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Transcript of Heung - Suk Hwang, Gyu-Sung Cho Department of Industrial Engineering ,
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Heung - Suk Hwang, Gyu-Sung Cho
Department of Industrial Engineering ,Engineering College, Dongeui University
Gaya-dong, san-24 Pusanjin-ku, Pusan, 614-714 KOREA
Web-Based Project Risk Analysis ModelUsing Network Simulation
2005. 10. 11.
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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
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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
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Web-based Decision Support System
Internet/Intranet
Project ManagementSystem
Project ManagementSystem
InformationSystem
Group-JointWork
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Step 1 : Individual Evaluation of Alternatives- Brainstorming to Generate Alternatives and
to Define the Performance Factors- Evaluation of Alternatives Using AHP and
Fuzzy set ranking methodologies
Step 2 : Integrate the Individual Analysis- Heuristic Model- Fuzzy Set Priority Method
Step 3 : Risk Analysis Model - Stochastic Network Simulation Model- Fuzzy Set Priority Method
- Web-based Internet/Intranet Solution Builder
- GUI-type Program
- Integrated decision supportsystem
Step 1 : Individual Evaluation of Alternatives- Brainstorming to Generate Alternatives and
to Define the Performance Factors- Evaluation of Alternatives Using AHP and
Fuzzy set ranking methodologies
Step 2 : Integrate the Individual Analysis- Heuristic Model- Fuzzy Set Priority Method
Step 3 : Risk Analysis Model - Stochastic Network Simulation Model- Fuzzy Set Priority Method
- Web-based Internet/Intranet Solution Builder
- GUI-type Program
- Integrated decision supportsystem
Figure 2 . Three-step Approach of Project Evaluation Model
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NetworkInternet/Intranet
Server
Protocol Encoding
Protocol Decoding
Client
NetworkInternet/Intranet
Server
Protocol Encoding
Protocol Decoding
Client
Figure 4. Client and Server in Decision Support System
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☞ 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
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The GUI-type program of Solution Builder-2001
New File
Open
Close
Save
Save in Other Name
Encoding
Project Information
Printer Setup
Pre-Show
E-Mail Sending
Brainstorming
AHP
Integrate
Convert Brainstorming File into AHP File
AHP
Convert AHP File into Integrating Ranking File
Aggregating Ranking Method
Exit
Edit
Edit
Add
Delete
Move
Copy
Insert
Select All
Line Up
Sort
Change
Edit Levels
Add Level
Delete Level
Left - line
Upper - line
Right - line
Bottom - line
Centering
Centering Vertical
Show
Initial Size
Enlargement
Reduce
Tool Bar
Search Node
Status Bar
Standard
Item
Character
Line up
AHP
Integrating Ranking
File
New File
Open
Close
Save
Save in Other Name
Encoding
Project Information
Printer Setup
Pre-Show
E-Mail Sending
Brainstorming
AHP
Integrate
Convert Brainstorming File into AHP File
AHP
Convert AHP File into Integrating Ranking File
Aggregating Ranking Method
Exit
Edit
Edit
Add
Delete
Move
Copy
Insert
Select All
Line Up
Sort
Change
Edit Levels
Add Level
Delete Level
Left - line
Upper - line
Right - line
Bottom - line
Centering
Centering Vertical
Show
Initial Size
Enlargement
Reduce
Tool Bar
Search Node
Status Bar
Standard
Item
Character
Line up
AHP
Integrating Ranking
File
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Help
Index
Homepage
Solution Builder?
AHP
Compute
Partial Mode
Ideal Mode
Perf. Sensitivity
Dynamic Sensitivity
Trend Sensitivity
Node Information
Aggregating Priority
Basic Information
Heuristic 1
Heuristic 2
Fuzzy Set Priority
Tool
Copy in Clipboard
Save in Image File
Save in HTML
Option
Network
Server Setup
Client Setup
Help
Index
Homepage
Solution Builder?
AHP
Compute
Partial Mode
Ideal Mode
Perf. Sensitivity
Dynamic Sensitivity
Trend Sensitivity
Node Information
Aggregating Priority
Basic Information
Heuristic 1
Heuristic 2
Fuzzy Set Priority
Tool
Copy in Clipboard
Save in Image File
Save in HTML
Option
Network
Server Setup
Client Setup
Figure 5. Main-program of Solution Builder 2001
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2.1 Brainstorming☞ We used a brainstorming method and developed a GUI-type program
File Edit Show
New File
Open
Close
Save
Save in Other Name
Encoding
Project Information
Printer Setup
Pre-Show
E-Mail Sending
Exit
Edit
Add
Delete
Move
Copy
Insert
Select All
Line Up
Sort
Change
Initial Size
Enlargement
Reduce
Tool Bar
Search Node
Status Bar
Standard
Item
Character
Line up
Left - line
Upper - line
Right - line
Bottom - line
Centering
Centering Vertical
File Edit Show
New File
Open
Close
Save
Save in Other Name
Encoding
Project Information
Printer Setup
Pre-Show
E-Mail Sending
Exit
Edit
Add
Delete
Move
Copy
Insert
Select All
Line Up
Sort
Change
Initial Size
Enlargement
Reduce
Tool Bar
Search Node
Status Bar
Standard
Item
Character
Line up
Left - line
Upper - line
Right - line
Bottom - line
Centering
Centering Vertical
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☞ Sample output of alternative generation and construct the decision structure of an example for school selection
Education
Friendship
School Fee
Campus Life
Course
Transportation
School Selection
Solution Builder 2001 Brainstorming
File(F) Edit(E) Show(S) Tool(T) Client/Server Window(W) Help(H)
Node Data
School Selection
Education
Friendship
Campus Life
School Fee
Transportation
Course
Education
Friendship
School Fee
Campus Life
Course
Transportation
School Selection
Solution Builder 2001 Brainstorming
File(F) Edit(E) Show(S) Tool(T) Client/Server Window(W) Help(H)
Node Data
School Selection
Education
Friendship
Campus Life
School Fee
Transportation
Course
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2.2 Alternative Evaluation Using AHPSolution Builder 2001 BrainstormingFile(F) Edit(E) Show(S) Tool(T) Client/Server Window(W) Help(H)
Level 1Level 2Level 3Level 4Level 5Level 6Level 7Level 8
Lev
e l 1
Lev
e l 2
Lev
e l 3
Lev
e l 4
Lev
e l 5
School Selection
FriendshipEducation School Life School Fee Course Transportation
School A School CSchool B
Tree-View
Solution Builder 2001 BrainstormingFile(F) Edit(E) Show(S) Tool(T) Client/Server Window(W) Help(H)
Level 1Level 2Level 3Level 4Level 5Level 6Level 7Level 8
Lev
e l 1
Lev
e l 2
Lev
e l 3
Lev
e l 4
Lev
e l 5
School Selection
FriendshipEducation School Life School Fee Course Transportation
School A School CSchool B
Tree-View
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☞ A sample output pair-wise matrix of sample problem
Table 1. Pair-wise Comparison Matrix
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☞ the final result of school selection AHP which is given by School B(0.378) > School A(0.367) > School C(0.254).
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Solution Builder 2001 BrainstormingFile(F) Edit(E) Show(S) Tool(T) Client/Server Window(W) Help(H)
School A
School C
Conf HelpPrintDel
School C
School B
School A
School B
Solution Builder 2001 BrainstormingFile(F) Edit(E) Show(S) Tool(T) Client/Server Window(W) Help(H)
School A
School C
Conf HelpPrintDel
School C
School B
School A
School B
Figure 9. The AHP Result of School Selection Problem
The AHP Result of School Selection Problem
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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
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☞ Heuristic Method 1 rank order is given by C(0.467) > B(0.400) > A(0.133).
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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) .
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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, otherwiseTo 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).
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Figure 2. Three Steps of Risk Analysis
Identification · That is the risk ?· How can it be categorized?
Estimation
Identification
· What is the size of the risk ?· What is exposed to risk ?· What is the the risk?s likelyhood
of occurring ?· What is considered an acceptable risk ?· What is the exposure to risk ?· What is other choices exist to avert the risk?
Identification · That is the risk ?· How can it be categorized?
Estimation
Identification
· What is the size of the risk ?· What is exposed to risk ?· What is the the risk?s likelyhood
of occurring ?· What is considered an acceptable risk ?· What is the exposure to risk ?· What is other choices exist to avert the risk?
1) Project Risk Facets
4. Project Risk Analysis
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Researsh anddevelopmentuncertainty
R/D Risk
Economic productionand acquisition
uncertainty
Acquisition Risk
Operational Risk
Technical andoperationaluncertainty
Figure 3. Project Risk in Life Cycle
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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.
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Technical Capabiliy/Approach MethodTechnical Capabiliy/Approach Method
Cost Cost Schedule TimeSchedule Time Performance Performance
Uncertainty Uncertainty
RiskRisk
Figure 4. Project Risk Structure
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Risk Risk
AcquisitionAcquisition Decision Decision
Performance/Tech.Schedule.
Cost.
Operational
Support.
Figure 5. Risk Identification
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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
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-2 -1 0 1 2
.1 .2 .3 .4 .5 .6 .7 .8 .9 1.0Base Case Post-research 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
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4) Stochastic Network Simulation Method
SIMULATION
(Stochastic Network
SIMULATION)
NetworkFormulation of
Project
Parameter Estimate ofNetwork Activities : T, C, P
- Input Data- Criteria for project Risk (Success or fail Prob.)
Random No. Generationfrom the Distributions ofT, C, P
Simulation Spec andOptions
Output
Figure 6. Schematic Structure of Stochastic Network Simulation Model
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Timet
30.65
c274.34
0.50.6
0.7
Cost
Success probability
Figure 7. Sample Output for Time/Cost.
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5) MODEL APPLICATIONA 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.
S.I.DT2OT2
DT1OT1
Stop
Advanced Developmentof Main Body
Senser Acquisition
System IntegrationMain Body, Sample
- Four sub-systems ; new-CNC, Auto-assembler, main-body, and censers. - The detail network flow of this system is shown in Figure 9
Figure 8. Project Block Diagram
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INIT
ALL
OR
ALL
OR
ALL
Auto-assembler
New-CNC
MBODY
Senser
CNC
AA-AF
◆
CNCPDF◆
OR
ALL
OR
ALL
AATCOK
AATAOK
AATAF
AATBOK
AATBF
AATCF
CNCPD
OR
ALL
OR
ALL
START
TECHR
BASR PROTO SYSIN
OR
TERM
TESTOK
SUCWIN
SENS-SN
GDS
SENS
AA-BF
AA-CF
AA-COK
AA-AOK
AA-BOK
AND
TERM
TESTE
APLD
APLDF
AND
TERM
SENS-OK
AAF
AATF
○◆
◆
◆
○
○
○
○
INIT
ALL
INIT
ALL
OR
ALL
OR
ALL
OR
ALL
OR
ALL
Auto-assembler
New-CNC
MBODY
Senser
CNC
AA-AF
◆
CNCPDF◆
OR
ALL
OR
ALL
OR
ALL
OR
ALL
AATCOK
AATAOK
AATAF
AATBOK
AATBF
AATCF
CNCPD
OR
ALL
OR
ALL
OR
ALL
OR
ALL
START
TECHR
BASR PROTO SYSIN
OR
TERM
OR
TERM
TESTOK
SUCWIN
SENS-SN
GDS
SENS
AA-BF
AA-CF
AA-COK
AA-AOK
AA-BOK
AND
TERM
AND
TERM
TESTE
APLD
APLDF
AND
TERM
AND
TERM
SENS-OK
AAF
AATF
○◆
◆
◆
○
○
○
○
Figure 9. The detail Network Flow Diagram of Sample System
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Figure 10. Cost/Time Diagram
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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.
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Thank You
Kainan University,Prof. Heung-Suk Hwnag