des
DESCRIPTION
AutomationTRANSCRIPT
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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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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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