Heung - Suk Hwang, Gyu-Sung Cho Department of Industrial Engineering ,

1. Web-Based Project Risk Analysis Model • Using Network Simulation 2005. 10. 11. Heung - Suk Hwang, Gyu-Sung Cho Department of Industrial Engineering , Engineering College, Dongeui University Gaya-dong, san-24 Pusanjin-ku, Pusan, 614-714 KOREA

2. Contents • 1. Introduction • 2. Individual Project Alternative Evaluation Using • AHP(Step 1) • 3. Integrating the Results of Individual Evaluations • 4.Project Risk Analysis Models • - Project Risk Facets • - Model Application • 5. Summary and Conclusions

3. 1. Introduction • ☞Developed a project risk analysis model based on simulation • and multi-attribute structured decision support system • ☞ Project Risk : Project schedule, Cost and Performance risk • ☞ 1) Deterministic risk factor analysis model based or AHP • (analytic hierarchy process) weighted value, and • 2) Network simulation model based on venture evaluation • and review technique. • ☞ Also we developed computer program and demonstrated the • pro posed methods, • ☞ Then we carryout risk analysis

4. Web-based Decision Support System Project Management System Information System Group-Joint Work Internet/Intranet

5. Figure 2 . Three-step Approach of Project Evaluation Model

6. Figure 4. Client and Server in Decision Support System

7. ☞ Construct decision structure and Derive out the evaluation alternatives - the group decision ideas, the creative ideas ☞ we used a brainstorming method and developed a GUI-type program ☞ To create the ideas of project evaluation alternatives and methods for decision support system analysis, ☞ we construct decision structure using the brainstorming file in the internet/intranet–based environment

8. The GUI-type program of Solution Builder-2001

9. Figure 5. Main-program of Solution Builder 2001

10. 2.1 Brainstorming ☞ We used a brainstorming method and developed a GUI-type program

11. ☞ Sample output of alternative generation and construct the decision structure of an example for school selection

12. 2.2 Alternative Evaluation Using AHP

13. ☞ A sample output pair-wise matrix of sample problem Table 1. Pair-wise Comparison Matrix

14. ☞ the final result of school selection AHP which is given by School B(0.378) > School A(0.367) > School C(0.254).

15. Figure 9. The AHP Result of School Selection Problem The AHP Result of School Selection Problem

16. 3. Integration of Individual Evaluation ☞ For the integration of the results of individual evaluations, prioritized sets, we used two Heuristic models 1, Model 2 and Fuzzy set priority method 1) Heuristic Model 1 : • For example of the Heuristic Method 1, a sample result with • N = 5 e valuators and M = 3 alternatives is given as : • Evaluator 1 : B > A > C, Evaluator 2 : B > C > A, • Evaluator 3 : C > A > B, Evaluator 4 : C > B > A, • Evaluator 5 : C > B > A

17. ☞ Heuristic Method 1 rank order is given by C(0.467) > B(0.400) > A(0.133).

18. 2) Heuristic Model 2 : - The evaluator frequency matrices were added to form a summed frequency matrix - Then, the preference matrix was developed by a comparison of the scores in the component cells(A, B versus B, A). - If the A, B value equals B, A, then each component cell in the matrix is given by 1/2. On the other hand if the A, B value is greater than the B, A , then A, B is given by one and B, A cell of the preference matrix is given by 0. ☞ By applying the Heuristic Model 2 to the same example of Heuristic Method 1, the result is given by C(0.450) > A(0.392) > B(0.158).

19. 3) Fuzzy Set Priority Method . The fuzzy matrix complement cell values sum to 1 and fuzzy set difference matrix is defined as follows : R-RT = U(A, B) - (B, A), if U(A, B) > U(B, A), = 0, otherwise To obtain fuzzy preferences, following five steps are considered : Step 1 :Find the summed frequency matrix (using heuristic method 2) Step 2 : Find the fuzzy set matrix R which is the summed frequency matrix divided by the total number of evaluators Step 3 : Find the difference matrix R - RT = U(A, B) - U(B, A), if U(A, B) > U(B, A), = 0, otherwise where, for U(A, B) quantifies, A is preferable to B. Step 4 : Determine the portion of each part Step 5 : The priority of the fuzzy set is then the rank order of values in decreasing. The sample problem result by fuzzy set priority method is given by C(0.492) > B(0.387) > A(0.121).

20. 4. Project Risk Analysis 1)Project Risk Facets Figure 2. Three Steps of Risk Analysis

21. Figure 3. Project Risk in Life Cycle

22. 2) PROJECT RISK ANALYSIS MODELS . Normally project risk can be assessed by following factors : ①  Contribution to project performance, ②  Technical validity, ③  Economic effect, ④  Systematic validity.

23. Figure 4. Project Risk Structure

24. Figure 5. Risk Identification

25. 3) Risk Factor Analysis Method In this study, we proposed two practical risk analysis models : 1) risk factor analysis model, and 2) network simulation model[6] are given as following. A Deterministic model based on risk factor analysis method using a scoring method, such as AHP(Analytic Hierarchy Process)[4] weighted value. Four steps of this method is given by : Step 1 : construct the evaluation items and evaluate each items in the evaluating form using -2∼+2 scoring scale, Step 2 : compute the AHP weighted value of each evaluation items and compute the weighted score of each evaluation item, Step 3 : compute the total evaluation score of each major evaluating items considering following items(in this study, we used for items as following) - industrial improvement feasibility, - technical feasibility, - economical feasibility, - institutional feasibility Step 4 : compute the risk using probability scale

27. -2 -1 0 1 2 Base Case Post-research .1 .2 .3 .4 .5 .6 .7 .8 .9 1.0 PF· PT · PE · PI=PE PF · PT · PE · PI=PE 0.93×0.85×0.93×0.93=0.70 0.94×0.89×0.94×0.94=0.74

28. 4) Stochastic Network Simulation Method Figure 6. Schematic Structure of Stochastic Network Simulation Model

29. Figure 7. Sample Output for Time/Cost.

30. 5) MODEL APPLICATION A new manufacturing system development : - In the advanced development step after successful completion of its 3 years basic research. - The system consisted of a main body and three sub-systems(A, B, C). - The main body is planned to develop in house, and three censers will be imported. The project block diagram is given as Figure 8. Figure 8. Project Block Diagram • Four sub-systems ; • new-CNC, Auto-assembler, main-body, and censers. • - The detail network flow of this system is shown in Figure 9

31. Figure 9. The detail Network Flow Diagram of Sample System

32. Figure 10. Cost/Time Diagram

34. 5. CONCLUSION - In this research, developed a risk analysis model, - To quantify the risks and to generate the choice of the actions to be taken to reduce the project uncertainties. - Two analysis models are proposed in this study; 1) risk factor analysis model and 2) network simulation model using VERT(venture evaluation and review technique). - The objective of proposed models are to estimate 1) the schedule, 2) cost and 3) performance risks. - The proposed models will be used in the area of R&D project evaluation to reduce project risks. - Also, developed computer programs and have shown the results of sample run for an acquisition project of manufacturing system. It was known that the proposed model was a very acceptable for R&D project evaluation.

35. Thank You Kainan University, Prof. Heung-Suk Hwnag