Electronic Assembly Process - Part 1

1Arena Tutorial 3 - Electronic Assembly Process - 1© 2009 – Mark Polczynski

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Arena Tutorial 3 –

Electronic AssemblyProcess - Part 1

Technology

Forge

Version 1.0

Arena Tutorial 3 - Electronic Assembly Process - 1 2

Tutorial Objectives:

• Create a basic model of an electronic assembly process.

• Use an Assign module to assign different delay times for different assemblies.

• Use Record modules to create new measures of system performance.

• Review the properties of the often-used Weibull probability distribution.


Metalcase

Circuit board

Sealant

Metalcase

Metal case comes in 2 versions:

Part A and Part B

Top and bottom case pieces are

identical.

ElectronicAssemblyExample


Process we will be

simulating

Context Diagramfor this Example

Electronic

Assembly

Part A

Case Supplier

Part B

Case Supplier

Ship

Scrap

Salvage

Part A

Part B

Good

assembly

Salvaged

assembly

Scrap

assembly

Circuit Board

Supplier

Circuit

board

Store Room

SealantCase

Case


Simulation goals are to collect statistics on:

• Resource utilization for each resource – What percent of the available work time is each resource in the process busy?

• Number of units in queue at each operation – How many units are waiting to be worked on at each operation?

• Time in queue at each operation – How long does each unit wait to get worked on?


Do not include circuit boards and

sealant in this model


Basic Model

Desired statistics for each process module:

- Resource utilization- Units in queue- Time in queue



Do these next…

Configure Create Modules


ConfigureFinish Part A

Surfaces


Next

ConfigureFinish Part B

Surfaces


We will return to this module later to specify Delay Type

Start configuring theSeal Assembly

module


Do this next…

Configuredecision modules


ConfigureRework Seal

module








Part A and Part B have different

delay times

Finish configuring theSeal Assembly module


Start configuring theAssign module

for Part A


Finish configuring theAssign module

for Part A


Start configuring theAssign module

for Part B


Finish configuring theAssign module

for Part B


0

0.05

0.1

0.15

0.2

0.25

0 2 4 6 8 10 12

Pro

bab

ility

Sealer Time (minutes)

Weibull distributionof Sealer Times

/1)( xexxf

α = 2.5 β = 5.3

x

Time between arrivals

Probability of next part arriving x minutes after previous part


Finish configuring the Seal Assembly module




Runsimulation!




Review results




Review results


Change pictures for Part A and Part B


Animate resources


Animated model








Simulation goals are to collect statistics on:

• Resource utilization for each resource – What percent of the available work time is each resource in the process busy?

• Number of units in queue at each operation – How many units are waiting to be worked on at each operation?

• Time in queue at each operation – How long does each unit wait to get worked on?

• Cycle time – How long does each part take to get through the entire system?• Good assembly cycle time,• Salvaged assembly cycle time,• Scrap assembly cycle time.

Addcycle time statistics


Cycle time:How long does each part take to get through the entire system?

• Good assembly cycle time,• Salvaged assembly cycle time,• Scrap assembly cycle time.

How does this split out?


Addcycle time recorders


Configure the Record

modules

The other Record modules are

configured similarly

From a few slides ago


Cycle times for assemblies







Arena Tutorial 3 - Electronic Assembly Process - 1

36

The Weibull distribution can take on many shapes,depending on the values of the shape parameters:

• a ~= 1

• a ~= 4

• 1 < a < 4

abta

aet

b

a )/()1(

Review of Weibull

distribution


37

abta

aet

b

a )/()1(

For a = 1, Weibull reduces to Exponential…

1)/()11(

1

1 btetb

)/()0(1 btetb

)/(1 bteb

)( te b/1


38

f(t):for Weibull

0.0000000

0.0100000

0.0200000

0.0300000

0.0400000

0.0500000

0.0600000

0.0700000

0.0800000

0.0900000

0.1000000

0 10 20 30 40 50 60

Weibull: a=1

Weibull: a=.8

Weibull: a=1.2

abta

aet

b

atf )/()1()(

Plot 1 Plot 2 Plot 3

Exponential λ = 0.1

Weibull a = 1 0.8 1.2b = 10 12.98 8.05

Effect of varying a for Wiebull


Weibull vs Normal

0

0.005

0.01

0.015

0.02

0.025

0.03

0 10 20 30 40 50 60 70 80 90 100

Normal

Wiebull: a=4

Wiebull: a=3

Wiebull: a=5


Wiebull a 4 3 5

b 55 43 68

Normal a 50

b 14.5

For a ~4, Weibull mimics Normal Distribution


f(t) for Weibull Disctibution

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

0 20 40 60 80 100 120 140

a=1.2

a=2

a=2.5


a = 1.2 2 2.5

b= 42 48 56

Wiebull for: 1 < a < 4


The Arena Input Analyzer can help us to use the best time distribution models:








Contact the Author:

Mark Polczynski, PhDThe Technology [email protected]

mailto:[email protected]

Documents

Electronic Assembly Process - Part 1