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Spreadsheet Modeling Dr Brad Morantz

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1 Spreadsheet Modeling Dr Brad Morantz

2 Background  Almost everyone has a spreadsheet at their desk  Few have mod/sim packages at their desk Arena costs $18K OpNet is $45K  Sometimes need to do Proof of Concept  Need to insure testing in corners of envelope of variable space

3 DASE? DOE?  DASE = Design & Analysis of Simulation Experiments  DOE = Design of Experiment An experiment must be properly designed to produce realistic and quality results An experiment must try out all ranges of potential values  Search the corners of the envelope  Brad’s Theorem: Every system has a point in variable space where the system goes ‘postal’

4 Advantages  Availability of software  Clear box Can see what is going on inside Can make changes easily  Can make changes and see what happens  Many plug-ins to enhance performance and presentation

5 DASE Advantages  Design Easy to change input variables Easy to monitor/see input values Scenario Manager  Analysis Easy to create links to analysis Many analysis tools in spreadsheet Graph/Chart in spread sheet

6 DASE Considerations  Input values must reach the “corners of the envelope” Volume filling in variable space Easy to implement test matrix Values must be realistic Can not have impossible combinations

7 First Exposure  I saw this first time teaching in the B school at GSU  Can quickly build spreadsheet model to make business decisions  I built a spreadsheet model to track my mortgage Found 3 mistakes Saved $1000’s

8 Business Model  Want to hold Rock Concert to make $ Name band costs  $10K to appear  $1 a head over 5000 people Local band is $1K  Attract more people Concessions  25% profit  Sell more on hot days Etc, Etc, but can we make a profit? DASE considerations!

9 Science Problem  Have a MP Computer MIMD capable  Have lots of data arriving daily  How to optimize throughput  Built spreadsheet model Allowed me to wipe out sections Simulated down time  Results proof of concept  Bought me a Arena  Over doubled throughput  DASE considerations

10 Projectile  Input angle and muzzle velocity  Need to know how far it will go  Only realistic ranges for both variables  Can see all values as it travels  Easy to plot trajectory  DASE Considerations  Sample program Sample program

11 Guided Weapon  Have weapon  Given specifications  Calculate SSPD  Then have guided weapon  Calculate SSPD  Multiple guided weapon w/ unitary target  Calculate SSPDn  Sample program Sample program

12 Acronyms  SSPD Single Shot Probability of Damage  CEP circular error probable  REP range error probable  DEP deflection error probable  SR slant range  There are plenty more, see reference next slide

13 References  Weaponeering, Conventional Weapon System Effectiveness, Morris R Driels  Numerous books on Spreadsheet modeling (all are on business applications) contact me if need info

14 Big Thanks  To Will Haas who loaned me the Weaponeering book and who taught me much about this. He was very patient and I appreciate it.

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