROBLEM WITH GTG #13. RECOMMEND BORE SCOPE UNIT

Reliability Engineer

NIAPSServer collecting & sending data off ship

Reliability Analysis, Equipment Operation Advisories, Maintenance Recommendations, Planning, Execution, Tracking, Closeout, Metrics

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Phase 1 Remote Monitoring & Risk Prediction

SYSTEMS

• SSDG

• MPDE

• GTM

• Reduction & Combining Gears

• Lube Oil & Line Shaft Bearings

• Water Jets

• AC Plants

• MPACs

• Machinery Condition and Predicted Reliability Assessment for 8 systems• Current Health

• Predicted failure risk (30/60/90/180 days)

• Remote monitoring capability (shore side) through DS connectivity between on-board data acquisition and data filtering (DQE) and the Navy Maintenance Engineering Library Server (MELS)

• Establishment of the CLSRN N4R, Reliability Engineer, position to implement and manage the CBM Process for LCS sustainment

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Phase 2: Ship-Board Reliability Management

• Shipboard views of shore-side Phase 1 implemented MRMS screens (same 8 systems)

• Operational recommendations to minimize equipment degradation • Machinery alignment recommendations

• O-Level maintenance recommendations

• Operating range recommendations

• Onboard application – “What-if” Calculation Engine• Calculates predicted future machinery failure risk based on current health,

planned maintenance and mission operating profile

• Provides for evaluation of speculative changes to operational profile (environment, speed, load, line-up) as it might affect system reliability

Concept of OperationConcept of Operation

• Material Readiness Assessment– Equipment failure mode conditions will be assessed using available

data transmitted through Distance Support– Overall equipment current health (readiness) assessed as a roll-up of

failure mode conditions

• Failure Risk Forecasting– Equipment failure mode predicted risk (residual useful life) will be

assessed using current health, historical performance and duty cycle data and forecasted for 30/60/90/120 day span

• Mission Risk Assessment– Based on the predicted failure mode risk levels at the prescribed time

span, an assessment against Mission Risk will be estimated for the applicable systems

EQUIPMENT/ SYSTEM PERFORMANCE AND RELIABILITY ANALYSISC

alc

ula

tion

Str

ess

Indu

cin

g E

ven

tR

elia

bil

ity

Model

In

pu

tSen

sor

Voltage Imbalance

PRESENTATIONHEALTH ASSESSMENTSTATE DETECTION

Current Imbalance

Mechanical Param

DATA ACQUISITION

Bearing Wear

Winding Short

Electrical Param

Steady StateOps

High Vibration

Rotor ImbalancePerformance

Analysis

Current HealthStatus

Time

Damage

Period of Operation

Oper

ati

onal P

erfo

rmance

Rel

iabil

ity

Predicted Reliability

TransientOps

Stress InducingEvents

Reliability Prediction

Current Reliability/Cumulative Damage

Working Age

Reliability Model

PROGNOSTICS

Planned Operating Profile

BBN Diangosis

ANOMALY DETECTION

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Phase 3: Reliability Engineering Data Integration System (REDI) Using Enterprise

Service Bus

• Provides framework to automate the Sustainment Process Work-Flow to improve process effectiveness and reduce cost within manning constraints

• Support feedback loop to validate/update diagnostics and risk prediction algorithms through information from conditions found and maintenance actions taken

• Predictive risk based logistics model for effective advance planning, using HM&E system reliability analysis results

• Links to applicable Navy and ISP systems to automate data sharing and continuous process validation (metrics) and improvement

LCS Machinery Condition & Reliability Displays

LCS Machinery Condition & Reliability Displays

The Reliability Engineering Based CBM +

• Web enabled application to facilitate distance support

• Extensive HM&E data collection

• Allows for a shift from periodically scheduled Preventive Maintenance (PM), ICMP, and failure based Corrective Maintenance to a maintenance strategy based on predicted machinery failure risk

• Reduces the dependence on shipboard manpower and will support achieving the LCS design objectives of:

– Increased equipment readiness through a higher systems availability gained by more effective availability planning prior to mission operating periods

– Reduced cost of O-Level and shore side on-shelf spares and maintenance tasks since a better awareness of equipment health at all times allows for very effective logistic planning

CBM +

Value to the FleetCBM +

Value to the Fleet

• Will provide the decision management support for execution of effective LCS life cycle sustainment

• Will provide the means to establish more accurate budget forecasts

• Ship operators will achieve:

– Reduced dependence on shipboard manpower through more effective utilization of Distance Support

– Operator awareness of impending equipment risks to prevent cascading and collateral failures

– Increased equipment readiness gained by more effective availability planning prior to mission operating periods