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Representing system

• System:– a collection of mutually interacting objects

designed to accomplish a goal (machines repair system)

• Entities:– denotes an element/object within boundary of

system (machines, operators, repairman)• Entity – work being performed on object• Resource – performing the work

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System– Manufacturing facility/ system– Bank operation– Airport operations (passengers, security, planes, crews,

baggage)– Transportation/logistics/distribution operation– Hospital facilities (emergency room, operating room,

admissions)– Computer network– Business process – Chemical plant– Fast-food restaurant– Supermarket– Theme park– Emergency-response system

Representing system

• Attribute:– Characteristic or property or an entity (machine

ID, Type of breakdown, time that machine went down)

• Activity:– transforms the state of an object usually over

some time (repairman service time, machine run time)

Representing system

• State of the system:– Numeric values that contain all the information

necessary to describe the system at any time.

• Events:– Change the state of the system(end of service of

machine,machine breaks down) • Endogenous

– Activities and events occurring with the system

• Exogenous– Activities and events occurring with the environment

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Types of Simulation Models

Static

System model

Deterministic Stochastic

Dynamic Static Dynamic

Continuous Discrete Continuous Discrete

Monte Carlo simulation

Discrete-eventsimulation

Simulates the behavior of entities when an event occurs at a distinct point in time

Types of Simulation Models

• A deterministic simulation model is one that contains no random variables;

• A stochastic simulation model contains one or more random variables

Types of Simulation Models

• A static simulation model is a representation of a system at a particular point in time. [Monte Carlo simulation]

• A dynamic simulation is a representation of a system as it evolves over time.

Types of Simulation ModelsDiscrete event:

state of system changes only at discrete points in time(events)

Types of Simulation Models

Continuous event:State of system changes continuously over time

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Simulation methods

Spread sheet simulation [0,T]

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Simulation of such systems is easily accomplished by partitioning

simulated time into discrete intervals of length dt and stepping

the system through time one dt at a time.

System dynamics is an approach to understanding the behaviour of

complex systems over time. It deals with internal feedback loops and time

delays that affect the behavior of the entire system.

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Modeling of a system as it evolves overtime by a representation

where the state variables change instantaneously at separated

points in time

Discrete Event Simulation

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Problemformulation

Setting ofobjectivesand overallproject plan

Modelconceptualization

Datacollection

Modeltranslation

Verified?

No

Validated?

No

No ExperimentalDesign

Production runsand analysis

More runs?

Documentationand reporting

No

Implementation

Yes

YesYes

Yes

Simulation Steps

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Simulation Steps

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Applications: System Analysis

SIMULATION TYPICAL APPLICATIONS

Facility Layout.

Sequencing & Optimization In Assembly Line.

Capital Expenditure Assessment.

Capacity Requirement Planning.

Production Scheduling.

Production Process Improvement.

Supply Chain Logistics.

Service Level Reliability.

Labour Utilization.

Intermediate Storage.

Batch Production Sequencing.

Annual Delivery Program.

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Application Area – Auto Tube Manufacturing

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1. Improve equipment utilization

2. Reduce waiting time and queue sizes

3. Allocate resources efficiently

4. Eliminate stock-out (shortage) problems

5. Minimize negative effects of breakdowns

6. Minimize negative effects of rejects and waste

7. Study cost reduction plans

8. Establish optimum batch sizes and part sequencing

9. Resolve material handling issues

10. Study effect of setup times and tool changeovers

11. Optimize prioritization and dispatching logic for goods and services

12. Demonstrate new tool design and capabilities www.flexsim.com

Application Area – Packaging line design

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Application Area - Mining

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Application Area – Container Ports – Flexsim CT

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Application Area – Security Infrastructure – Border Check point

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Application Area – Aquarium Fish Export

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Application Area – Emulation

Emulation should allow you to go from testing to deployment with no code changes. Emulation should work like the real world.

PLSee is a plug-in module that enables communication between a running Flexsimsimulation and almost any PLC

www.flexsim.com

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Application Area – Healthcare – Flexsim HC

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Medical facilities

are among the

most complex in

the world.

Numerous factors

contribute to

overall efficiency

and work-flow, including:patient flowstaff utilizationresource management

www.flexsim.com

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DISRUPTIONS OF NATURAL & MAN-MADE

Wagner and Neshat (2010)

BUSINESS DISRUPTIONS

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BUSINESS DISRUPTIONS

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BUSINESS DISRUPTIONS

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BUSINESS DISRUPTIONS

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BUSINESS DISRUPTIONS

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Simulation survey

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Traffic-Signal Time Settings by Using Simulation

LCR

KR

RMRRHR

PHASE 1

LCR

KR

RMRRHR

PHASE 2

LCR

KR

RMRRHR

PHASE 3

LCR

KR

RMRRHR

PHASE 4

LEGEND

KR : KUTCHERY ROAD

RMR : RAMAKRISHNA MUTT ROAD

RHR : ROYAPETTAH HIGH ROAD

LCR : LUZ CHURCH ROAD

FIG.2 PHASE DIAGRAM OF THE INTERSECTION

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Problem Statement

The modelling of traffic systems is really difficult

complexity of road networks and random operation of vehicles.

Objective of minimizing the total delay caused to the vehicles at the intersection.

The signalized intersection connecting

Luz-Church Road, Royapettah High Road,

RamaKrishna-Mutt Road and Kutchery Road in Mylapore

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Simulation tool is used for fast analysis of alternate courses of action in time critical situations– Initialize simulation from situation database

– Faster-than-real-time execution to evaluate effect of decisions

Applications: air traffic control

Applications: On-Line Decision Aids

livedatafeeds

analysts anddecision makers

forecasting tool(fast simulation)

situationdatabase

interactive simulation environment

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Applications: On-Line Decision Aids

Air traffic control software failure

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A Few Example Applications

Wargaming: test strategies; training

Transportation systems: improved operations; urban planning

Computer communicationnetwork: protocol design

Parallel computer systems: developing scalable software

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Most unnatural deaths caused by road accidents, suicides: data July 3 2014

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pdf

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Applications

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Most unnatural deaths caused by road accidents, suicides: data July 3 2014

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SIMULATION PACKAGES

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SIMULATION PACKAGES

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SIMULATION PACKAGES

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SELECTION OF SIMULATION PACKAGES

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Geometric simulation systems simulate the geometry of an element or an entire manufacturing system, usually in three dimensions

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Journals

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Discrete Event Simulation

An actual or envisioned system A useful simulation model of that system

to

Modeling of a system as it evolves overtime by a representation where the state variables change instantaneously at separated points in time

Types of Simulation Models

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Types of Simulation Models

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Types of Simulation Models

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A hybrid optimization and simulation approach is emphasized for strategic decisions

under uncertainty.

Fu, Glover and April (2005)

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Components of DES simulation

Simulation clock: A variable giving the current value of simulated time. Unit of time is assumed to be same as unit of input parameters

Activity: A duration of time of specified length which is known when it begins eg. Arrival, Service time

List/set: A collection of associated entities ordered in some logical fashion

e.g. In an outpatient clinic a set might include the patience waiting for service ordered by severity of disorder or first come first serve

Event notice: A record of an event to occur at the current or future time along with associated data to execute the event.

Event List/Future Event List: A list of event notices for future events ordered by time of occurrence

Delay: A duration of time of unspecified length which is not known until it ends e.g. waiting time in queue

Statistical counters: Variables used for storing statistical information about the system performance.

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Currently in queue

Components of DES simulation

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Time advance mechanism

To advance the time from current event to the next scheduled

event

Two approaches:

Fixed increment time advance (Seldom used)

Next event time advance (Most common)

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Fixed increment time advance

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Fixed increment time advance

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Next event time advance

Most Imminent first

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Next event time advance

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Currently in queue

Components of DES simulation

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Next event time advance

•Assume that the probability distributions of the inter arrival times A1, A2, …and the service times S1, S2, … are known•At time e0 = 0 the status of the server is idle, and the time t1 of the first arrival is determined by generating A1

•The simulation clock is then advanced from e0 to the time of the next (first) event, e1 = t1. status of the server is changed from idle to busy. Delay is zero. •Generate S1, A2. If t2 < c1, the simulation clock is advanced from e1 to the next event e2 = t2 else to c1

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DES Time Advance Program• Initialization routine – a subprogram to Initialise the simulation model at time

zero

• Timing routine – a subprogram that determines the next event from the event list and then advances the simulation clock to the time when the event is to occur.

• Event routine – a subprogram that updates the system state when a particular type of event occurs

• Library routines – a set of subprograms used to generate random observations from probability distributions that were determined as part of the simulation model

• Report generator – a subprogram that computes estimates of the desired measures of performance and produces a report when the simulation ends

• Main program – a subprogram that invokes the timing routine to determine the next event and then transfers control to the corresponding event routine to update the system state. The main program may also check the termination and invoke the report generator when the simulation is over.

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DES Time Advance Program

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DES Time Advance Program

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DES Time Advance Program

Two techniques to generate future events

Bootstrapping occurrence of an event generates next occurrence of the same type of event

Next Logical event e.g. Service completion generates next event

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DES Time Advance Program

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DES Time Advance Program

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Manual simulation DES single server queue

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Manual simulation DES single server queue

Currently in queue

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Measures of performance

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Measures of performance

Product of previous value of Q (t) and the width of time interval between from last event to now

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Measures of performance

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