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IET 525 System Analysis and Simulation Instructor: William J. Bender, Ph.D., PE, Office phone:...

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IET 525 System Analysis and Simulation Instructor: William J. Bender, Ph.D., PE, Office phone: 963-3543, Home # 509 933-3583 E-mail: [email protected] please call or write Web Page www.cwu.edu/~benderw/benderw.html this page has syllabi, exams, and handouts Teaching Philosophy this is a graduate course students do a lot of reading and learning on our own. Class is for reviewing concepts, discussion, and group exercises. Labs are performed on students time “doesn’t have to be Wed night” • Syllabi
Transcript

IET 525 System Analysis and Simulation

• Instructor: William J. Bender, Ph.D., PE,

• Office phone: 963-3543, Home # 509 933-3583 E-mail: [email protected] please call or write

• Web Page www.cwu.edu/~benderw/benderw.html this page has syllabi, exams, and handouts

• Teaching Philosophy this is a graduate course students do a lot of reading and learning on our own. Class is for reviewing concepts, discussion, and group exercises. Labs are performed on students time “doesn’t have to be Wed night”

• Syllabi

IntroductionChapt 1

• Need for Modeling & Simulation• Terminology• Model Building• Simulation

– Simulation Modeling & Analysis McGraw-Hill, by Law & Kelton– Discrete -Event Simulation Prentice Hall, by Banks, Carson, & Nelson

• Simulation of a Bank Teller• Data Collection/ Statistics• Apply what you know pg 17

Needfor Modeling & Simulation

• Chemicals, Pharmaceuticals, hospitals, shipping, retail, defense, electronics, construction, manufacturing, shipping, communications

• …all industries need a method to “try something out” before building or changing a process/ manufacturing line.

• Bottom line helps decision makers solve complex problems by providing a systematic process to develop data, experiment and see what happens

Simulation

• “Building logical & mathematical models of real or proposed systems & use PCs to experiment with the parameters/ resources of the system.

• We will simulate systems via a simulation language called Visual SLAM…very user friendly

• AweSim is a program that runs the simulation & animates Visual SLAM … very user friendly

• one of many…I learned Extend a graphical simulation package that my dissertation was formed around

System

• We will perform “Systems Analysis” by modeling and simulation systems & see what happens

• A system is “Interdependent items that describe the area of interest or perform a specific function”

• And is defined by the SCOPE of the problem we are trying to solve

Construction System

Trades, Equip, Material, Processes, etc

Design

Weather

Rules

Suppliers

System

• External forces may effect system– Include– Ignored– Treated as inputs

Construction System

Trades, Equip, Material, Processes, etc

Design

Weather

Rules

Suppliers

Models

• Models are the description of systems/ abstract of the system– Physical ie WSU hydraulic lab

– Math ie Differential equations, logical (CPM)

– Graphical ie visual computer displays

• First models are built…then simulated to understand interactions of elements

Model Building

• Key is defining the elements of the model/ system & how they interact with each other– Problem statement or Goal

– Established boundaries

– Performance measures/ Design alternatives

• Takes an iterative process

System Goal

Boundaries

Performance

Model Simulate &

Solve Problem

Simulation

• Build Models and experiment with it on a computer• Benefits

– Work out bugs before built if proposed ie hospital/ man line

– W/O disturbing operating systems

– NTD

Model Design

Parameters

Performance

Simulate Solve Problem

Simulation States Discrete or Continuous

• Continuous = constantly changing ie weather, waves, auto pilot

• Discrete Event = Small incremental steps ie construction, bank teller, manufacture line, etc– Deterministic ie 10 minutes or 2 days

– Stochastic ie normally distributed, mean =10, std =2

Simulation of Bank Teller

• An example to show where we are going…• Want to model the operations of a bank determine how

long a person waits in line and % of time a teller is idle• Model is:

Wait for tellerCustomer Arrives

Served by teller

Exit bank

How Long? % of time idle?

Simulation of Bank TellerConcepts

• At any instant model is in a particular state• As events occur, state changes• Events define the model

Wait for tellerCustomer Arrives

Served by teller

Exit bank

How Long? % of time idle?

Simulation of Bank TellerCustomer

#ArrivalTime

Service time

1 3.2 3.82 10.9 3.53 13.2 4.2

Cus # Arrtime

Sertime

StartDeptime

Timein line

Timeinbank

(1) (2) (3) (4) (3)-(2) (4)-(2)

1 3.2 3.2 7.0 0 3.82 10.9 10.9 14.4 0 3.5

3 13.2 14.4 18.6 1.2 5.4Pg 8& 9

Simulation of Bank TellerEvent oriented Description

TimeEvent

Cus#

Event # inline

# inbank

Teller Idletime

0.0 1 St 0 0 Idle3.2 1 Arr 0 1 Busy 3.2

7.0 2 Dep 0 0 Idle

To track customers in line & teller busy or idle at discrete points in time

Time

# in line

Pg 10 & 11

Simulation of Bank TellerEvent oriented Description

Time

Busy

•Need Data

•At any point in time the model is in a particular state

•Need “Book keeping” function to track changes

•Two perspectives 1)Customer 2)Teller

Idle

Teller Status

Data Collection & Analysis

• Use existing Data or Collect Data• Existing data, ie census, cost data, government…may be

easily obtained but typically very broad• Surveys especially for qualitative material..Delphi• Field Studies/ experimenting, expensive but best type• Descriptive Statistics

Data Collection & Analysis Descriptive Statistics

• Grouping Data• Group Data into cells for Frequency Distribution or

Cumulative Frequency• Displayed graphically as Histogram

# of People

Ave wait time

Data Collection & Analysis Descriptive Statistics

• Parameter Estimation• Population = All possible observation• Sample = only part of population

• Can estimate Population with mean = and

variance = 2

• From a sample can find mean & variance to describe a population

Data Collection & Analysis Descriptive Statistics

• Distribution Estimation• Use a know statistical distribution to estimate a

population, ie normal, beta, exponential, weibel

Chapt 1 Summary

• Build Model based on goal, parameters, design, performance

• Simulate to experiment with model and solve problem• Can use statistical estimation for data

Chapt 1 Exercises

• # 1-2 pg 18 Build a model for the MSET program from the students point of view similar to Figure 1-1

• # 1-6 Describe/ draw the functional/mechanical operation of a car using boxes connected with arrows, use chassie, engine, transmission, wheels …by developing a model. How can this be simulated to understand the performance characteristics of Speed, MPG, cargo capacity, cost, performance ie 0-60mph time

Chapt 1 ExercisesSolution

• # MSET program model similar to Figure 1-1

MSET

Course Interest

Project interestAdvisor/ Committee

Financial

Rules/ degree requirements

Available Classes

Others?

Chapt 1 ExercisesSolution

• # 1-6 Describe/ draw the functional/mechanical operation of a car using boxes connected by arrows, use chassie, engine, transmission, wheels …by developing a model. How can this be simulated to understand the performance characteristics of Speed, MPG, cargo capacity, cost, performance ie 0-60mph time

Chassie engine Trany Wheels

Simulate by changing:weight, wheel base, engine size, engine turbo, engine gas/ diesel, trany gears, wheel size and out put performance of speed, MPH, HP, Size, Cost…others

Chapter 2 Simulation Modeling Perspectives

• Modeling World Views• Discrete Simulations• Continuous Simulations• Visual SLAM

Simulation World Views

• The functional relationship of how a system is perceived and described

• Either:

• Discrete – Dependent variables change at specific points in simulated time

• Continuous– Dependent variables continuously change in simulated time

Discrete

• Discrete = Dependent variables change at specific points in simulated time– Construction of a road, Dependent Variable = % complete, specific lane openings – Window assembly line, Dependent Variable = people idle/busy, machine

idle/busy– Bank Teller Dependent Variable = # of customers, teller idle busy

Event Times

Dependent Variable

Continuous

• Continuous = Dependent variables continuously change in simulated time– Sine wave approximation of an ocean wave Dependent variable is the height

of the wave– Position of a space craft Dependent variable is exact location in orbit– Auto pilot of an aircraft, Dependent variables are speed, bearing, attitude, etc

Time

Dependent Variable

Combined

• Both discrete and continuous• Some activity develops slowly over time and at a specific

event the state changes• Chemical process, slowly reaches a certain concentration

then a catalyst is added an an explosion occurs

Event Times

Dependent Variable

Discrete Simulation Modeling

• Goal = Reproduce the activities the entities are engaged in to learn about the behavior of the system.– Entities = Objects within the boundaries of discrete system ie people, machines, $,

resources

– Activities = discrete function, unit of work

– Event = Start or stop of an activity

– Process = sequence of events that includes several activities

Discrete Simulation Modeling

Discrete Sim formulated by 3 methods:• Event Orientation = Define changes in the state at each event time (Busy/Idle)• Activity Scanning Orientation = Describe the activities which entities engage

in (system state based on activities condition)• Process Interaction orientation = Describe process which activities flow

(CPM)

Discrete Simulation Modeling Event Orientation

• Define changes in the state at each event time (Busy/Idle)• Done by: Determine the events that can change the state of the system & use logic to

model the system• ie Bank System

– Status of teller

– # of customers

• Performed by maintaining a calendar of events and cause their execution simulated time

Discrete Simulation Modeling Activity Scanning Orientation

• Describe the activities which entities engage in (system state based on activities condition).

• Done by: describing activities & prescribe conditions which cause an activity to start or end

• Not used much (must scan all activities) except when an activity is indefinite or determined by a prescribed condition

Discrete Simulation Modeling Process Interaction Orientation

• Describe process which activities flow (CPM)• Simulation that includes elements that occur in defined

patterns• Manufacturing/ construction/ where you want to

understand the entire process

Discrete Simulation Modeling Process Interaction Orientation

Model the flow of entities thru a system & define a sequence of events that are executed by the simulation

Continuous Simulation Modeling

• Dependent Variables change continuously over time• Models are frequently written as derivatives….or

differential equations• State variable SS (wave height/ speed) over time T want to

determine the response of the variable over time

2 2 t t)(s dt

ds(t)

•Or integrate ds/dt over time using numerical integration methods using simulation

Visual SLAMAweSim

• Visual SLAM is the computer language that is specifically written for simulation

• AweSim is the software product that combines language with modern window, graphics…makes SLAM user friendly

• Visual SLAM able to do discrete simulations as event or process orientations or both. Also does continuous and combined continuous/discrete.

Visual SLAMAweSim

• Consists of nodes and branches to model queues, servers, machines and decision points.

• DE modeler defines the events and the changes to the system when events occur

• Continuous model is represented by diff eq that describe the dynamic behavior of of the state variables

Modeling Perspectives Summary

• Discrete Simulations...three orientation mostly use– Event – Process

• Continuous Simulations– Defined by diff eq for constant changes

• Visual SLAM/ AweSim– Computer Language that performs simulation

• Will become clearer when we work with a simulation

Modeling Perspectives Exercises

• Page 32• # 2-3 Paint shop describe system using event orientation

and process orientation• #2-4 Describe HVAC control in terms of state variables,

time events and state events

Modeling Perspectives Exercises Solutions

• # 2-3 Paint shop – event orientation 4 events, 1) arrive to prep area, 2) complete prep, 3) arrive at spray machine, 4) end spray/take

out – process orientation essentially visualize an entity going thru the following sequence waiting for prep, prep,

travel to spray, wait for spray, spraying

• #2-4 Describe HVAC control – state variable = temperature– time events = reset thermostat, turn on heat or cool, breakdown, lose power– state events temperature crosses the thermostatic setting….moisture content to turn on/off humidifier


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