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SMS > SMS Module 1 > Flashcards

SMS Module 1 Flashcards

1
Q

Simulation Definition

A

Simulation is the imitation of a real world process or system over time. It helps us to study the behavior of a system as it evolves.

It can be done either by hand or using a computer using the mathematical and symbolic relationships between entities of the system.

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2
Q

Appropriate Use Cases For Simulation

A
  1. To study and experiment on complex systems and understand their internal interactions.
  2. It can be used to experiment on systems with new policies or designs prior to implementation.
  3. It can be used to verify analytical solutions.
  4. Knowledge gained from simulation can be great value towards improving the system under investigation.
  5. Valuable insight can be gained about which variables are important and how they interact from simulations.
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3
Q

Inappropriate Use Cases For Simulation

A
  1. When a problem can be easily solved using common sense.
  2. When a problem can be easily solved using analytical solutions.
  3. It’s easier to experiments in real life.
  4. Development cost of the model exceeds that of performing experiments.
  5. If there is less or no data is available.
  6. If the system behavior is too complex or cannot be defined.
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4
Q

Advantages Of Simulation

A
  1. New policies, designs, decisions etc can be explored and tested without disrupting the ongoing real system.
  2. New designs and systems can be tested without committing actual or physical resources.
  3. Insight can be gained about which variables are important to the performance of the system.
  4. Insight can be gained about various interactions between variables in the system.
  5. Hypothesis about how or why phenomena occur can be tested for feasibility.
  6. Bottleneck analysis can be performed to gain insights about how, why and where processes are delayed.
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5
Q

Disadvantages Of Simulation

A
  1. Model building requires special training, it is an art learned over time and through experience.
  2. Simulation modeling and analysis can be time consuming and expensive.
  3. Two models constructed by two competent individuals may have similarities but will never be the same.
  4. Results obtained from simulation maybe hard to interpret, it is hard to determine if observation is result of interrelationships in the system or pure randomness.
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6
Q

Steps In A Simulation Study

A
  1. Problem Formulation
  2. Setting of objective and overall project plan
  3. Model conceptualization
  4. Data collection
  5. Model translation
  6. Verification
  7. Validation
  8. Experimental Design
  9. Production runs and analysis
  10. More runs
  11. Documentation and reporting
  12. Implementation

Refer Simulation Study Diagram

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7
Q

Step 1 : Problem Formulation

A
  1. Every study should begin with a problem statement.

2. The analyst and policy makers both must clearly understand the problem statement and agree with it’s formulation.

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8
Q

Step 2 : Setting Of Objective And Overall Project Plan

A
  1. The objective indicates the questions to be answered by simulation.
  2. The overall project plan must include :
  3. 1 Statement of alternative systems
  4. 2 Method for evaluating effectiveness of alternatives
  5. 3 Cost of study
  6. 4 The number of days or time required and also the manpower or number of people involved in the study
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9
Q

Step 3 : Model Conceptualization

A
  1. Construction of a model is as much art as it is science.
  2. Modeling is enhanced by it’s ability to :
  3. 1 Abstract essential features of a problem
  4. 2 Select and modify basic assumptions that characterize the system
  5. 3 Enrich and elaborate the model until useful results are obtained
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10
Q

Step 4 : Data Collection

A

There is constant interplay between construction of a model and collection of necessary input data.

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11
Q

Step 5 : Model Translation

A
  1. Real world system result in complex models that require a lot of computation and storage.
  2. They can be programmed using simulation languages or special purpose software.
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12
Q

Step 6 : Verification

A
  1. The simulation program or model and it’s performance needs to be verified after development.
  2. It is verified only if the input parameters and logical structure are correctly represented.
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13
Q

Step 7 : Validation

A
  1. A model is validated to determine that a model is an accurate representation of the real system.
  2. It is achieved through calibration of the model, which is an iterative process of comparing the model to actual system behavior and identifying differences between the two.
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14
Q

Step 8 : Experimental Design

A
  1. The alternative designs that are to be simulated must be determined.
  2. For each experimental design, decisions need to be made such as :
  3. 1 Length of initialization period
  4. 2 Length of simulation runs
  5. 3 No. of replications to be made of each run
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15
Q

Step 9 : Production Runs And Analysis

A

They are used to estimate measures of performance for the system designs being simulated.

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16
Q

Step 10 : More Runs

A

Analyst determines if additional runs are required and what additional experiments that need to be performed based of past runs.

17
Q

Step 11 : Documentation And Reporting

A

Two types of documentation

  1. Program documentation : Used by analysts to understand how the model/program operated.
  2. Process documentation : History of the simulation project, analysis results, alternatives, experiment results etc
18
Q

Step 12 : Implementation

A
  1. Success of the implementation depends on previous steps.
  2. If the model user has been thoroughly involved in the process, the likelihood of a good implementation will have been increased.
19
Q

Entity

A

An entity is an object of interest in a system.

Ex : Departments, orders, parts etc are entities in a factory system.

20
Q

Attribute

A

An attribute denotes the property of an entity.

Ex : Quantities of each order, number of machines in each department.

21
Q

Activity

A

Activities represent a time period of specified length.

Ex : Manufacturing process, service time

22
Q

System State

A

It is defines as a collection of variables necessary to describe a system at any time, relative to the objective of study.
Ex : Busy or idle state of server

23
Q

Event

A

An event is defined as an instantaneous occurrence that may change state of system.

  1. Endogenous : Activities and events occurring within a system.
  2. Exogenous : Activities and events occurring in an environment that affects the system.
24
Q

Event Notice

A

A record of an event to occur at current time or future along with necessary data to execute the event.
Ex : Arrival of customer at clock 8 with customer number as data.

25
Q

Delay

A

Duration of time of unknown length. The duration is known only when it ends.
Ex : Customer waiting in line for service to begin.

26
Q

FEL

A

Future Event List - list of event notices for future events ordered by time of occurrence.

27
Q

Clock

A

A variable representing simulated time.

28
Q

System

A

A collection of entities that interact together over time.

Ex : Bank, grocery store

29
Q

Average Waiting Time

A

Total time customers wait in queue / Total no. of customers

30
Q

Probability Of Waiting

A

No. of customers who wait / Total no. of customers

31
Q

Average Service Time

A

Total service time / Total no. of customers

32
Q

Probability Of Idle Server

A

Total idle time of server / Total simulation time

33
Q

Average Time Between Arrival s

A

Sum of all time between arrivals / No. of arrivals - 1

34
Q

Average Waiting Time For Those Who Wait In Queue

A

Total time customers wait in queue / Total no. of customers who wait

35
Q

Average Time Customer Spends In System

A

Total time customers spend in system / Total no. of customers

SMS (2 decks)

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