Transcript SE405_All_Labs.ppt

Lab2
• Objectives: Introduction to awesim environment
(Network and control parts, Running models,
Opening/saving models), introduction to simple modeling
structures (arrivals, queuing, service, termination), and
probabilistic branching, getting time in the system
(attributes and collect block).
• “Simple machining center” model
M2
Parts arrive
Queue1
M1
Queue2
M3
stage 1
stage 2
Parts departs
Lab2
• “Simple machining center” model
Processing time
uniform (6, 10) min
Identical parallel machines
M2
Parts arrive
Queue1
Inter arrival
times
exponential
with lambda=0.2 part/min
M1
Queue2
Processing time
uniform (2.5, 5.5) min
M3
What are the machine utilization?
What are the queue lengths and times?
Simulate it for 30 days (8 hours working time per day)
Parts departs
Lab2
• Embellishment 1: Add an inspection station at
the end, and assume that 5% of the jobs fail
inspection and they require rework starting from
beginning. Ins. time Normal (10,2)
• Embellishment 2: After inspection, 2 % requires
rework in stage 2 only (not from beginning) in
addition to the 5% in embellishment 1.
• Embellishment 3: Obtain time in the system for
parts.
Lab2
• Assignment 2: Model the following system
and answer the same questions answered
in the lab.
normal(10,2)
M1
Parts arrive
Queue2
Queue1
Inter arrival
times
exponential
with mean=15 min.
Inspection
M2
Processing time (identical machines)
normal (mean=22.5, std=5.7) min
3% rework
Submit a print out of model, control, output, and your answers.
Lab 3
• Objectives; To cover; Entity dependent
processing times, routing (conditional
branching), and naming of attributes to
make the model easier to read.
Lab 3 Simple machining center with
inspection
• Embellishment 1; There are two types of
parts coming to system, type A and type B,
as depicted in next slide. Type A has to go
thorough a different machine in the second
stage. We want to get time in the system
separately by item type, and overall as
well. Use renaming of the attributes for
arrival time.
Lab 3 Simple machining center with
inspection (Embellishment 1)
Gamma(1,2) min
Type A
Queue3
M4
Normal(10,2) min
Type A
M2
Type B
Queue1
Type B
M1
Queue2
uniform (2.5, 5.5) min
Parts arrive
Inter arrival times exponential ;
with lambda=0.005 part/min Type A
with lambda=0.015 part/min Type B
Queue4 Insp.
M3
uniform (4, 6) min
(identical machines)
5% rework
Lab3
In-lab work-out
Normal (8,2)
Queues are not depicted here
Type B
Ins1
Gamma(2,2)
Type A 40%
5% rework
M1
M2
Type B 50%
Normal (6,1)
uniform(5.5, 7.5)
Inter arrival times;
gamma(2,5)
Run simulation for 5000 parts
Where is the bottleneck?
Ins2
Type A
3% rework
Lab 4
• 1. Entity dependent processing times and
entity dependent numbering of collect
block. 2. Balking blocking 3.Different uses
of collect block and histogram.
Lab 4 Simple machining center with
inspection
• Embellishment 1; Inspection time depends on
job type. For type A inspection time is Normal
(8,2) for type B inspection time is Normal (15,3).
Use one collect block to get time in the system
separately by numbering the collect block using
attribute.
• Embellishment 2; Assume that if there are more
than 5 parts waiting in queue 1, the arriving
parts will be sent to another shop for processing.
Obtain how often this happens. We would like to
obtain histogram of time in the system as well.
Lab4
In-lab work-out;
Maintenance shop
• Maintenance facility of a large manufacturer
performs two operations in series . The units that
are maintained are heavy, and the space in the
shop is available only for 8 units including the
units being worked on. The proposed design
allocates 4 units for first queue, 2 units for
second queue. Company subcontracts incoming
units if the maintenance shop is full. If the
second queue is full, the first workstation is
blocked.
Lab4
In-lab work-out;
Maintenance shop
• Arrivals; exponential with mean 0.4 time units
• Processing times; first station exponential with
mean 0.25, second station exponential with mean
0.5
• No significant time for transfer from first station to
next.
• Evaluate proposed design for 300 time units in
terms of
– utilizations, time in the system, time between the
subcontracting, queue lengths, fraction of time work
station 1 is blocked (The correct answers avr. tims =
2.7, time btw balk = 1.5)
– Any better design???
LAB 5
• Objective: 1. To complete the in-lab
workout started in previous lab and the
embellishment of it. 2. To learn how to do
batch arrivals, use of NQ(), multiple runs,
the ranking in queues, flexible use of
attributes.
LAB 5
In-lab workout
• Complete the model for the problem described
in previous lab.
• Embellishment: Assume that there are two types
of units that comes to the system, and second
stage operation time depends on type of unit as
follows; Type A Gamma(0.5,0.6) and Type B
Gamma(1, 0.8). Use one collect block to get
time in the system separately by type. Produce a
histogram of time in the system for both types.
LAB 5
TV inspection station
• Consider the following TV inspection & adjustment station where we
have two inspectors and one adjuster. TV sets arrive in sets of two
TVs with uniform btw 7 and 15.
TVs
Queue1
Ins1
85% to packing
85% to packing
Queue2
Ins2
Queue3 Adj.
Return of adjusted sets
Incoming TVs join the shorter queue. The processing time in inspection stations
are uniform(6, 12). Adjustment takes shifted gamma(2, 2) with min 1.5.
Obtain time in the system based on 1000 parts leaving the system. Do 50 runs.
LAB 5
TV inspection station
• Embellishment: Assume that in all queues,
we use shortest process time first rule.
After adjustment, make sure the TVs go
back to the same inspector queue that
they came from.
LAB 5 – Assignment 3
TV inspection station
• Embellishment of TV inspection model: There
are two types of TV sets. 40% type A and 60%
type B. Adjustment time depends on the type of
TV set as follows; Type A gamma(2, 2) with min
1.5 and Type B gamma(1.8, 2.5) with min 1. Also
assume that if a TV is adjusted before, it passes
the inspection 95% of the time. Change ranking
rule to longest processing time first. Do your
simulation for 40 runs, obtain time in the system
by type.