1. Defining Procedures for Decision Analysis May 02-14 & Engr 466-02A April 30, 2002 Client & Faculty Advisors –Dr. Keith Adams –Dr. John Lamont –Dr. Ralph Patterson III Team Members –Marvin Choo –Dave Cohen –Amy Kalbacken –Natasha Khan –Jesse Smith –Theodore Scott

2. Acknowledgments Faculty Advisors Faculty Advisors Dr. Doug Gemmil Dr. Doug Gemmil Dr. Kenneth Kirkland Dr. Kenneth Kirkland Dr. Jo Min Dr. Jo Min Dr. Ron Nelson Dr. Ron Nelson Dr. Steve Russell Dr. Steve Russell Dr. Howard Van Aucken Dr. Howard Van Aucken Dr. Max Wortman Dr. Max Wortman

3. Presentation Outline Problem Statement Problem Statement Design Objectives Design Objectives End-Product Description End-Product Description Assumptions & Limitations Assumptions & Limitations Project Risks & Concerns Project Risks & Concerns Technical Approach Technical Approach Evaluation of Project Success Evaluation of Project Success

4. Presentation Outline Recommendations for Future Work Recommendations for Future Work Personnel Budgets Personnel Budgets Financial Budgets Financial Budgets Lessons Learned Lessons Learned Closing Summary Closing Summary

5. Problem Statement Problem Problem – –Companies often are required to make major decisions regarding the commercialization process for a product, process, or service – –How can we maximize efforts most efficiently during the decision-making process? Goal Goal – –Develop a guide that aids users in the decision- making process

6. Design Objectives Design Constraints Design Constraints –Inaccurate research (especially Internet) –Uncovering all factors –Limited understanding of algorithms

7. Design Objectives Intended Users & Uses Intended Users & Uses –People in decision-making positions Gain greater understanding of methods Gain greater understanding of methods –Software Programmers Have background reference information Have background reference information Detailed starting point for developing software Detailed starting point for developing software

8. End Product Description The report will aid individuals in conducting a thorough analysis of the decision factors surrounding their particular product, process, or service The report will aid individuals in conducting a thorough analysis of the decision factors surrounding their particular product, process, or service

9. End Product Description Written Report Written Report –Key factors regarding decision processes –Algorithms used in decision analysis –Examples of Algorithms –Functional Software Specification –Reference Material

10. Assumptions Considering company goals Considering company goals Aids in decision-making but will not be the only tool used Aids in decision-making but will not be the only tool used Take into account other decision-making factors and considerations Take into account other decision-making factors and considerations Using decision-making algorithms Using decision-making algorithms

11. Assumptions Use algorithms based on research Use algorithms based on research Have basic knowledge of decision-making process Have basic knowledge of decision-making process For any business interested in decision analysis software For any business interested in decision analysis software No sophisticated mathematics or statistics are used in algorithms No sophisticated mathematics or statistics are used in algorithms

12. Limitations Ranking the importance of each factor differently Ranking the importance of each factor differently Not all data accounted for Not all data accounted for Selected algorithms may not be applicable to all decisions Selected algorithms may not be applicable to all decisions Need to apply each process to specific situation Need to apply each process to specific situation

13. Limitations Limited knowledge of algorithms Limited knowledge of algorithms Algorithms may require a statistical background or other expertise Algorithms may require a statistical background or other expertise All factors & constraints may not be uncovered All factors & constraints may not be uncovered Algorithm applicability is based on project requirements & criteria Algorithm applicability is based on project requirements & criteria

14. Project Risks & Concerns Scheduling interviews Scheduling interviews Finding information Finding information Losing a team member Losing a team member Understanding project Understanding project

15. Technical Approach Purpose To determine an algorithm for use in creating software that will implement the decision analysis process To determine an algorithm for use in creating software that will implement the decision analysis processProcess Determine the basic project process Determine the basic project process Compile a list of potential algorithms Compile a list of potential algorithms Create a set of criteria for evaluating the algorithms Create a set of criteria for evaluating the algorithms Research the algorithms Research the algorithms Select the most applicable algorithms Select the most applicable algorithms

16. Technical Approach “Basic Project Process”

17. Technical Approach “List of Algorithms” Artificial Neural Networks Artificial Neural Networks Bayesian Logic Bayesian Logic Decision Matrix Decision Matrix Decision Tree Decision Tree Fuzzy Logic Fuzzy Logic Genetic Algorithms Genetic Algorithms Linear Algebra Linear Algebra

18. Technical Approach “Criteria for Evaluating the Algorithms” What type of problems is the algorithm good for? What type of problems is the algorithm good for? What input data is needed? What input data is needed? What kind of control is needed? What kind of control is needed? How does the algorithm work? How does the algorithm work? What are the expected outputs? What are the expected outputs? How easy or difficult is it to implement? How easy or difficult is it to implement? Is there any information on the solution time, problem size, etc. Is there any information on the solution time, problem size, etc. Are there any examples available for the algorithm? Are there any examples available for the algorithm? Are there sufficient conditions for convulgence? Are there sufficient conditions for convulgence? If the algorithm is discovered to be ineffective what are the reasons in support of the determination. If the algorithm is discovered to be ineffective what are the reasons in support of the determination.

19. Technical Approach “Selecting the Best Algorithms” Artificial neural networks Able to learn, memorize, and create relationship between data Able to learn, memorize, and create relationship between data Able to work with the non-linearities Able to work with the non-linearities Used for the accurate prediction of events Used for the accurate prediction of events Decision trees Useful for handling a lot of complex information Useful for handling a lot of complex information Genetic algorithms Multi objective solutions can be defined Multi objective solutions can be defined

20. Project Success Initial Startup –Identifying key factors –Interview coordination Interview Results & Project Definition –Conduction Interviews –Completing Project Plan

21. Project Success Implementation –Algorithms –Functional Software Specification Testing –Scenario Example –Needs further testing

22. Project Success End Product –Guide Algorithms Report Algorithms Report Functional Software Specification Functional Software Specification Reference Material Reference Material –Final Report Software Package

23. Recommendations for Further Work Create detailed models of selected algorithms Create detailed models of selected algorithms Consult with professionals to evaluate algorithms Consult with professionals to evaluate algorithms Develop a functional software package Develop a functional software package

24. Personnel Budget PlannedRevisedActual Dave Cohen 778790 Amy Kalbacken 889596 Theodore Scott 758690 Marvin Choo 818185 Natasha Khan 797983 Jesse Smith 898993

25. Budgeted Hours Vs. Actual Hours

26. Financial Budget Item Original Estimate Cost Revised Estimate Cost Actual Cost to Date Printing $60.00 $60.00$45.00$42.00 Transportation $0.00 $0.00 Labor Equipment & Parts $0.00 $0.00 Telephone Total Estimated Cost $0.00 $0.00

27. Lessons Learned Essential team attributes Essential team attributes –Teamwork –Time Management –Brainstorming Knowledge acquired Knowledge acquired –Division of labor, team goals, task management –Interview information –Defining scope of project

28. Lessons Learned Algorithms Algorithms –Complexity –Need to study more carefully Issues faced in decision-making process Issues faced in decision-making process –Time vs. Money –Who is involved in decision-making process –Engineering vs. Business Processes

29. Closing Summary Conclusion A tool created to aid during the decision-making process would be well worth developing A tool created to aid during the decision-making process would be well worth developingBenefits Identifies key factors in the decision process Identifies key factors in the decision process Characterizes the decision-making process Characterizes the decision-making process Determines the best decision processes Determines the best decision processes Aid in further analyzing a particular decision Aid in further analyzing a particular decision Narrows in on the optimum decision Narrows in on the optimum decision

30. Questions