KING FAHD UNIVERSITY OF PETROLEUM & MINERALS
COLLEGE OF COMPUTER SCIENCES & ENGINEERING
Department of Systems Engineering
SE 405
STOCHASTIC SYSTEM SIMULATION
LAB MANUAL
Prepared by
Mr. Shaikh Arifusalam
Mr. Atique W. Siddiqui
Mr. Al-Durgam
KING FAHD UNIVERSITY OF PETROLEUM & MINERALS
Systems Engineering Department
SE 405 (062)
Lab # 1
INTRODUCTION AND MANUAL SIMULATION
Objective 1: Introduction to Simulation.
A comprehensive introduction to the problem of simulation is given in this lab. The
students are introduced to the area by giving several examples from daily life. The
different nature of simulation-based programming is emphasized. The concepts of
timing and event list are illustrated through the use of relevant examples.
Introduction to the following concepts:
1.
2.
3.
4.
5.
6.
7.
8.
Need of simulation in real world problems.
Objectives attainable by simulation.
Use of simulation as a tool for solving complex problems in real life.
Different ways of simulation of problems.
Use of programming languages in simulation.
Different commercial packages like Awesim and ProModel.
Reliability of the results.
Single server queuing problem and its variations.
Objective 2: Understanding Manual Simulation.
To enable the students to perform manual simulation. This lab will guide the students
in understanding the basic operations behind a simulation problem in a step-by-step
process.
Things to do:
To conduct manual simulation the following is needed.
1.
2.
3.
4.
5.
6.
Define objectives of the single-server queue simulation problem.
Initialization of the problem.
Define Events and Event List.
Understand How to update state variables every time an event happens.
Understand the collection of statistics.
Stopping rule.
Assignment
The students are requested to perform manual simulation as given in the example
from the textbook for the single server queuing model. Tables are provided for
recording the stepwise change in the state variables and different parameters.
Systems Engineering Department
SE 405 (062)
Lab # 1
INTRODUCTION AND MANUAL SIMULATION
Assignment
Single Server Queuing System – Manual Simulation.
Consider the Example given in Page 11 in your text book for single server queuing
system. Event wise Table representation on manual simulation is explained. The
explanation in the book is done till the number delayed reaches to 6. Using the
following data, continue working on the same problem till the number delayed
reaches 10.
Arrival Times: A1=0.4, A2=1.2, A3=0.5, A4=1.7, A5=0.2, A6=1.6, A7=0.2, A8=1.4,
A9=1.9, A10=0.8, A11=1.2, A12=0.2, A13=1.0, A14=1.5, A15=0.5.
Service Times: S1=2.0, S2=0.7, S3=0.2, S4=1.1, S5=3.7, S6=0.6, S7=1.0, S8=0.5,
S9=1.5, S10=2.0, S11=1.2, S12=0.5, S13=1.3, S14=1.5, S15=0.5.
Calculate the following performance measures when you stop the simulation at the
number delayed as 10 customers.
a) Average number of customers in the Queue.
b) Average delay per customer.
c) Utilization of the server.
Also Provide the graphs for the number of customers in the queue Q(t) and the
Utilization of the server B(t).
Systems Engineering Department
SE 405 (062)
Lab # 2
SIMULATION USING ARENA
Objective:
To enable the students to perform a simple single server simulation using ARENA.
A handout for introduction to ARENA basic modules and a step wise manual for
single server simulation model is provided to the students.
Things to do:

Introduce the flow chart and data modules of ARENA.

Develop a single server model as per the data in the handout provided.

Compare the manual simulation with the model whenever required.

Obtain the SIMAN report and extract the results for the average waiting time
of the customers, average number of customers in the queue and the average
utilization of the server.

Further discuss the other related and significant results from the SIMAN
report as well as the other reports from the reports panel.
Systems Engineering Department
SE 405 (062)
Lab # 3
ENHANCING THE SINGLE SERVER MODEL
Objective: Enhancing the single server model build in the previous lab and introduce
the DECIDE module in ARENA.
Things to do:
Part A: Assume that radios arrive at a inspection center for repair where an inspector
does the inspection. Create a single server model in ARENA with the following data:
Interarrival time
Service time
Run length
Base time units
Radio: Exp (6) min.
Uniform (5,8) min
5 days of 8 hour shift
Minutes
Part B: Create another type of entities TVs, with the interarrival times exponentially
distributed with mean 30 minutes.
Part C: For Animation enhancement select different pictures for different entities.
Part D: Modify the model now by inserting a DECIDE module between the process
module and the dispatch module. Select the option 2-way by chance and give 80% in
the percentage true option, which means that 80% of the entities pass the inspection
and the rest fail.
Part E: Modify the model now by changing the option in the DECIDE module.
Select the option 2-way by condition and select entity type in the if option and radios
in the named option. This means that entities radios pass the condition and all radios
go in one direction and the others, TVs go in another direction.
Assignment: Add another type of entities named tape recorders to the model
developed in Part E whose interarrival times are exponentially distributed with a mean
of 45 minutes. Modify the decide module to separate all the three types of entities.
Obtain the SIMAN report and extract the following results:
1.
2.
3.
4.
5.
Average number of entities in the queue
Average total time in the system for radios, tvs and tape recorders
Average waiting time for all the entities
Total number of radios, tvs and tape recorders out of the system and
Average utilization of the inspector.
Note: The report should be a MS-WORD file which shows the flow chart, SIMAN
report and the above results extracted from the report.
Systems Engineering Department
SE 405 (062)
Lab # 4
ANIMATION, PLOTS AND NEW MODULES.
Objective: Enhancing the inspection model build in the previous lab and introduce
the Resource Picture Placement and plot options from the animate tool bar.
Things to do:
Part A: Assume that parts arrive at an inspection center for repair where an inspector
does the inspection. Create a single server model in ARENA with the following data:
Interarrival time
Service time
Run length
Base time units
Radio: Exp (8) min.
Normal (5,1) min
5 days of 8 hour shift
Minutes




Using the resource picture placement add picture to the Inspector and give
different images for Idle and Busy option.
Using Plot button create a dynamic plot for Work in Process.
Using Plot button create a dynamic plot for Inspector Utilization.
Using Text and Graphic buttons give the Title for the Model Build.
Part B: Introducing ASSIGN and RECORD modules. Consider a Electronic
Assembly/Testing System as shown in the figure. The figure also gives the relevant
data.
Develop and ARENA model and run for four 8 hour shifts to obtain the following
results:
1. Utilization of all the Resources.
2. Average total time in the system for Scrapped, Shipped and Salvaged parts.
3. Average waiting time and average number in queue for all the queues.
Note: Two students can work as a group. The complete model should be developed
and the results should be shown in the computer to the lab instructor. The lab
instructor will check the model for all the groups and give appropriate grade for their
work.
Systems Engineering Department
SE 405 (062)
Lab # 5
SCHEDULES, RESOURCE STATES AND FAILURES.
Objective: Enhancing the Electronic Assembly/Testing System build in the previous
lab and introduce the Schedules, Resource States, and Resource Failures.
Things to do:
Part A: Complete the Electronic Assembly/Testing System.
Part B: Original model is shown to production manager. He pointed out that this is
only the first shift of a two-shift day and should be run for 10 days. He suggested the
following things based on the results from the previous results:

On second shift there are two operators at Rework (the bottleneck station)

The Sealer fails sometimes
o Uptimes ~ exponential, mean 2 hours
o Repair times ~ exponential, mean 4 minutes
Modify the existing model with the information above and then compare the results of
part A and part B.
Systems Engineering Department
SE 405 (062)
Lab # 6
QUEUE RANKING, BALKING AND VARIABLE DISPLAYS
AND HISTOGRAMS.
Objective: Introducing the concepts of Queue ranking, Balking, variable displays and
generating histograms.
Things to do:
Model: Build a single server model for a banking system where the customers arrive
at a bank for teller services. The model should calculate the average time spent by the
customer in the bank. The details are given below.
Interarrival time
Service time
Run length
Base time units
Radio: Exp (10) min.
Normal (15,2)
250 Customers
Minutes
Part A: Change the default ranking of the queues from FIFO to LIFO, Lowest
Attribute Value and Highest Attribute Value options and compare the results for time
in the system.
From the Simon Report write the value for time in system for all the rankings given
Ranking
FIFO
LIFO
LAV
HAV
Time in System
Part B: The customer enters the queue only if a customer finds the teller queue length
to be less than 10, else he leaves the system. This is called balking. Add a DECIDE
module and give this condition selecting the 2-way-by-condition option. Obtain the
average time between balking using RECORD module.
From the Simon Report write the value for time in system and time between balking.
Statistic
Time in System
Time Between Balking
Result
Part C: Using VARIABLE option from animation bar, place variables to display the
number of customers leaving the system with service and without service. Place a
variable that shows the current number of customers in the teller queue.
Part D: Using HISTOGRAM option from animation bar, place histograms for time in
the system for the customers served and time between balking for the customers
leaving the system without service.
Systems Engineering Department
SE 405 (062)
Lab # 7
BATCHING, COSTING & INPUT ANALYZER
Part A: Assume that there are four units in a manufacturing plant i.e., A, B, C and D.
In Plant A steel plates are cut into shape that are used as raw material to plant C where
these plates are shaped to be shipped to the unit D for painting. Plant B also processes
plastic part batches to be sent to Plant C for further processing. Plant B joins plastic
part (4 plastic parts together) to be shipped to plant D for painting. Use following data
to model:
Base time units: Minutes
Run Length: 5 days of 8 hour shift
Unit
Interarrival time
Service time
A: Steel
Steel Sheets: Exp (20)
Cutting
min.
B: Plastic
Plastic= Exp (20) min.
Normal (15,8) min/sheet
Normal (50,10) min/batch
assembly
C: Steel
Normal (30,10) min/sheet
Shaping
D: Paint work
Steel: Triangular (20,40,60) min/sheet
Plastic: Triangular (30, 50,65) min/sheet
Part B: Analyze the cost incurred using following data
Costs: busy or idle (/hr)
Cost busy/idle (/hr)
Plastic cutter
$10
$10 / 8
Steel cutter
$12
$12 / 8
Shaper
$15
$15 / 8
Painter
$5
$5 / 3
Steel sheets
Holding cost=$1/hr
Plastic Parts
Holding cost=$.5/hr
Part C: Analyze the following 3 sets of Data and fit distribution (give atleast 2 dist.)
DATA SET
Distribution
Parameter
A
Sq Error:
P-value:
Sq Error:
P-value:
B
Sq Error:
P-value:
Sq Error:
P-value:
C
Sq Error:
P-value:
Sq Error:
P-value:
Systems Engineering Department
SE 405 (062)
Lab # 8
BLOCK MODULES, VAT & NVA & ROUTING OF ENTITIES
Part A: Consider the case of two machines running at Expo (2) and Expo (3)
processing times. One operator is need for parts loading and unloading for the two
machines. It takes 0.5 minutes for the operator to load and unload parts. Parts arrive to
the system according to Expo (8) the rout sheet for the parts is machine#1 then
machine#2. Design a simulation model for the system described.
1.
2.
3.
4.
What is the average utilization of the different resources in the system?
What is the average value of the cycle time of the parts in the system?
On average, what is the value of the parts’ value adding time (VAT)?
On average, what is the value of the parts’ non-value adding time (NVA)?
Part B: Again, construct the same model described in Part A using “Block” modules.
Part C: Consider a flow line layout manufacturing shop, where manufactured parts
pass through three consecutive machines namely: Drill, Tapping machine and
Painting machine. Processing times of the parts on the mentioned machines are shown
in the following table:
Resource
Drill
Tapping machine
Painting machine
Processing time
Triangular (2,4,5)
Normal (3,1)
Uniform (4,6)
Also, it takes 3 minutes to transfer the parts between the three different machines and
5 minutes transfer time between the painting machine location and the exit point of
the system. Construct a simulation model for the system.
1.
2.
3.
4.
Animate the routing of the parts in the system
What is the average cycle time of the parts in the system?
On average, what is the value of the parts’ value adding time (VAT)?
On average, what is the value of the parts’ non-value adding time (NVA)?
Assignment (Next Lab): Enhance Part B to include routing of parts between
machine 1 and machine 2 assuming the transfer time of parts between the two
machines distributed uniformly between (1, 1.5) minutes.
Hint: use Enter and leave modules for each process (Process 1 and 2)
Systems Engineering Department
SE 405 (062)
Lab # 9
JOB SHOP PROBLEM
Part A: The systems to be modeled, consists of parts arrivals, four manufacturing
cells and part departures. Cells 1, 2, 3 and 4 each have a single machine. The system
produces three part types, each visiting a different sequence of stations. The part steps
and process times (in minutes) are given in table below. All process times are
triangularly distributed.
Part Type
1
2
3
Cell/Time
1
6, 8, 10
1
11, 13, 15
2
7, 9, 11
Cell/Time
2
5, 8, 10
2
4, 6, 8
1
7, 10, 13
Cell/Time
3
15, 20, 25
4
15, 18, 21
3
18, 23, 28
Cell/Time
4
8, 12, 16
2
6, 9, 12
Cell/Time
3
27, 33, 39
The inter-arrival times between successive part arrivals (all types combined) are
exponentially distributed with a mean of 13 minutes. The distribution by the type is
26%, part 1; 48%, part 2; 26%, part 3. Parts enter near cell 1 and leave near cell 4.
We want to collect statistics on resource utilization, time and number in queue. The
simulation time is 24 hrs a day 5 days a week.