@SIMUL8 Virtual User Group We know not everyone can take time out to attend conferences and user meetings, so we're making it easy for you to get involved with our series of virtual user groups. Learning Zone: Brian Harrington will call on his experience as a Six Sigma Black Belt Black Belt to share his thoughts on "A Six Sigma approach to building successful simulations.

1. Successful Simulations
using Less is More
By: Brian Harrington
9/17/2013
MTN-SIM, LLC
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2. Chaos of Change
We need to batch
build the Bodyside
Outers.
The new laser
welder looks like it
will be over 58
seconds.
How many carriers
are on the FS
delivery system?
We will be running
this 2-10 hr shifts.
How many units
between Seg1 and
Seg2?
The Main
Framing
conveyor runs
at 45fpm.
There are 3 repair
resources available.
We have 3 different
Pallet types. What
is the build
schedule?
Last week… we had
a 3 hr breakdown.
Looks like we are
2 weeks behind!
3 seconds for the
lift table to go up,
then another 3
seconds to drop.
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3. Complex Systems and Shorten
Development Time
This is a good equation for stress!
We’ll simulate it!
This just pushed the stress on the simulation team!
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4. Less is More using 6-Sigma
DMAIC or DMADV steps:
Define, Measure, Analyze, Improve, Control
Define, Measure, Analyze, Design, Verify
DES Steps:
Objective, Assumptions, Data Collection, Build Model, Verify,
Validate, Experimentation, Results
Very Similar steps!
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5. Y=f(x’s) Transfer Function
6-Sigma focuses on Key Input Factors (x’s) to deliver your
Response.
All of the x’s can be measured & controlled to increase accuracy
& precision of hitting your Target (Y).
System/Process
Trivial Many (N’s)
Vital Few (X’s)
Inputs (N’s & X’s)
Output (Y)
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6. The Art & Science of DES
Experience modelers tend to create a model with the least amount
of objects (data) to meet the objective.
A common modeling error is to add too much detail to the model;
attempting to simulate every move or event within the system.
The two key questions become:
1. What is the significant input?
2. How do we control it?
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7. The P-Diagram
The P-Diagram not only helps engineers to define the Key Parameters for
a robust design, but also acts as an excellent communication tool for
team reviews.
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8. Basic Building Blocks
The 6 Basic Building Blocks: Start Point, Queue, Activity, Conveyor,
Resource, and End Point.
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9. 6 is all you Need
1. Work Item Types: Can represent parts, carriers, signals,
phone calls, just about anything that requires a “Label
Profile”.
2. Activities: Work Centers, machines, tasks, process steps,
anything that requires a “Cycle Time”.
3. Storage Areas: Buffers, de-couplers, banks, magazines,
anything that requires a finite space to occupy over time.
4. Conveyors: Moving parts from pt A to Pt B; Number of parts
& Speed of conveyor.
5. Resources: Manpower, crews, forklifts, tugs; anything that
require a certain resource to be present.
6. End Pt: Keep track of statistics and free memory!
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10. Manufacturing Example
Problem Statement: 30% proposed increase in throughput of an overhead
sequencing bank of finite capacity
Questions from management:
Do we need to add capacity (additional lane), or
can we maintain the current size and improve
our sequencing routing logic?
The two key questions from Simulation Team:
1. What is the significant input?
2. How do we control it?
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11. Sequence Bank
(60 units)
Net JPH & Gross JPH into System
Vehicle Mix Percent
# of Designated Lanes
Capacity # Size of Deck
Overflow lanes
Sequencing Logic
Repair Times
Conveyor Cycle Times
# of vehicles on input transfers
The last goes on…
Throughput
Net JPH
INPUT SYSTEM OUTPUT
Priority of Work
# Resources
Build Schedule
Routing Logic
Consecutive jobs
The list goes on…
CONTROLS
Human Decisions
Internal Failures
Crew Factors
Market Demand
NOISE
Objective: Do we need to add an additional Lane?
P-Diagram (Seq Bank)
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12. Reduce Inputs & Get Answers
1. Examine the system assuming ideal (perfect)
sequence logic.
2. Some of the N’s & X’s can be ignored.
3. Determine the breakpoint where the system fails;
maybe it’s 23%.
 Use the least amount of data to get initial answers
to management ASAP!
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13. Establish Credibility
1. The program team might have critical answers sooner;
hence managers have additional time to secure funds.
2. The initial answers provided and backed by data will keep
the team engaged, and eager to provide further details!
3. The simulation engineer learns more about the system,
and can add additional details as necessary.
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14. Graph your Data!
One of the most basic steps in 6-Sigma; Exploit your data!
Stat-Fit for
SIMUL8
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15. Leverage Statistical Distributions!
• Curve fit your data! Instead of using lengthy
spreadsheets.
• Black-box; entire segments of the model can be
collapsed using distributions.
• If using empirical datasets, drop them into a “S8
Probability Profile Distribution”
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16. Use Known Distributions
The data collection phase of modeling can be the
lengthiest and most time consuming.
i.e.)
Downtime (MTBF & MTTR); such as Exponential & Erlang
respectively.
Cycle times often use a Fixed distribution; that is the “Design
Cycle Time”.
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17. Steady State
A common data collection error is to capture all data
points, and attempt to force them into one
distribution.
– Filter out the outliers; usually catastrophic points are
outside the scope of the steady state system.
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18. Tornado of Change
Utilizing Six-Sigma tools in conjunction with model building
keeps the team informed on what is of most importance to get
the program launched.
This is how several large manufacturing companies are able to
shorten the overall launch time, and bring their new product to
the market before the competition
If you find yourself caught up in the tornado of
change; just remember “Less is More”!
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19. Questions
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