Introduction
The system I modeled was the production process for a hydro-mechanical aircraft engine fuel controller, at Hamilton
Sundstrand (HS). Specifically, the assembly and test aspect. A basic overview of the system is as follows:
Customers submit orders to HS for fuel controls, along with a delivery request. An automated inventory system looks at
the current “free” inventory, and through purchasing orders any additional parts needed. Using known average leadtimes for control parts, the system places orders so that the parts will arrive with just enough time to assemble the
control, hence minimizing inventory expenses. In the case of the control I focused on, about 2 weeks prior to requested
delivery date, the order is placed in queue, where a service technician assembles a “kit” of all the parts necessary to
build the control. After the kit is assembled, it awaits the availability of a builder .
There are nine major assembly operations, and a tenth to put the cover on once the internal mechanisms have been
assembled. Once the control is successfully assembled, it is briefly inspected, and having passed inspection gets
transported to another building to await testing. There are three major components of testing, including setup,
performance testing, and calibration. If the control passes the test, it’s transported to Final Process, where it’s cleaned,
soaked in preserving fluid, and prepared for shipment to the customer. Final Inspection reviews the control right before
it leaves for the customer.
Using a bar-code scanner type device, workers are timed and measured by how fast they can perform an operation
(assembly, test, or final process). In fact, the performance of organization is in part based on their ability to perform
operations close to a standard. Anything additional is unwanted “variation.”
A major area of concern, and particularly frustrating to assembly workers, is part shortages. According to production
workers, when they get in a rhythm, that last thing they want is to have to stop in the middle of what they are doing,
because the next part they need in the assembly is a few days late. Typically what occurs, is that operations are
performed (to the extent possible) out of sequence, or more commonly, an operation is partially completed, then another
one is started while the operator waits for the part(s) from the prior operation to arrive. There are hundreds of parts that
make up a control, and when you have fluctuating demand for parts during any given month, coupled with a system that
schedules “just in time” and suppliers who can’t meet tight lead times, variability and part delays are inevitable. For the
control I investigated, 27/68 - 40% were started without complete kits.
Problem Formulation
Between production workers and management, it is believed that part shortages are a key driver towards increased
assembly time, increased probability of failure at test, increased variability, and low ability to deliver controls on-time.
However, as the controls are complex (several hundred parts) and the inventory system is used company-wide,
management is cautious about making any changes. That is unless the benefits of reducing the number of part shortages
can be demonstrated quantitatively. Which is where simulation comes in.
My problem was to quantitatively demonstrate, through statistics and simulation, the benefits on organizational
performance that building controls with all their parts. I planned to do this by simulating the building of complete kits
vs. partial kits, and observing the effects on the system measures of performance. The measures of performance (MOP)
for this system were:



Total assembly and test time (includes final process)
% of controls delivered on time
1st time yield (i.e. passing testing the first time)
Secondary (but relevant) MOP were:
 Inventory level
 Total cost of manufacturing the control
Project Objectives
Flowing from the problem statement, my specific objectives were to:




Establish a statistically significant correlation between part shortages and assembly time, test time, final process
time, probability of test failure.
Quantify the reduction in assembly and test time if all parts were available.
Quantify the probability of meeting on time-delivery, if all parts were available (i.e. reduced variance)
Quantify the reduction in production time assuming no controls are rejected at test (100% yield)
The ultimate purpose of the simulation would be to answer the question: “What impact to our organization would result
if all controls were started with complete kits?”
Model Conceptualization & Data Collection
The sample: Most data came from a year’s worth of data for the particular control under investigation. Fortunately, HS
keeps detailed records for each control, on an operation-by-operation basis. Unfortunately, the data was severely
fragmented, had to be sorted and assembled (no easy task!). For example: one report might have the number of hours of
rework, while another the distribution of test times. Trying to match several reports together to create a coherent picture
was formidable.
My key interests in the data were to find time distributions for assembly, test, and final process times, % of controls
passing the first test, etc. and to try and statistically correlate that with kit-parts missing. My initial intent was, through
hypothesis testing, determine if there was a statistically significant difference in MOPs of controls that had been started
with missing parts, vs. controls that started complete. My goal was to seek a correlation between the MOPs and 1)
whether or not the assembly was started with parts missing, 2) number of parts missing, 3) class of part missing (e.g. a
high precision valve vs. a bolt), and 4) the number of parts missing of each class. Unfortunately, as I quickly
discovered, HS did not maintain any data for any substantial length on parts initially missing from kits!
I eventually settled upon number one - looking for correlation’s based on controls started with complete or incomplete
kits. Since this information was not overtly present in the data, I had to infer it. Controls were labeled as “not complete
kits” if the sequence of operations of out of order, and there was a change in date. For ex., a control with operations 10,
20, 30, 50 on one day, and 40, 50,… completed in the future was labeled as being incomplete. I also labeled as
incomplete kits when there was an abnormally large gap between operations, a week for example.
Other problems I encountered with the data were that operators, for various reasons, didn’t always punch in and out
when they were supposed to. Sometimes the 1st operation had an unusually large time associated with it, while the next
several operations had zero. Sometimes the operator missed the punch all together, and there was no data for an
operation. The cover assembly (the last operation before testing) is one that frequently had no time associated to it.
My initial motivation for looking at the data on an operation-by-operation basis was to generate probability distribution
functions (PDFs) for each operator, and try to correlate their performance to the MOPs. Unfortunately, the
inconsistency of the data, and the fact more than one operator works on a control led me to abandon this idea. I settled
for breaking up the operations by assembly, test, and final process.
After censoring incomplete control records, I generated 68 controls to from my sample - 41 were controls with out any
indication of being assembled without a full complement of parts, and 27 were controls highly suspect of being built
with partial kits. From this sample, the following information was extracted:







Assembly time for each control, without the cover
Cover assembly time
Assembly + Cover (total assembly)
Test time (total)
% of Test failures (controls failing one or more times)
Rework hours per control
Number of days waiting for parts (for those controls that were started incomplete)
For each of each above, the following were performed to validate the input data I would be using in my simulation:
1.
2.
3.
Runs-charts - to verify that the data was stable, and that there were no trends
Histogram - to get a better idea of the possible family of PDFs that might represent the data
Probability Plot - to test the fit of the data with a particular PDF family, to estimate PDF parameters
And for those data which appeared to be satisfactorily represented by a normal distribution, the following were also
performed:
1.
2.
Hypothesis test for equality of variance
Hypothesis test for equality of population means
See appendix for all plots and hypothesis testing
As a result of the hypothesis testing, the only thing that can be said with confidence is that there is a statistical difference
between the total assembly (main assembly and cover) for kits that were started complete vs. incomplete. There was
found to be no statistical difference in variance, as a result of kits started complete / incomplete. While the total Test
Time, and Test Failure rate was slightly higher for the controls started with incomplete kits, the difference is within a
95% confidence interval. Therefore, I cannot be 95% confident that there is a difference.
Note: I was not entirely comfortable with my choice of the exponential distribution to represent the data from “Part
delay” or “Rework time,” it was the best out of several (e.g. normal, lognormal, etc.)
Model Conceptualization
Perhaps the best way to illustrate my model concept, is to list the assumptions I made (which were derived in part from
production personnel input).
From both a objectives standpoint, the most important aspects of the model were the 1) assembly, 2) test, and 3) final
process section. They were also the most important from a validation perspective, because these are the areas which are
most heavily measured.
Assembly
As a builder starts the control, the kit is either complete or it’s missing. He builds as far as he can with the pieces
available. Typically this means skipping part or all of an operation until the parts become available. It may also mean
taking something apart, to get access to the area that was skipped over.
Assumptions (A) and Justifications (J)
Ordering
A1: Orders arrive probabilistically, modeled by an exponential distribution
J1: Historical data obtained supports the hypothesis that order data could have been generated from an exponential
distribution.
Assembly
A1: Only one builder assembles the control at a time
J1: Standard practice on the actual production floor. A second worker (e.g. on second shift) may take over building
from the previous worker’s shift, however.
A2: Workers are not available to work on additional controls until the control they started is complete, i.e. they don’t
start a new control while waiting for parts.
J2: In actuality, there is enough resource capacity and enough other minor tasks so that only starting additional controls
is unnecessary. The small order rate relative to production time is also a factor.
A3: Workers are available whenever there is work.
J3: Of the three major tasks production workers are responsible for – customer return material, engineering
development, and production, production has the highest priority to the extent that workers are immediately available to
work on production issues.
A4: The assembly distributions are equal for each worker
J4: The resolution of the historical data is not sufficient to distinguish between individual performance. The DF for
assembly times is a composite of all workers involved with assembly, and hence is a good approximation to individual
DFs.
A5: Controls that fail testing do not consume parts from inventory
J5a: Based on worker input, most rework is on manufactured parts, such as valves.
J5b: The historical data is not sufficient to develop any model on the usage of extra parts during rework.
A6: Controls that fail testing and require assembly rework are given highest priority (of controls waiting assy queue).
J6: Standard policy
A7: The total assembly time is modeled by a normal DF.
J7: The data supports the hypothesis that a normal distribution is sufficient to have generated the historical data.
Testing
A1: Controls fail only once
J1A: The data is not sufficient to generate rework DFs on a per failed-test basis.
J1B: Rework is lumped on one test failure – this is produces total rework times in good agreement with historical data.
A2: The test distributions are equal for each worker
J2: See A4, Assembly
A3: Rework testing is lumped with normal testing, when a failure occurs. The control then proceeds to assembly for
rework, and returns back to testing to finish rework:
Testing  Failure  Rework Testing  Rework Assembly  Resume Normal Testing
J3A: The historical data is not sufficient to model multiple test-failure / reject situations.
J3B: The lumped assembly / test rework model is a good approximation to the total historical rework time, per control.
A4: Test time DF is not statistically different for controls started with complete vs. incomplete kits
J4: The data can be represented by a normal DF; hypothesis testing cannot reject Ho (see appendix also).
A5: The probability of a test failure is independent of whether the control assembly was started with a complete kit.
J5: See J4 above
Final Process
A1: FP time DF is not statistically different for controls started with complete vs. incomplete kits
J1: See J4, Testing
Inventory/Parts
A1: Missing parts can be lumped together and represent any / all missing parts.
J1: Controls are comprised of hundreds of parts, the data is not sufficient to predict which parts will be missing and at
what percentage of time
J2: Lumped parts model whether a control was started with a complete / incomplete assembly, and is sufficient to satisfy
this project’s objectives.
Misc.
A1: There is a negligible machine downtime
J1: The production cycle time for a control, as well as the frequency of orders, along with infrequent machine problems
make machine down time negligible.
A2: Kit assembly time, Inspection time, and Final Process can be modeled by a normal DF.
J2: Historical data and hypothesis tests support the above statements.
Other assumptions include travel times between locations, and DFs for Inspection, Kit Assembly, etc. These
assumptions are not key to achieving project objectives. Where ever possible, data has been used to substantiate the
assumptions.
Decision / Input Variables
The following decision / input variables are of interest to this project’s objectives. All variables may be adjusted
through the “Model Parameters / Run-time Interface,” under Simulation. Special note: When changing parameters
through the Model Parameters section, the simulation must be run from this menu!
D1: Schedule offset
This is the total amount of time available to produce a control, up until the customer request date. It is the time / date
work begins on the control. If the offset is too small, it’s likely that the customer request date will be missed. If the
offset is too large, the control sits around until it’s ready to ship, impacting inventory costs. The optimum setting is to
produce controls as close to the customer request target as possible.
D2: Inventory level
The amount of spare capacity kit parts is measured by the inventory level. Because in actuality supplier parts are often
delayed beyond their expected shipment date, an inventory with excess controls will be able to absorb periods where
parts are delayed, hence minimizing assembly wait time. However, extra parts is accompanied by extra cost (holding
cost).
D3: Part Delay Probability
This is the probability that a part needed for assembly will not be available when needed. This is a decision variable,
because management can decide when to order spare parts. Parts ordered sooner than needed or earlier than the current
“just in time” (which isn’t working) would also decrease the probability that a part would not be available when needed.
Two other variables, though not under direct control are:
Failure Rate: The probability of a control failing at test. For each control that’s just been assembled, is a probability
associated with it failing testing. This variable is included for the purposes of quantitatively illustrating the benefits of
producing higher quality (i.e. fewer test failures) controls.
Order Rate: This variable is not under direct control (although sales may influence the number) and is included to
create various scenarios, to see how the system behaves under different order contions.
VERIFICATION
Verification was achieved primarily through the following means



Observing that values for key metrics were within expected range
Observing the model animation
Tracing of model logic
Output Values with Expected Range
The following array values (i.e. performance metrics) are generated each time the model is run. They are stored in the
Output section, and the name of the file is OUTPUT.XLS. The columns represent output variables (various times),
while the rows represent unique controls going through the control.
Variable Name (Column)
Variable Description
T1
T2
T3
T4
T5
T6
T7
T8
T9
T10
T11
T12
T13
T14
T15
T16
T17
T18
Order in Time (abs.)
Customer Request Time (abs.)
Scheduled Control Build Time (abs.)
Scheduled Part Delay (rel.)
Kit Assembly Time (rel.)
Assembly Time, w/o Rework (rel.)
Inspection Time (rel.)
Test Time, w/o Rework (rel.)
Test Output Queue Time (rel.)
Final Process (FP) Time (rel.)
Rework Assembly Time (rel.)
Rework Test Time (rel.)
Deviation from Customer Request Target (rel.)
Total Production Time (Kit FP) (rel.)
Part Delay, Actual (rel.)
Time After Final Process (abs.)
Input to Kit Assembly Time (abs.)
Time out of System (abs.)
Each of the above variables, for a wide variety of initial conditions was verified against an expected range of values.
The expected range values were derived from the model component CDFs. Ex. For a test time normally distributed,
N(10,1), I know that 99.7% of the values will lie between +/- 3 standard deviations, or (7,13). If I receive many values
outside of this range, I know a problem exists with the system. As the complexity of the system grows and the number
of component interactions increases, the above table proved extremely useful for debugging each section of the model.
This also turned out to be an excellent validation tool, comparing the variable results to historical values.
Note: The times for the above 18 variables are either in absolute (abs.) simulation time, or relative (rel.) simulation time.
Observing Model Animation
This was useful to determine visually if the model flow was behaving as I had intended. For almost all components,
there exists a DISPLAY command, which displays the control (and it’s identifying #) when the control reaches a
particular station. Ex. //Display "Assy Q " $ HMU Assy Q is the location name, and HMU is the number of the
control passing through that logic, at that moment.
The display lines have currently been commented out, but can easily be uncommented out, to facilitate visual tracking.
Model Tracing
The last primary means I used to verify my model, was to use the step trace function, and trace through the model step
by step. I was able to detect individual lines of code operating incorrectly through this function, and correct them.
VALIDATION
The development of my model consisted of modeling the most crucial elements (most strongly related to the objectives)
first, comparing the output results with historical data (validation), and then adding more detail and complexity,
gradually incorporating more “reality” in the model. Each step along the way, I performed hypothesis tests on the key
output measures against historical measures. Most were statistically equivalent. In my final model, I heavily relied on
the above table of 18 performance metrics, whose values were tested for statistical equivalence to historical values. It
should be noted that the historical parameters were obtained from data using the statistical methods outlined in the
INPUT section of this report, and they, therefore are estimates themselves.
Lastly, throughout the development of my model, I also consulted with the operators and technicians closest to the
process, to ensure that my interpretation of reality was valid or reasonable.
Note: See also appendix for sample calculations and test cases, 1-4.
Test Cases – Input Parameter Schedule
Mean Order Time
80
80
80
80
Schedule Offset
7
7
21
7
Initial Inv. Level
5
5
0
0
Failure Probability
Delay Probability
0
1
.25
.25
0
1
.65
.65
Experimental Design & Production Runs
The objectives of this simulation project, and results were:
OBJ1: Establish a statistically significant correlation between part shortages and assembly time, test time, final process
time, probability of test failure.
Result: As detailed in the appendix, the results of comprehensive input data analysis and hypothesis testing showed a
correlation to kits complete / not complete only for Total Assembly Time. This was incorporated in the model.
OBJ2: Quantify the reduction in assembly and test time if all parts were available.
Result:
Case
Parts Available
Parts Missing
Mean (hrs)
68.34
113.2
Standard Deviation (hrs)
3.45
14.4
P-Value
.0000
For a .95 confidence hypothesis test the two means are equal, Ho is overwhelmingly rejected. Therefore, the model
predicts a substantial difference in assembly time between controls with complete / incomplete kits!
OBJ3: Quantify the probability of meeting on time-delivery, if all parts were available (i.e. reduced variance)
Result: For the sample with parts available without delay, on average the controls are ready 74 hours before the
customer requests them. For the sample with controls initially missing parts, controls are on average 26 hours over due
from the time the customer wants them (this is in good agreement with actual data). A number other is zero is
undesirable – overdue cause poor customer relations, under-due causes excessive inventory costs. While the data is not
normal and a hypothesis test cannot be performed, the data clearly shows that controls consistently are produced ahead
of schedule when parts are available, and consistently behind schedule when they are not readily available.
OBJ4: Quantify the reduction in production time assuming no controls are rejected at test (100% yield)
Result: See OBJ2
The next and final stage of validation and experimental design to change the current system, and observe how well the
model predicts the results.
APPENDIX
INPUT DATA HYPOTHESIS TEST SUMMARY
Assumed DF
Mean
Mean (MP*)
P-value
CF
Reject Ho
Assy
Normal
14.272
16.441
0.0034
(-3.42, -.57)
Yes
Cover
Normal
2.084
1.897
0.85
(-.26, .85)
No
Assy+Cover
Normal
16.158
17.833
0.012
(-3.12, -.23)
Yes
Test
Normal
12.76
12.79
0.930
(-.70, .64)
No
FP
Normal
2.558
2.441
0.67
(-.41, .64)
No
SD
SD (MP*)
CF
Reject Ho
2.900
3.120
(.71, 1.447)
No
1.184
0.999
(.701,1.47)
No
2.889
3.003
1.42
1.24
0.815
1.157
No
No
Assumed DF
Mean
Mean (MP*)
Rework Hrs/unit
Exponential
12.36
13.92
Part Delays
Exponential
N/A
25.7142857
*Note: Ho: 1 = 2
Ha: 1  2
Sample Minitab Input Data Analysis
Run Chart for Assy Time (Ops 10-90)
20
C1
15
10
2
12
22
32
42
Observation
Number of runs about median:
Expected number of runs:
Longest run about median:
Approx P-Value for Clustering:
Approx P-Value for Mixtures:
18.0000
22.0000
5.0000
0.1057
0.8943
Number of runs up or down:
Expected number of runs:
Longest run up or down:
Approx P-Value for Trends:
Approx P-Value for Oscillation:
24.0000
27.6667
5.0000
0.0851
0.9149
Test Failures
0.51
0.56
0.363
(-.285, .199)
No
Probability Plot for Normality, Assy Time (Ops 10-90)
99
ML Estimates
95
Mean:
14.4473
StDev:
2.66945
90
70
60
50
40
30
20
10
5
1
10
15
20
Data
Run Chart for Assy Time (Ops 10-90) - Missing Parts
26
21
C7
Percent
80
16
11
5
15
25
Observation
Number of runs about median:
Expected number of runs:
Longest run about median:
Approx P-Value for Clustering:
Approx P-Value for Mixtures:
20.0000
14.4815
3.0000
0.9850
0.0150
Number of runs up or down:
Expected number of runs:
Longest run up or down:
Approx P-Value for Trends:
Approx P-Value for Oscillation:
19.0000
17.6667
3.0000
0.7357
0.2643
CASE1 Report
General Report
Output from C:\ProMod4\models\Mike_MSA_Project10.MOD [MSA_Project_2]
Date: Dec/21/1999
Time: 05:56:13 AM
-------------------------------------------------------------------------------Scenario
: Model Parameters
Replication
: 1 of 1
Simulation Time : 8760 hr
-------------------------------------------------------------------------------LOCATIONS
Location
Scheduled
Current
Name
Hours
Contents % Util
--------- ---------- -----Order Q
8760
2
0.00
Kit Assy
8760
0
4.78
Assy Q
8760
0
0.00
Inventory
8760
5
0.00
AB1
8760
0
6.95
AB2
8760
0
5.29
AB3
8760
0
6.90
Insp
8760
0
0.00
TQ In
8760
0
0.00
TRig1
8760
0
7.30
TRig2
8760
1
8.17
TQ Out
8760
0
0.00
FP
8760
0
1.48
Output Q
8760
0
0.00
Total
Average
Hours
Average
Maximum
Capacity
Entries
Per Entry
Contents
Contents
--------
-------
----------
---------
--------
999999
106
196.349132
2.37591
8
1
104
4.026721
0.0478058
1
999999
104
2.097740
0.0249047
1
999999
109
413.515514
5.14534
8
1
38
16.029763
0.0695355
1
1
28
16.539571
0.0528662
1
1
38
15.906816
0.0690022
1
999999
104
1.214096
0.0144139
2
999999
104
2.094596
0.0248674
2
1
48
13.327688
0.0730284
1
1
56
12.785786
0.0817356
1
999999
103
1.207825
0.0142016
1
2
103
2.516660
0.0295909
2
999999
103
78.805311
0.926592
4
LOCATION STATES BY PERCENTAGE (Multiple Capacity)
Location
Name
--------Order Q
Assy Q
Inventory
Scheduled
Hours
--------8760
8760
8760
%
Empty
----7.51
97.51
0.00
%
Partially
Occupied
--------92.49
2.49
100.00
%
Full
---0.00
0.00
0.00
|
|
|
|
|
|
|
%
Down
---0.00
0.00
0.00
------
Insp
TQ In
TQ Out
FP
Output Q
8760
8760
8760
8760
8760
98.56
97.52
98.58
97.05
37.41
1.44
2.48
1.42
2.94
62.59
0.00
0.00
0.00
0.01
0.00
|
|
|
|
|
0.00
0.00
0.00
0.00
0.00
LOCATION STATES BY PERCENTAGE (Single Capacity/Tanks)
Location
Name
-------Kit Assy
AB1
AB2
AB3
TRig1
TRig2
Scheduled
Hours
--------8760
8760
8760
8760
8760
8760
%
Operation
--------4.78
5.85
4.44
5.80
6.89
7.76
%
Setup
----0.00
0.00
0.00
0.00
0.00
0.00
%
Idle
----95.22
93.05
94.71
93.10
92.70
91.83
%
Waiting
------0.00
1.10
0.85
1.10
0.41
0.41
%
Blocked
------0.00
0.00
0.00
0.00
0.00
0.00
%
Down
---0.00
0.00
0.00
0.00
0.00
0.00
RESOURCES
Resource
Name
Util
-----------Op1
8.66
Op2
6.52
Op3
8.60
TOp1
10.42
TOp2
11.82
Average
Hours
Per
Usage
Average
Hours
Travel
To Use
Average
Hours
Travel
To Park
% Blocked
In Travel
%
-
Units
Scheduled
Hours
Number
Of Times
Used
-----
---------
--------
--------
--------
--------
---------
1
8577.5
114
5.830096
0.684211
0.065371
0.00
1
8577.5
84
5.962595
0.690476
0.048128
0.00
1
8577.5
114
5.789114
0.684211
0.065371
0.00
1
8577.5
144
5.524160
0.680556
0.082312
0.00
1
8577.5
167
5.401222
0.670659
0.095652
0.00
RESOURCE STATES BY PERCENTAGE
Resource
Name
-------Op1
Op2
Op3
TOp1
TOp2
Scheduled
Hours
--------8577.5
8577.5
8577.5
8577.5
8577.5
%
In Use
-----7.75
5.84
7.69
9.27
10.52
%
Travel
To Use
-----0.91
0.68
0.91
1.14
1.31
FAILED ARRIVALS
Entity
Name
------------Kit Parts
Control Order
Location
Name
--------Inventory
Order Q
Total
Failed
-----0
0
%
Travel
To Park
------0.86
0.63
0.86
1.10
1.28
%
Idle
----88.35
90.73
88.41
86.36
84.77
%
Down
---2.13
2.13
2.13
2.13
2.13
ENTITY ACTIVITY
Average
Average
Average
Average
Current
Hours
Hours
Hours
Hours
Total
Exits
Quantity
In System
In
System
In Move
Logic
Wait For
Res, etc.
In
Operation
-----
---------
----------
---------
---------
----------
103
1
347.143184
35.254728
2.167476
309.554874
0
0
-
-
-
-
104
5
417.020750
2.000000
0.000000
0.000000
0
2
-
-
-
-
Average
Hours
Entity
Name
Blocked
----------------------JFC160 1
0.166107
Kit Parts Base
Kit Parts
415.020750
Control Order
-
ENTITY STATES BY PERCENTAGE
Entity
Name
-------------JFC160 1
Kit Parts Base
Kit Parts
Control Order
%
In Move
Logic
------10.16
0.48
-
%
Wait For
Res, etc.
--------0.62
0.00
-
%
In Operation
-----------89.17
0.00
-
%
Blocked
------0.05
99.52
-
VARIABLES
Variable
Name
----------------RW cnt
Move Time
Part Delay1
Part Delay2
Part Delay3
AssyTime1
AssyTime2
AssyTime3
RW Hrs
HMU cnt
Order Mean
Schedule Offset
Inventory Initial
Failure Prob
Delay Prob
--Case 2 Report
Total
Changes
------1
1
38
28
38
38
28
38
0
107
1
1
1
1
1
Average
Hours
Per Change
---------0.000000
0.000000
229.480263
306.986321
224.176316
229.891184
307.467857
224.591158
0.000000
81.552075
0.000000
0.000000
0.000000
0.000000
0.000000
Minimum
Value
------0
0
0
0
0
0
0
0
0
0
80
7
0
0
0
Maximum
Value
------0
2
2
2
2
17.6955
20.6455
19.737
0
106
80
14
5
0.25
0.6
Current
Value
------0
2
2
2
2
15.6147
13.4831
15.764
0
106
80
7
5
0
0
Average
Value
------0
2
1.9358
1.80319
1.96852
12.9628
12.5581
13.1483
0
57.9424
80
7
5
0
0
-------------------------------------------------------------------------------General Report
Output from C:\ProMod4\models\Mike_MSA_Project10.MOD [MSA_Project_2]
Date: Dec/21/1999
Time: 05:59:00 AM
-------------------------------------------------------------------------------Scenario
: Model Parameters
Replication
: 1 of 1
Simulation Time : 8760 hr
-------------------------------------------------------------------------------LOCATIONS
Location
Scheduled
Current
Name
Hours
Contents % Util
--------- ---------- -----Order Q
8760
3
0.00
Kit Assy
8760
0
4.38
Assy Q
8760
0
0.00
Inventory
8760
5
0.00
AB1
8760
0
17.00
AB2
8760
0
6.06
AB3
8760
0
5.99
Insp
8760
0
0.00
TQ In
8760
0
0.00
TRig1
8760
0
7.72
TRig2
8760
0
9.38
TQ Out
8760
0
0.00
FP
8760
0
1.35
Output Q
8760
0
0.00
Total
Average
Hours
Average
Maximum
Capacity
Entries
Per Entry
Contents
Contents
--------
-------
----------
---------
--------
999999
98
251.155918
2.80974
10
1
95
4.034453
0.0437526
1
999999
95
2.113821
0.0229239
1
999999
100
449.920250
5.13608
8
1
124
12.009516
0.169998
1
1
32
16.584844
0.0605839
1
1
33
15.913697
0.0599489
1
999999
189
1.217471
0.0262674
2
999999
189
2.225704
0.0480203
2
1
84
8.045702
0.0771506
1
1
104
7.903308
0.0938292
1
999999
188
3.396569
0.0728944
3
2
94
2.514755
0.0269848
2
999999
94
14.921085
0.160112
3
LOCATION STATES BY PERCENTAGE (Multiple Capacity)
Location
Name
--------Order Q
Assy Q
Inventory
Insp
TQ In
Scheduled
Hours
--------8760
8760
8760
8760
8760
%
Empty
----7.86
97.71
0.00
97.40
95.38
%
Partially
Occupied
--------92.14
2.29
100.00
2.60
4.62
%
Full
---0.00
0.00
0.00
0.00
0.00
|
|
|
|
|
|
|
|
|
%
Down
---0.00
0.00
0.00
0.00
0.00
------
TQ Out
FP
Output Q
8760
8760
8760
93.21
97.30
84.97
6.79
2.69
15.03
0.00 | 0.00
0.00 | 0.00
0.00 | 0.00
LOCATION STATES BY PERCENTAGE (Single Capacity/Tanks)
Location
Name
-------Kit Assy
AB1
AB2
AB3
TRig1
TRig2
Scheduled
Hours
--------8760
8760
8760
8760
8760
8760
%
Operation
--------4.38
15.66
5.09
5.05
7.18
8.83
%
Setup
----0.00
0.00
0.00
0.00
0.00
0.00
%
Idle
----95.62
83.00
93.94
94.01
92.28
90.62
%
Waiting
------0.00
1.34
0.97
0.94
0.54
0.55
%
Blocked
------0.00
0.00
0.00
0.00
0.00
0.00
%
Down
---0.00
0.00
0.00
0.00
0.00
0.00
RESOURCES
Resource
Name
Util
-----------Op1
20.31
Op2
7.46
Op3
7.49
TOp1
13.28
TOp2
16.42
Average
Hours
Per
Usage
Average
Hours
Travel
To Use
Average
Hours
Travel
To Park
% Blocked
In Travel
%
-
Units
Scheduled
Hours
Number
Of Times
Used
-----
---------
--------
--------
--------
--------
---------
1
8577.5
278
6.043932
0.223022
0.201970
0.00
1
8577.5
96
5.976198
0.687500
0.055062
0.00
1
8577.5
99
5.800990
0.686869
0.056788
0.00
1
8577.5
292
3.304243
0.595890
0.137755
0.00
1
8577.5
367
3.244450
0.594005
0.167364
0.00
RESOURCE STATES BY PERCENTAGE
Resource
Name
-------Op1
Op2
Op3
TOp1
TOp2
Scheduled
Hours
--------8577.5
8577.5
8577.5
8577.5
8577.5
%
In Use
-----19.59
6.69
6.70
11.25
13.88
%
Travel
To Use
-----0.72
0.77
0.79
2.03
2.54
FAILED ARRIVALS
Entity
Name
------------Kit Parts
Control Order
Location
Name
--------Inventory
Order Q
Total
Failed
-----0
0
%
Travel
To Park
------2.87
0.72
0.75
1.89
2.33
%
Idle
----74.69
89.69
89.64
82.71
79.12
%
Down
---2.13
2.13
2.13
2.13
2.13
ENTITY ACTIVITY
Average
Average
Average
Average
Current
Hours
Hours
Hours
Hours
Total
Exits
Quantity
In System
In
System
In Move
Logic
Wait For
Res, etc.
In
Operation
-----
---------
----------
---------
---------
----------
94
1
386.759574
59.996468
2.492777
319.418309
0
0
-
-
-
-
95
5
465.027621
2.000000
0.000000
0.000000
0
3
-
-
-
-
Average
Hours
Entity
Name
Blocked
----------------------JFC160 1
4.852021
Kit Parts Base
Kit Parts
463.027621
Control Order
-
ENTITY STATES BY PERCENTAGE
Entity
Name
-------------JFC160 1
Kit Parts Base
Kit Parts
Control Order
%
In Move
Logic
------15.51
0.43
-
%
Wait For
Res, etc.
--------0.64
0.00
-
%
In Operation
-----------82.59
0.00
-
%
Blocked
------1.25
99.57
-
VARIABLES
Variable
Name
----------------RW cnt
Move Time
Part Delay1
Part Delay2
Part Delay3
AssyTime1
AssyTime2
AssyTime3
RW Hrs
HMU cnt
Order Mean
Schedule Offset
Inventory Initial
Failure Prob
Delay Prob
Case 3 Report
Total
Changes
------95
1
30
32
33
30
32
33
188
99
1
1
1
1
1
Average
Hours
Per Change
---------91.751032
0.000000
288.804633
265.384531
264.654848
289.247733
265.826062
264.989606
46.502069
88.362192
0.000000
0.000000
0.000000
0.000000
0.000000
Minimum
Value
------0
0
0
0
0
0
0
0
0
0
80
7
0
0.25
0.6
Maximum
Value
------94
2
2
2
2
19.4907
20.6455
19.737
1651.71
98
80
14
5
1
1
Current
Value
------94
2
2
2
2
13.2932
14.129
11.0475
1651.71
98
80
7
5
1
1
Average
Value
------53.5136
2
1.92089
1.94361
1.74392
14.1368
12.9824
11.1285
936.625
57.16
80
7
5
1
1
-------------------------------------------------------------------------------General Report
Output from C:\ProMod4\models\Mike_MSA_Project10.MOD [MSA_Project_2]
Date: Dec/21/1999
Time: 06:02:45 AM
-------------------------------------------------------------------------------Scenario
: Model Parameters
Replication
: 1 of 1
Simulation Time : 8760 hr
-------------------------------------------------------------------------------LOCATIONS
Location
Scheduled
Current
Name
Hours
Contents % Util
--------- ---------- -----Order Q
8760
3
0.00
Kit Assy
8760
0
5.48
Assy Q
8760
0
0.00
Inventory
8760
7
0.00
AB1
8760
0
10.60
AB2
8760
0
6.22
AB3
8760
0
8.76
Insp
8760
0
0.00
TQ In
8760
0
0.00
TRig1
8760
0
10.15
TRig2
8760
0
8.92
TQ Out
8760
0
0.00
FP
8760
0
1.70
Output Q
8760
1
0.00
Total
Average
Hours
Average
Maximum
Capacity
Entries
Per Entry
Contents
Contents
--------
-------
----------
---------
--------
999999
123
225.452301
3.1656
9
1
119
4.033353
0.054791
1
999999
118
2.206339
0.0297201
1
999999
125
362.538976
5.17322
9
1
68
13.655985
0.106005
1
1
33
16.501909
0.0621647
1
1
47
16.318596
0.0875541
1
999999
148
1.215007
0.0205275
2
999999
148
2.521770
0.0426053
2
1
77
11.548779
0.101513
1
1
71
11.007310
0.0892145
1
999999
148
1.545311
0.026108
2
2
118
2.521966
0.0339717
2
999999
118
44.959305
0.605616
5
LOCATION STATES BY PERCENTAGE (Multiple Capacity)
Location
Name
--------Order Q
Assy Q
Inventory
Insp
TQ In
TQ Out
FP
Output Q
Scheduled
Hours
--------8760
8760
8760
8760
8760
8760
8760
8760
%
Empty
----5.94
97.03
0.00
97.95
95.77
97.42
96.65
54.95
%
Partially
Occupied
--------94.06
2.97
100.00
2.05
4.23
2.58
3.30
45.05
%
Full
---0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
|
|
|
|
|
|
|
|
|
|
|
|
%
Down
---0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
------
LOCATION STATES BY PERCENTAGE (Single Capacity/Tanks)
Location
Name
-------Kit Assy
AB1
AB2
AB3
TRig1
TRig2
Scheduled
Hours
--------8760
8760
8760
8760
8760
8760
%
Operation
--------5.48
9.35
5.27
7.32
9.63
8.39
%
Setup
----0.00
0.00
0.00
0.00
0.00
0.00
%
Idle
----94.52
89.40
93.78
91.24
89.85
91.08
%
Waiting
------0.00
1.25
0.95
1.44
0.52
0.53
%
Blocked
------0.00
0.00
0.00
0.00
0.00
0.00
%
Down
---0.00
0.00
0.00
0.00
0.00
0.00
RESOURCES
Resource
Name
Util
-----------Op1
12.95
Op2
7.69
Op3
10.81
TOp1
15.39
TOp2
13.61
Average
Hours
Per
Usage
Average
Hours
Travel
To Use
Average
Hours
Travel
To Park
% Blocked
In Travel
%
-
Units
Scheduled
Hours
Number
Of Times
Used
-----
---------
--------
--------
--------
--------
---------
1
8577.5
174
5.924753
0.459770
0.113695
0.00
1
8577.5
99
5.998111
0.666667
0.058511
0.00
1
8577.5
141
5.883674
0.695035
0.078947
0.00
1
8577.5
244
4.720311
0.688525
0.120172
0.00
1
8577.5
230
4.431604
0.643478
0.116939
0.00
RESOURCE STATES BY PERCENTAGE
Resource
Name
-------Op1
Op2
Op3
TOp1
TOp2
Scheduled
Hours
--------8577.5
8577.5
8577.5
8577.5
8577.5
%
In Use
-----12.02
6.92
9.67
13.43
11.88
%
Travel
To Use
-----0.93
0.77
1.14
1.96
1.73
FAILED ARRIVALS
Entity
Name
------------Kit Parts
Control Order
ENTITY ACTIVITY
Location
Name
--------Inventory
Order Q
Total
Failed
-----0
0
%
Travel
To Park
------1.54
0.77
1.05
1.63
1.59
%
Idle
----83.38
89.41
86.01
80.85
82.68
%
Down
---2.13
2.13
2.13
2.13
2.13
Average
Average
Average
Average
Current
Hours
Hours
Hours
Hours
Total
Exits
Quantity
In System
In
System
In Move
Logic
Wait For
Res, etc.
In
Operation
-----
---------
----------
---------
---------
----------
117
1
359.327812
41.840872
2.276291
313.861274
0
1
-
-
-
-
118
7
377.106585
2.000000
0.000000
0.000000
0
4
-
-
-
-
Average
Hours
Entity
Name
Blocked
----------------------JFC160 1
1.349376
Kit Parts Base
Kit Parts
375.106585
Control Order
-
ENTITY STATES BY PERCENTAGE
Entity
Name
-------------JFC160 1
Kit Parts Base
Kit Parts
Control Order
%
In Move
Logic
------11.64
0.53
-
%
Wait For
Res, etc.
--------0.63
0.00
-
%
In Operation
-----------87.35
0.00
-
%
Blocked
------0.38
99.47
-
VARIABLES
Variable
Name
----------------RW cnt
Move Time
Part Delay1
Part Delay2
Part Delay3
AssyTime1
AssyTime2
AssyTime3
RW Hrs
HMU cnt
Order Mean
Schedule Offset
Inventory Initial
Failure Prob
Delay Prob
Case 4 – Report
Total
Changes
------31
1
38
33
47
38
33
47
60
124
1
1
1
1
1
Average
Hours
Per Change
---------262.888419
0.000000
228.398816
253.263606
181.682723
228.911737
253.751424
182.122468
136.293633
70.641419
0.000000
0.000000
0.000000
0.000000
0.000000
Minimum
Value
------0
0
0
0
0
0
0
0
0
0
80
7
0
0.25
0.6
Maximum
Value
------30
2
2
2
2
19.4907
20.6455
20.6684
495.103
123
80
14
5
0.25
0.6
Current
Value
------30
2
2
2
2
19.4907
16.0977
20.6684
495.103
123
80
7
5
0.25
0.6
Average
Value
------14.92
2
1.94231
1.94361
1.92086
13.6995
13.7407
12.4394
233.847
62.1273
80
7
5
0.25
0.6
-------------------------------------------------------------------------------General Report
Output from C:\ProMod4\models\Mike_MSA_Project10.MOD [MSA_Project_2]
Date: Dec/21/1999
Time: 06:05:50 AM
--------------------------------------------------------------------------------
Scenario
: Model Parameters
Replication
: 1 of 1
Simulation Time : 8760 hr
-------------------------------------------------------------------------------LOCATIONS
Location
Scheduled
Current
Name
Hours
Contents % Util
--------- ---------- -----Order Q
8760
3
0.00
Kit Assy
8760
0
5.48
Assy Q
8760
0
0.00
Inventory
8760
2
0.00
AB1
8760
0
10.60
AB2
8760
0
6.22
AB3
8760
0
8.76
Insp
8760
0
0.00
TQ In
8760
0
0.00
TRig1
8760
0
10.15
TRig2
8760
0
8.92
TQ Out
8760
0
0.00
FP
8760
0
1.70
Output Q
8760
1
0.00
Total
Average
Hours
Average
Maximum
Capacity
Entries
Per Entry
Contents
Contents
--------
-------
----------
---------
--------
999999
123
225.452301
3.1656
9
1
119
4.033353
0.054791
1
999999
118
2.206339
0.0297201
1
999999
120
12.644767
0.173216
4
1
68
13.655985
0.106005
1
1
33
16.501909
0.0621647
1
1
47
16.318596
0.0875541
1
999999
148
1.215007
0.0205275
2
999999
148
2.521770
0.0426053
2
1
77
11.548779
0.101513
1
1
71
11.007310
0.0892145
1
999999
148
1.545311
0.026108
2
2
118
2.521966
0.0339717
2
999999
118
44.959305
0.605616
5
LOCATION STATES BY PERCENTAGE (Multiple Capacity)
Location
Name
--------Order Q
Assy Q
Inventory
Insp
TQ In
TQ Out
FP
Output Q
Scheduled
Hours
--------8760
8760
8760
8760
8760
8760
8760
8760
%
Empty
----5.94
97.03
84.64
97.95
95.77
97.42
96.65
54.95
%
Partially
Occupied
--------94.06
2.97
15.36
2.05
4.23
2.58
3.30
45.05
%
Full
---0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
|
|
|
|
|
|
|
|
|
|
|
|
%
Down
---0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
------
LOCATION STATES BY PERCENTAGE (Single Capacity/Tanks)
Location
Name
-------Kit Assy
AB1
AB2
AB3
TRig1
TRig2
Scheduled
Hours
--------8760
8760
8760
8760
8760
8760
%
Operation
--------5.48
9.35
5.27
7.32
9.63
8.39
%
Setup
----0.00
0.00
0.00
0.00
0.00
0.00
%
Idle
----94.52
89.40
93.78
91.24
89.85
91.08
%
Waiting
------0.00
1.25
0.95
1.44
0.52
0.53
%
Blocked
------0.00
0.00
0.00
0.00
0.00
0.00
%
Down
---0.00
0.00
0.00
0.00
0.00
0.00
RESOURCES
Resource
Name
Util
-----------Op1
12.95
Op2
7.69
Op3
10.81
TOp1
15.39
TOp2
13.61
Average
Hours
Per
Usage
Average
Hours
Travel
To Use
Average
Hours
Travel
To Park
% Blocked
In Travel
%
-
Units
Scheduled
Hours
Number
Of Times
Used
-----
---------
--------
--------
--------
--------
---------
1
8577.5
174
5.924753
0.459770
0.113695
0.00
1
8577.5
99
5.998111
0.666667
0.058511
0.00
1
8577.5
141
5.883674
0.695035
0.078947
0.00
1
8577.5
244
4.720311
0.688525
0.120172
0.00
1
8577.5
230
4.431604
0.643478
0.116939
0.00
RESOURCE STATES BY PERCENTAGE
Resource
Name
-------Op1
Op2
Op3
TOp1
TOp2
Scheduled
Hours
--------8577.5
8577.5
8577.5
8577.5
8577.5
%
In Use
-----12.02
6.92
9.67
13.43
11.88
%
Travel
To Use
-----0.93
0.77
1.14
1.96
1.73
%
Travel
To Park
------1.54
0.77
1.05
1.63
1.59
%
Idle
----83.38
89.41
86.01
80.85
82.68
%
Down
---2.13
2.13
2.13
2.13
2.13
FAILED ARRIVALS
Entity
Name
------------Kit Parts
Control Order
Location
Name
--------Inventory
Order Q
Total
Failed
-----0
0
ENTITY ACTIVITY
Average
Average
Average
Average
Average
Hours
Entity
Name
Blocked
---------------------JFC160 1
1.349376
Kit Parts Base
Kit Parts
12.790881
Control Order
-
Current
Hours
Hours
Hours
Hours
Total
Exits
Quantity
In System
In
System
In Move
Logic
Wait For
Res, etc.
In
Operation
-----
---------
----------
---------
---------
----------
117
1
359.327812
41.840872
2.276291
313.861274
0
1
-
-
-
-
118
2
14.790881
2.000000
0.000000
0.000000
0
4
-
-
-
-
ENTITY STATES BY PERCENTAGE
Entity
Name
-------------JFC160 1
Kit Parts Base
Kit Parts
Control Order
%
In Move
Logic
------11.64
13.52
-
%
Wait For
Res, etc.
--------0.63
0.00
-
%
In Operation
-----------87.35
0.00
-
%
Blocked
------0.38
86.48
-
VARIABLES
Variable
Name
----------------RW cnt
Move Time
Part Delay1
Part Delay2
Part Delay3
AssyTime1
AssyTime2
AssyTime3
RW Hrs
HMU cnt
Order Mean
Schedule Offset
Inventory Initial
Failure Prob
Delay Prob
Program Text File
Total
Changes
------31
1
38
33
47
38
33
47
60
124
1
1
1
1
1
Average
Hours
Per Change
---------262.888419
0.000000
228.398816
253.263606
181.682723
228.911737
253.751424
182.122468
136.293633
70.641419
0.000000
0.000000
0.000000
0.000000
0.000000
Minimum
Value
------0
0
0
0
0
0
0
0
0
0
80
7
0
0.25
0.6
Maximum
Value
------30
2
2
2
2
19.4907
20.6455
20.6684
495.103
123
80
14
0
0.25
0.6
Current
Value
------30
2
2
2
2
19.4907
16.0977
20.6684
495.103
123
80
7
0
0.25
0.6
Average
Value
------14.92
2
1.94231
1.94361
1.92086
13.6995
13.7407
12.4394
233.847
62.1273
80
7
0
0.25
0.6
********************************************************************************
*
*
*
Formatted Listing of Model:
*
*
A:\Mike_MSA_Project10.MOD
*
*
*
********************************************************************************
Time Units:
Distance Units:
Initialization Logic:
Hours
Feet
RW_cnt = 0
Move_Time = 2
HMU_cnt = 0
Order_Mean = Order_Mac
Schedule_Offset = Schedule_Mac
Inventory_Initial = Inven_Mac
Failure_Prob = Failure_Mac
Delay_Prob = Delay_Mac
********************************************************************************
*
Locations
*
********************************************************************************
Name
---------Order_Q
Kit_Assy
Assy_Q
Inventory
AB1
AB2
AB3
Insp
TQ_In
TRig1
TRig2
TQ_Out
FP
Output_Q
Cap
-------INFINITE
1
INFINITE
INFINITE
1
1
1
Infinite
INFINITE
1
1
INFINITE
2
INFINITE
Units
----1
1
1
1
1
1
1
1
1
1
1
1
1
1
Stats
----------Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Rules
Cost
---------- -----------Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
Oldest, ,
********************************************************************************
*
Entities
*
********************************************************************************
Name
-------------JFC160_1
Kit_Parts_Base
Kit_Parts
Control_Order
Speed (fpm)
-----------150
150
150
150
Stats
Cost
----------- -----------Time Series
Time Series
Time Series
Time Series
********************************************************************************
*
Path Networks
*
********************************************************************************
Name
Type
T/S
From
Factor
-------- ----------- ---------------- -------------Net1
Passing
Time
N1
N2
Net2
Passing
Time
N1
To
BI
Dist/Time
Speed
-------- ---- ----------- ----N2
N3
N2
Bi
Bi
Bi
Move_Time
Move_Time
Move_Time
Net3
Passing
Time
Net4
Net5
Passing
Passing
Time
Time
Net6
Passing
Time
Net7
Net8
Net9
Net10
Passing
Passing
Passing
Passing
Time
Time
Time
Time
N2
N1
N2
N1
N1
N2
N1
N2
N1
N1
N1
N1
N3
N2
N3
N2
N2
N3
N2
N3
N2
N2
N2
N2
Bi
Bi
Bi
Bi
Bi
Bi
Bi
Bi
Bi
Bi
Bi
Bi
Move_Time
Move_Time
Move_Time
4*Move_Time
Move_Time
Move_Time
Move_Time
Move_Time
4*Move_Time
4*Move_Time
4*Move_Time
4*Move_Time
********************************************************************************
*
Interfaces
*
********************************************************************************
Net
Node
---------- ---------Net1
N1
N2
N3
Net2
N1
N2
N3
Net3
N1
N2
N3
Net4
N1
N2
Net5
N1
N2
N3
Net6
N1
N2
N3
Net7
N1
N2
Net8
N1
N2
Net9
N2
N1
Net10
N2
N1
Location
---------Assy_Q
AB1
Insp
Assy_Q
AB2
Insp
Assy_Q
AB3
Insp
Insp
TQ_In
TQ_In
TRig1
TQ_Out
TQ_In
TRig2
TQ_Out
TQ_Out
FP
TQ_Out
AB1
AB2
TQ_Out
AB3
TQ_Out
********************************************************************************
*
Resources
*
********************************************************************************
Res
Ent
Name
Units Stats
Search
Search Path
Motion
Cost
-------- ----- -------- ---------- ------ ---------- -------------- ----------Op1
1
By Unit
Closest
Oldest Net1
Home: N2
(Return)
Empty: 150 fpm
Full: 150 fpm
Op2
1
By Unit
Closest
Oldest Net2
Home: N2
Empty: 150 fpm
Full: 150 fpm
(Return)
Op3
1
By Unit
Least Used Oldest Net3
Home: N2
(Return)
Empty: 150 fpm
Full: 150 fpm
TOp1
1
By Unit
Closest
Oldest Net5
Home: N2
(Return)
Empty: 150 fpm
Full: 150 fpm
TOp2
1
By Unit
Closest
Oldest Net6
Home: N2
(Return)
Empty: 150 fpm
Full: 150 fpm
********************************************************************************
*
Clock downtimes for Resources
*
********************************************************************************
Res
Frequency
Logic
-------- --------------------Op1
24 hr
Wait .5
24 hr
Wait .25
24 hr
Wait .25
Op2
24 hr
Wait .5
24 hr
Wait .25
24 hr
Wait .25
Op3
24 hr
Wait .5
24 hr
Wait .25
24 hr
Wait .25
TOp1
24 hr
Wait .5
24 hr
Wait .25
24 hr
Wait .25
TOp2
24 hr
Wait .5
24 hr
Wait .25
24 hr
Wait .25
First Time Priority
Scheduled Node
List
Disable
---------- ---------- --------- -------- -------- ------4 hr
99
Yes
All
No
2 hr
99
No
All
No
6
99
No
All
No
4
99
Yes
No
2
99
No
No
6
99
No
No
4
99
Yes
No
2
99
No
No
6
99
No
No
4
99
Yes
No
2
99
No
No
6
99
No
No
4
99
Yes
No
2
99
No
No
6
99
No
No
********************************************************************************
*
Processing
*
********************************************************************************
Process
Routing
Entity
Location Operation
Rule
Move Logic
-------------- --------- -------------------------------- -----------Control_Order Order_Q
//HMU Order #
HMU = HMU_cnt
//Display $HMU
Blk
Output
Destination
---- -------------- ----------- -
//"Order-in Time"
//Absolute Time
PT[HMU,1]=clock()
//Customer Request Time, units in hrs
//Absolute Time
PT[HMU,2] = U(336,336,1) + PT[HMU,1]
//Schedule to Assembly (2 weeks prior to delivery)
PT[HMU,3] = PT[HMU,2] - Schedule_Offset*24
//Relative Time
Wait PT[HMU,3] - Clock()
FIRST 1
Control_Order
//Order Kit Parts w/ Probabilistic Delay
IF Rand(1)< Delay_Prob then
Begin
// Display "Hi"
PT[HMU,4] = E(65.45,2)
//Relative Time
Wait PT[HMU,4]
ORDER 1 Kit_Parts TO Inventory
End
ELSE
Begin
ORDER 1 Kit_Parts TO Inventory
//Display "High"
End
1
Control_Order Kit_Assy
Move for Move_Time
Kit_Assy //Display "Kit Assy " $HMU
//Schedule Time (Time that total production time
begins)
PT[HMU,17]=clock()
PT[HMU,5]=clock()
Wait N(4,.25,3)
//Kit Assy Time
PT[HMU,5]=clock()-PT[HMU,5]
1
Kit_Parts_Base Assy_Q
FIRST 1
Move for Move_Time
Kit_Parts_Base Assy_Q
//Display "Assy Q " $ HMU
RANDOM 1
RANDOM
/*IF Contents(Assy_Q) >= 2 then
Order 1 Kit_Parts TO Inventory
ELSE
Wait 0*/
1
Kit_Parts_Base AB1
Move with Op1 then free
Kit_Parts_Base AB2
Move with Op2 then free
Kit_Parts_Base AB3
RANDOM
Kit_Parts
JOIN 1
JOIN
Move with Op3 then free
Inventory //Display $[HMU,
Move for Move_Time
1
Kit_Parts
AB1
Kit_Parts
AB2
Kit_Parts
AB3
Move for Move_Time
JOIN
Move for Move_Time
Kit_Parts_Base AB1
//Display "AB1" $ HMU
Real
Real
Real
Real
Real
T_Start=0
T_End=0
X1 = 0
X2 = 0
RW = 0
PT[HMU,6]=Clock()
T_Start = Clock()
//Display "Request Inventory - AB1"
Join 1 Kit_Parts
T_End = Clock()
Part_Delay1 = T_End - T_Start
PT[HMU,15]=T_End - T_Start
X1=N(16.158,2.889,4)
X2=N(17.833,3.003,4)
IF Part_Delay1 < X1 Then
Begin
Use Op1 for (X1 - Part_Delay1)
AssyTime1 = (X1 - Part_Delay1)
End
ELSE
BEGIN
IF Part_Delay1 < X2 Then
Begin
Use Op1 for (X2 - Part_Delay1)
AssyTime1 = (X2 - Part_Delay1)
End
ELSE
AssyTime1 = X2
END
//Calculate Assy Time (no rework)
PT[HMU,6]=Clock()-PT[HMU,6]
1
JFC160_1
FIRST 1
Move with Op1 then free
Kit_Parts_Base AB2
//Display "AB2 " $ HMU
Real
Real
Real
Real
Real
T_Start=0
T_End=0
X1 = 0
X2 = 0
RW = 0
PT[HMU,6]=Clock()
T_Start = Clock()
//Display "Request Inventory - AB2"
Join 1 Kit_Parts
T_End = Clock()
Insp
Part_Delay2 = T_End - T_Start
PT[HMU,15]=T_End - T_Start
X1=N(16.158,2.889,5)
X2=N(17.833,3.003,5)
IF Part_Delay2 < X1 Then
Begin
Use Op2 for (X1 - Part_Delay2)
AssyTime2 = (X1 - Part_Delay2)
End
ELSE
BEGIN
IF Part_Delay2 < X2 Then
Begin
Use Op2 for (X2 - Part_Delay2)
AssyTime1 = (X2 - Part_Delay2)
End
ELSE
AssyTime2 = X2
END
//Calculate Assy Time (no rework)
PT[HMU,6]=Clock()-PT[HMU,6]
1
JFC160_1
FIRST 1
Move with Op2 then free
Kit_Parts_Base AB3
//Display "AB3 " $ HMU
Real
Real
Real
Real
Real
Insp
T_Start=0
T_End=0
X1 = 0
X2 = 0
RW = 0
PT[HMU,6]=Clock()
T_Start = Clock()
//Display "Request Inventory - AB3"
Join 1 Kit_Parts
T_End = Clock()
Part_Delay3 = T_End - T_Start
PT[HMU,15]=T_End - T_Start
X1=N(16.158,2.889,6)
X2=N(17.833,3.003,6)
IF Part_Delay3 < X1 Then
Begin
Use Op3 for (X1 - Part_Delay3)
AssyTime3 = (X1 - Part_Delay3)
End
ELSE
BEGIN
IF Part_Delay3 < X2 Then
Begin
Use Op3 for (X2 - Part_Delay3)
AssyTime3 = (X2 - Part_Delay3)
End
ELSE
AssyTime3 = X2
END
FIRST 1
JFC160_1
//Calculate Assy Time (no rework)
PT[HMU,6]=Clock()-PT[HMU,6]
1
JFC160_1
Move with Op3 then free
Insp
//Display "Insp " $ HMU
Insp
PT[HMU,7]=clock()
Wait N(1.25,.25,7)
FIRST 1
JFC160_1
RANDOM 1
RANDOM
JFC160_1
FIRST 1
JFC160_1
//Calc. Inspect. Time
PT[HMU,7]=clock()-PT[HMU,7]
1
JFC160_1
Move on Net4
TQ_In
//Display "TQ_in" $ HMU
1
JFC160_1
Move with TOp1 then free
JFC160_1
Move with TOp2 then free
TRig1
Real RW = 0
Real Temp1=0
Real Temp2=0
TQ_In
TRig1
TRig2
IF F_Test = 1 THEN
BEGIN
//Display "T-rig 1 " $ HMU
PT[HMU,8]=clock()
Use TOp1 for N(1.5,.25,8)
PT[HMU,8]=clock()-PT[HMU,8]
PT[HMU,12]=clock()
Use TOp1 for E(7.09,8)
PT[HMU,12]=clock()-PT[HMU,12]
Rework = 1
END
ELSE
BEGIN
IF Rework = 1 THEN
Begin
//Display "T-rig 1, rework " $ HMU
Temp1=clock()
RW = N(7.5,1,8)
Use TOp1 for RW
Temp2=clock()-Temp1
PT[HMU,8]=PT[HMU,8]+Temp2
//PT[HMU,19]=Temp2
RW_Hrs = RW_Hrs + RW
End
ELSE
Begin
//Display "T-rig 1 " $ HMU
PT[HMU,8]=clock()
Use TOp1 for N(12.5,1.5,8)
PT[HMU,8]=clock()-PT[HMU,8]
End
END
1
JFC160_1
TQ_Out
Move with TOp1 then free
TRig2
Real RW = 0
Real Temp1=0
Real Temp2=0
FIRST 1
JFC160_1
IF F_Test = 1 THEN
BEGIN
//Display "T-rig2 " $ HMU
PT[HMU,8]=clock()
Use TOp2 for N(1.5,.25,9)
PT[HMU,8]=clock()-PT[HMU,8]
PT[HMU,12]=clock()
Use TOp2 for E(7.09,9)
PT[HMU,12]=clock()-PT[HMU,12]
Rework = 1
END
ELSE
BEGIN
IF Rework = 1 THEN
Begin
//Display "T-rig2 Rework " $ HMU
Temp1=clock()
RW = N(7.5,1,9)
Use TOp2 for RW
Temp2=clock()-Temp1
PT[HMU,8]=PT[HMU,8]+Temp2
//PT[HMU,19]=Temp2
RW_Hrs = RW_Hrs + RW
End
ELSE
Begin
//Display "T-rig 2 " $ HMU
PT[HMU,8]=clock()
Use TOp2 for N(12.5,1.5,9)
PT[HMU,8]=clock()-PT[HMU,8]
End
END
1
JFC160_1
TQ_Out
Move with TOp2 then free
TQ_Out
//Display "TQ_out " $ HMU
IF F_Test = 0, 1
Move on
IF F_Test = 1
Move on
IF F_Test = 1
Move on
IF F_Test = 1
JFC160_1
Move on
FP
FIRST 1
Move for Move_Time
Real temp1=0
Real temp2=0
temp1 = clock()
Wait N(1.25,.25,10)
temp2 = clock()
PT[HMU,9]= PT[HMU,9]+(temp2-temp1)
1
JFC160_1
Net7
JFC160_1
Net8
JFC160_1
Net9
JFC160_1
Net10
//Display "FP " $HMU
PT[HMU,10]=clock()
Wait N(2.558,.815,11)
PT[HMU,10]=clock()-PT[HMU,10]
PT[HMU,16]=clock()
1
JFC160_1
PT[HMU,14]=PT[HMU,16]-PT[HMU,17]
FP
AB1
AB2
AB3
Output_Q
JFC160_1
Output_Q
//Display "Output Q " $ HMU
PT[HMU,13]=PT[HMU,2]-clock()
IF PT[HMU,13]>0 THEN
Begin
//Stay in Queue until cust. request time
Wait PT[HMU,13]
End
ELSE
Wait 0
1
FIRST 1
JFC160_1
EXIT
//Time out of system
PT[HMU,18]=Clock()
JFC160_1
AB1
//Display "Rework AB1 " $ HMU
Real RW = 0
RW = E(9.27,4)
PT[HMU,11]=clock()
Use Op1 for RW
//Calc. rework assy time
PT[HMU,11]=clock()-PT[HMU,11]
//Rest
F_Test
RW_cnt
RW_Hrs
FIRST 1
JFC160_1
Failed test flag, incr cntrs
= 0
= RW_cnt + 1
= RW_Hrs + RW
1
JFC160_1
Move with Op1 then free
AB2
//Display "Rework AB2 " $ HMU
Insp
Real RW = 0
RW = E(9.27,5)
PT[HMU,11]=clock()
Use Op2 for RW
//Calc. rework assy time
PT[HMU,11]=clock()-PT[HMU,11]
F_Test = 0
RW_cnt = RW_cnt + 1
RW_Hrs = RW_Hrs + RW
FIRST 1
JFC160_1
1
JFC160_1
Move with Op2 then free
AB3
//Display "Rework AB3 " $ HMU
Real RW = 0
RW = E(9.27,6)
Insp
PT[HMU,11]=clock()
Use Op3 for RW
//Calc. rework assy time
PT[HMU,11]=clock()-PT[HMU,11]
F_Test = 0
RW_cnt = RW_cnt + 1
RW_Hrs = RW_Hrs + RW
1
FIRST 1
JFC160_1
Insp
Move with Op3 then free
********************************************************************************
*
Arrivals
*
********************************************************************************
Entity
Location Qty each
First Time Occurrences Frequency
Logic
------------- --------- ----------------- ---------- ----------- -----------------------Control_Order Order_Q
1
0
INFINITE
E(Order_Mean)
//Attributes
F_Test = 0
Rework = 0
//HMU counter
INC HMU_cnt
/*If rand(1) <= -1 then
P_Short = 1
Else
P_Short = 0
*/
If rand(1) < Failure_Prob then
F_Test = 1
Else
F_Test = 0
//Order/Control #
Kit_Parts
Inventory Inventory_Initial 0
1
1
********************************************************************************
*
Attributes
*
********************************************************************************
ID
---------P_Short
Rework
F_Test
HMU
Type
-----------Integer
Integer
Integer
Integer
Classification
-------------Entity
Entity
Entity
Entity
********************************************************************************
*
Variables (global)
*
********************************************************************************
ID
Type
Initial value Stats
----------------- ------------ ------------- ----------#
#Counts # of controls getting rework
RW_cnt
Integer
0
#
#Time to traverse a path
Move_Time
Real
0
#
#Delay between order and complete kit, Op1
Part_Delay1
Real
0
#
#Delay between order and rest of kit, Op2
Part_Delay2
Real
0
#
#Delay between order and rest of kit
Part_Delay3
Real
0
#
#Running assy time for Op1 (records max)
AssyTime1
Real
0
#
#"Running" assy time for Op2
AssyTime2
Real
0
#
#"Running" assy time for Op3
AssyTime3
Real
0
#
#Total cumulative rework hours
RW_Hrs
Real
0
HMU_cnt
Integer
0
Order_Mean
Real
80
Schedule_Offset
Real
14
Inventory_Initial Integer
0
Failure_Prob
Real
.25
Delay_Prob
Real
.60
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time Series
Time
Time
Time
Time
Time
Time
Time
Series
Series
Series
Series
Series
Series
Series
********************************************************************************
*
Arrays
*
********************************************************************************
ID
Dimensions
Type
---------- ------------ -----------PT
150,18
Real
********************************************************************************
*
Macros
*
********************************************************************************
ID
----------------Order_Mac
Schedule_Mac
Inven_Mac
Failure_Mac
Delay_Mac
Text
-----------Order_Mean
Schedule_Offset
Inventory_Initial
Failure_Prob
Delay_Prob
********************************************************************************
*
Streams
*
********************************************************************************
Stream #
-----------1
2
3
4
5
6
7
8
Seed #
-----------1
2
3
4
5
6
7
8
Reset
-----------No
No
No
No
No
No
No
No