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  • Advanced M&S applied to

    Analysis Techniques for

    Supporting Decision Makers in

    Multi-Job Management in an

    Aeronautical IndustryAuthor: Enrico Briano

    Advisor: Prof. Agostino G. Bruzzone

    MISS Genoa Center - DIPTEM

    Co-Advisors: Matteo Cecada

    Giorgio Garassino

    Piaggio Aero Industries

    Francesco LongoUniversity of Calabria

  • Goals of the Research

    The main goal of the Research is to reduce

    the Assembling Line Lead Time. In order to

    reach this goal is requested to:

    Identify and Analyze Criticalities

    Reorganize all the Phases of the

    Production Process

    Evaluate the Impact of all the Stochastic

    Phenomena

  • First Hypothesis of Assembling

    Line Lead Time Reductionoperai/giorni 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

    1 6 6 6 6 6 6 11 11 17 17 23 23 23 23 23 23

    2 8 8 8 10 10 10 11 11 17 17 23 23 23 23 23 23

    3 9 9 9 9 9 9 9 9 9 9 9 9 18 18 18 18 18 18

    4 12 12 13 13 13 13 24 24 24 24 23 23 23 23 23 23

    5 12 12 13 13 13 13 24 24 24 24 23 23 23 23 23 23

    6 15 15 15 10 10 10 14 14 14 14 14 14 34 34 34 34 34 34

    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

    6 1 1 1 1 1 1

    8 1 1 1

    9 1 1 1 1 1 1 1 1 1 1 1 1

    10 2 2 2

    11 2 2

    12 2 2

    13 2 2 2 2

    14 1 1 1 1 1 1

    15 1 1 1

    17 2 2 1 1 1 1 1 1

    18

    23 4 4 4 4 4 4

    24 2 2 2 2

    34 1 1 1 1 1 1

    6 6 6 6 6 6 4 4 0 0 4 4 6 6 6 6 6 6 6 6

    Squadra B

    Garbati

    Salvador

    Cecchini

    Assy portelli principali e posteriori

    Squadra A

    Bidone

    D'Agostino

    Zone

    TE

    ST

    WE

    E

    Canepa

    Astengo

    Gaggero

    Fois

    Macci

    Palladino

    TE

    ST

    WE

    E

    Installazione portello bagagliaio

    Installazione particolari fuori scalo

    Installazione alettoni

    2Turno

    Predisposizione Modifiche

    Installazioni Portelli

    Installazione Canard

    Installazione antenne

    installazione pinne

    Raccordo ala fusoliera

    1Turno

    50 ore 1pers

    Predisposizione bulbo deriva

    Predisposizione poppino

    25 ore 1 pers

    110 ore 1pers

    50 ore 2 pers

    35 ore 2pers

    25 ore 2 pers

    60 ore 2 pers

    installazione Flap

    persone per giorno

    200 ore 4pers

    60 ore 2 pers

    58 ore 1persVerniciatura basico

    50 ore 1 pers

    24 ore 1 pers

    35 ore 2 pers

    50 ore 1 pers

    Data have been Modified due to their Confidential Nature

  • Methodology

    Build Simulators and Models devoted to analyzeRisks and Criticalities

    Development and Analysis of the Assembling LineSystems in order to: Reduce the Aircraft Mean Lead Time from 6 to 4 Months

    Reduce WIP

    Decrease the Number of Aicrafts simoultaneously present inthe Assembling Line

    Save a significant amount of Money in terms of BankingInterests

    Distribute better Resources on Planes

    Have a Positive impact on the Company Cash Flow

  • Station 8

    Slipway

    Station 8 bis

    Initial

    Arrangements

    Station 7

    Assembling

    Station 7 bis

    Moving Parts

    and Fillings

    Station 8 ter

    Interiors

    Trimming

    Final Tests

    2 Stations

    Station 4

    Final Interiors

    Assembling

    Station 5 bis

    Functional Tests

    Station 5

    High Value

    Components

    Station 6 bis

    Painting

    Station 6

    Installations

    The Present Productive

    Processes

    Total: 12

    Phases

    LT = 24

    Weeks

  • New Assembling Line

    Station 8

    Slipway

    Final Tests

    Station 1

    Station 2

    Final Interiors

    Assembling

    Station 3

    Functional Tests

    Station 4

    High Value

    Components

    Station 5

    Painting

    Station 6

    Installations and

    Fillings

    Total: 8 Phases

    LT = 16 / 18 Weeks

  • Departments to beReengineered

    Assemblers Dept.: Code 742 Carpenters

    Fillers

    Commanders

    Planters

    HVAC

    Assemblers

    Electricians Dept.: Code 744

    Interiors Dept.: Code 745

    Painters Dept.: Code 743

  • Data Collection

    Data were acquired by the

    Authors using the

    LAN-Based Company

    Informative System (CX)

    The Main Functions are:

    Inventory Status

    Bills Control

    Job Progress Control

    Worked Hours Control

  • Performance Analysis(Dept. 742)Att. Rep. 742

    0%

    50%

    100%

    150%

    200%

    250%

    300%

    0% 50% 100% 150% 200% 250% 300%

    Media / Ass.to

    Ma

    x / M

    in

    Data are Modified for Privacy Reasons

    Mean Extra-cost for 742 Dept. Is 30%compared with Scheduled

    Data have been Modified due to their Confidential Nature

  • Solar Simulator

    VBA Simulator based on the real Job Completion Time

    Dates extracted from the Bills start and finishing time(CX)

    Mean Airplane Lead Time overestimated based onstatitistical analysis

    Necessity to validate data and to develop a more

    detailed model

  • M.A.C.A.C.O. Simulator

    Stochastic Discrete Event Simulator

    Job Duration-Based historical data (from Aircrafts NC

    1077 to NC 1086) and experts estimation by beta

    distribution

    Production Process Model using concurrent PERT for

    each plane considering resources and constraints

    C++ built and animated

    Stochasticity provided by different probabilitydistribution; deterministic case is also allowed

    Allows formulating What-If Analysis on Criticalitiesand Bottlenecks by variating Input Data

  • Modelling Air Craft Analysis for

    Construction process and

    OrganizationInterface

    allows toevaluate:

    Job Status Production

    Real TimeLead Time

    Resource

    SaturationLevel

    UtilizationCoefficients

    PositionsSaturation

  • Bottleneck 49 Analysis(Test Press)

    Sensitivity Analysis: Bottleneck 49

    A

    B

    C

    D

    AB

    AC

    AD

    BC

    BD CDABC

    ABD

    ACD

    BCD

    0.0001

    0.001

    0.01

    0.1

    1

    10

    Eff

    ec

    ts

    Input Factors

    A: 46 Activity

    B: 47 Activity

    C: 48 Activity

    D: 52, 53 Activities

    F/F

    tab

    Activity 49 is a Bottleneck in the process: the causes

    of this phenomenon are the criticality of activities 52 e

    53 and the influence of the sinergy of activities 46 and

    48

    Data have been Modified due to their Confidential Nature

  • Sensitivity Analysis on

    Criticalities (1/2)

    26 Factorial Project based on Critical Path Activities

    Duration and on the Number of Fillers andAssemblers

    1814F: N OF ASSEMBLERS

    64E: N OF FILLERS

    140%60%D: CRITICALITY DURATION COEFF. Station 5

    140%60%C: CRITICALITY DURATION COEFF. Station 6

    140%60%B: CRITICALITY DURATION COEFF. Station 7

    140%60%A: CRITICALITY DURATION COEFF. Station 8

    MAXMINFACTOR

  • Sensitivity Analysis on

    Criticalities (2/2)Sensitivity Analysis: Criticalities

    A

    B

    CD

    E

    F

    AB

    AC

    AD

    AE

    AF

    BC

    BD

    BE

    BF

    CD

    CE

    CF

    DE

    DF

    EF

    ABC

    ABD

    ABE

    ABF

    ACD

    ACE

    ACF

    ADE

    ADF

    AEF

    BCD

    BCE

    BCF

    BDE

    BDF

    BEF

    CDE

    CDF

    CEFDEF

    ABCD

    ABCEABCF

    ABDE

    ABDFABEF

    ACDE

    ACDF

    ACEFADEF

    BCDE

    BCDFBCEF

    BDEF

    CDEF

    ABCDEABCDF

    ABCEF

    ABDEF

    ACDEFBCDEF

    0.000001

    0.00001

    0.0001

    0.001

    0.01

    0.1

    1

    10

    100

    1000

    Eff

    ec

    ts

    Input Factors

    A: St. 8 Criticalities

    B: St. 7 Criticalities

    C: St. 6 Criticalities

    D: St. 4 Criticalities

    E: # of Fillers

    F: # of Assemblers

    F/F

    tab

    Lead Time is strongly affected by criticalities on

    Stations 8, 6 and 4

    Data have been Modified due to their Confidential Nature

  • DOE & RSM Application

    16.0

    16.3

    16.6

    16.9

    17.2

    17.5

    17.8

    0.30

    0.50

    0.70

    0.90

    1.10

    14.414.715.015.315.615.916.216.516.817.117.417.718.018.318.6

    Plane Lead Time [weeks]

    F

    B

    Response Surface Methodology: Lead Time

    18.3-18.6

    18-18.3

    17.7-18

    17.4-17.7

    17.1-17.4

    16.8-17.1

    16.5-16.8

    16.2-16.5

    15.9-16.2

    15.6-15.9

    15.3-15.6

    15-15.3

    14.7-15

    14.4-14.7

    Local Best is at theminimum duration of

    Station 7 criticalities

    and at the maximumnumber of

    Assemblers

  • ANN Methodology Applied to thePlane Delivery Date Analysis

    Full Connected FeedForward Architecture

    Back Propagation Algorythm

    23 runs during Training

    23 runs during Test

    10 inputs: from job 49 to 58

    (Station 6)

    2 levels hidden layers

    1 output: Delivery Date

  • ANN Methodology Results(1/3)

    M ax

    Average

    Min

    Training

    Test0.00%

    1.00%

    2.00%

    3.00%

    4.00%

    5.00%

    6.00%

    7.00%

    8.00%

    Err

    or

    [%]

    Error Type

    Set

    Errors for Predition of Plane Delivery in the Different Sets

    Training

    Test

    7.96 %3.12 %TEST SET

    0.11 % 0TRAINING

    SET

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