atlast deployment &push pack spares optimizer

ATLAST Deployment & Push Pack Spares OptimizerATLAST Deployment & Push Pack Spares Optimizer Dr. N.GurvitzDr. S. Borodetzky

P. Van Eck1

Clockwork Solution Inc.3432 Greystone Dr. , Suite 202Austin, TX 78731Tel: (512) 338-1945

ATLAST Deployment &Push

Pack Spares Optimizer

Presented byDr. Naaman Gurvitz


P. Van Eck2


ATLAST Model Logic

EngineeringARDEC

MaintenanceDepot & Field

Deployment PM/Readiness Logistics/Supply

IMMC/Item Mgr

Operations

Depot Maintenance

BaseMaintenance

Repair Turn Around

Repair Locations,Rules/DOF, Capacity,Cycle Time

Awaiting PartsOccurrences

Awaiting MaintenanceOccurrencesArrivals to Depot

Achieved Flying Hours

Failures and Life Limit Events

Assembly Ages And Repair History

Flying Program

SystemConfigurations/Status

Aircraft/SparesAssembly Location/Age/Status Availability

Items Condemned

Tasks Performed

Order Lead Times

Shipment Times

Supply

Stock Levels

SparesUnavailability

Spare Pre-positioning

Spares Locations

Time-based ForecastsModel Input Data

Log Functions

Legend


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ATLAST Strengths & Applications Real-World Complexities (State-based

Forecasting) Supports Initialization Down to Serial

Number Initialized “State” of Components Phased Aircraft Inductions by Tail Number Aging Analysis Recap, Zero Aging Analysis Distribution Swapping based on Repair

Count Reconfigurable Indenture Structures Life Limit Event Management Op Temp Variations by Location Interchangeability/Substitutability Capacity Constraints Time-Dependent Outputs

Analysis to be Supported with Model

Maintenance Concept Modifications

(e.g. Recapitalization)

Aircraft Induction Strategies

Operations Surge

Parts Purging

Sparing Strategies

Deployment Planning


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ATLAST Outputs Maintenance

Removals (Causal, Timed, Opportunistic)

Modules to Depot Condemnations Tasks Performed % of Time Awaiting

Maintenance Avg. Time Awaiting

Maintenance Cost

O&S O&S Per Flight Hour

Readiness– Time on Wing– Availability– Achieved Flying Hours– Cumulative Age

Supply– % of Time Awaiting Parts– Avg. Time Awaiting Parts– Spares Stock Levels– Spares Unavailability

By Location and Time Dependent


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ATLAST Optimizer• Deployment & Push Pack Spares

Optimization Module:– Creates a full deployment scenario on any number

of aircraft at a single base– User defines logistics delay and operational

profiles– Generates availability vs. cost graph– Provides analyst necessary information to

determine optimal spares pack


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Scenario Setup Process

M a s t e rD a t a M o d e l

D e p lo y m e n tS c e n a rio

S e le c t T a ilN u m b e rs

Vie w T a ilN u m b e rs

S e le c t B a s eo r Lo c a t io n

Vie w B a s eo r Lo c a t io n

O p e ra t io n a lD e fin e

P ro file s

O p e ra t io n a lM o d ify

P ro file s

Lo g is t ic sS e t

D e la y

Lo g is t ic sM o d ify

D e la y

S e t H is t o rie s& C o m m e n t

S e t H is t o rie s& C o m m e n t

R B SO p t im iza t io n

A v a ila b ilit yVs . C o s t

Gra p h

S imu la t eS p a rin gP a c ka g e

P rio rD e p lo y m e n t

S c e n a rio ?

N o

Ye s

1s t S c re e n 2n d S c re e n 3rd S c re e n 4 t h S c re e n 5t h S c re e n

6t h S c re e n


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Scenario From Master Database

Choose Deployment

Scenario name

Select Base

Type Location

Select aircraft tail numbers

Choose Master

Select Master Database

OR


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Define Deployment Period

Assign OperationalProfile


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Set Logistic Delays


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Set Number of Histories

Type

DescriptiveInformation


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Simulation & Optimization

Select Ranking Method

Run Simulation Verifications

Ranked Spares List associated with Cost

and Estimated

Performance Select Sparing Strategy and

Run Simulation Verification


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Simulation & OptimizationSelected Sparing

Strategy

Red Line Estimated

Values

Blue Points Simulated

Values

Selected Point “co-ordinates”


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0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Cost [K$]

Ava

ilabi

lity

[%]

Validation

5 Aircraft in 8 quartersa) No Life Limits

b) Single exponential failure distributions

c) New aircraft

Identical Assumptions in

Simulation and Analytical Models


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Numerical Results: Case A

30

40

50

60

70

80

90

100

0 250 500 750 1,000 1,250 1,500

Cost [K$]

Avai

labi

lity

(%)

10 Aircraft in 8 quartersa) Life Limits

b) Multiple Weibull failure distributions

c) Initial ages


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Numerical Results: Case B

5 Aircraft in 4 quartersa) Life Limits


c) Initial ages

30

40

50

60

70

80

90

100

0 250 500 750 1,000 1,250 1,500

Cost [K$]

Avai

labi

lity

(%)


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Numerical Results: Case C

30

40

50

60

70

80

90

100

0 250 500 750 1,000 1,250 1,500

Cost [K$]

Avai

labi

lity

(%)

1 Aircraft in 1 quartera) Life Limits


c) Initial ages


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Conclusions• AT LAST Deployment Push Pack

Spares Optimization Module is both accurate and efficient

• Further developments will include:– An automatic adjustment mechanism– Improved handling of “coinciding” LRU

removals occurrences– Importing optimization results to the master

database


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Thank You


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Backup Slides


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Mathematical FormulationMarkov Process States

0 1 s + 1 s + 2s s + nm -1 s + nm

nm nm nm nm (n m -1) 2(nm -2)

2 s (s + 1) (s + 2) (s + nm -1) (s + nm )(s + 3)

0 1 s + 1 s+ 2s s + nm -1 s + nm

nm nm nm nm nm nm nm nm

2 s (s + 1) (s+ 2) (s + nm -1) (s + nm )(s + 3) (s + nm +1)

nm nm nm

(s +nm +i) (s + nm + i+ 1)

s + nm +i

AT-LAST – Finite Markov State Process

Traditional – Infinite Markov State Process

n=number of systems

m=number of LRU’s per system

s= number of spares

= effective failure rate

= repair turnaround rate

Legend

Same failure rates (enough spares to ‘fill up’ for failed units)

Reducing failure rates (function of operational units)

Repair rates function of number of failed units

Constant failure rates (independent of number of failures)

Repair rates function of number of failed units


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Steady State Markov Equations01 PnmP0

1s1s2ss P)1s(P)1nm(P)2s(Pnm0

nms1nms P)nms(P0

ss1s1s PsPnmP)1s(Pnm0

State 0

State sState s+1

State s+nm

1Pnms

0ii

Boundary Condition

01 PnmP0

ss1s1s PsPnmP)1s(Pnm0

State 0

State s

State s+nm

1P0i

i

Boundary Condition

nmsnms1nms1nms P)nms(PnmP)1nms(Pnm0


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Steady State Probabilities

nmsisifP!s

nm!i)!isnm(

!s!nm

si1ifP!i

nm

P

0

sssi

0

ii

i

1nms

1si

sisss

1i

ii

o !i)!isnm(!s!nm

!snm

!inm1P

0

i

i P!i1nmP

eP0

i1if

Poisson Distribution


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Little Theorem HW

s

0i

1nms

1si

siss

i1i

sinms

1si

ss

T!i)!1isnm(

!s!nmT!s

nmT!i

nm

T!i)!isnm(

!s!nm)si(T!s

nm

)s(W

nm!ieTnm)si(

)s(W

Tnmi

1si

1TWhere:

1TWhere:

MTTRMTTF1


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Unavailability Estimates

L

1iiiiii

L1sys

))s(WMTTR(m1

11)s,...,s(U

ii MTTF

1Where: calculated from outputs

ATLAST Expression: Applicable for serial systems in which LRU’s do not fail while the system is down

atlast deployment &push pack spares optimizer

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