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Transcript of Executive Information System (EIS) for the Aviation System ...carda/EIS.pdf · Executive...
Executive Information System (EIS) for theAviation System Risk Model (ASRM)
M.S. Thesis Defense
Student: Nathan Greenhut, M.S. StudentAdvisor: James T. Luxhøj, Ph.D.
Thesis Committee: Dr. Coit and Dr. Boucher
Department of Industrial and Systems EngineeringRutgers UniversityMarch 23rd, 2005
Research OverviewInitial Results
#1 Knowledge DisplaysCase DisplaysHaddon MatricesMulti-Factor Plots
#2 GAP AnalysisTaxonomyHaddon Matrices
#3 Sensitivity Analysis (SA)Birnbaum ImportanceIF Tool
#4 OptimizationAlgorithmsLinear ProgramGenetic Algorithm
Research Outcome (EIS)Further Remarks
Problem StatementHistorical Accident Rate
Overview of Risk ManagementFAA Office of System SafetyNASA Aviation Safety and Security Program
Literature SurveyRisk AnalysisBayesian Belief ModelsKnowledge Management
Aviation System Risk ModelV 1.0 Explanation of DSSV 2.0 Explanation of EIS
Problem Statement
To develop and disseminate methods, tools and feedback necessary to evaluate the risk impact of the NASA AvSP product portfolio (48) upon the 1990-1996 aviation accident baseline period.
An Executive Information System is required for the Aviation System Risk Model (ASRM) to gain an improved understanding of the interactions of the NASA AvSP products.
Aggregate data from the 20 ASRM risk models needs to be displayed in a meaningful way to NASA analysts, managers and executives.
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Boeing Summary of Commercial Airplane Accidents
Source: Boeing “Statistical Summary of Commercial Jet Airplane Accidents Worldwide Operations 1959-2003”
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Source: Boeing “Statistical Summary of Commercial Jet Airplane Accidents Worldwide Operations 1959-2003”
Boeing Summary of Commercial Airplane AccidentsProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Literature SurveyRisk Analysis
Bayesian Belief Models
Knowledge Management
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Decision Support System ASRM 1.0
(Jalil, 2003)
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Differences ASRM 1.0 (DSS) vs. ASRM 2.0 (EIS) Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Masters Thesis Research ProjectsResearch Project 1 Knowledge Displays
- Useful combination, presentation and dissemination of multiple streams of information collected.
Research Project 2 GAP Analysis- Provide summary statistics to Level 2 managers at NASA
and gain feedback for model development.
Research Project 3 Sensitivity Analysis- Use Birnbaum Sensitivity Analysis measures to determine
how much one causal factor affects another. Determines which nodes require more investigation and other methodologies.
Research Project 4 Optimization- Use Genetic Algorithms, Simulated Annealing, and Tabu-
Search in combination with developed database to give budgetary and accident rate optimization.
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Research Project 1 Comparisons of KD’sProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Research Projects StatusResearch Project 1 Knowledge Displays- Initial Case Displays, All Case Haddon & Multi-Factor- Final Result Model & Case Suite Haddon & Multi-Factor
Research Project 2 Gap Analysis- Initial All Case Gap Analysis- Final Result Model & Case Suite Gap Analysis, Pareto Chart
Research Project 3 Sensitivity Analysis- Initial Database Design and Opening Screen- Final Result Drill-down from case type to causal factor
Research Project 4 Optimization- Initial Compare A1 and A2 for LOC 405- Final Result Compare A1 and A2 for LOC 405, Any Model
Optimization*** Result EIS Prototype ***
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
EIS PrototypeProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
EIS Prototype – Multi-FactorProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Case Displays – Multiple EIS ViewsProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
EIS Prototype – Gap AnalysisProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
EIS Prototype – Pareto Causal FactorsProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Number of Analyses for Causal Factors
12.00
10.00 10.00
8.00 8.007.00 7.00 7.00 7.00
6.00 6.00 6.00 6.00 6.00
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
SBEInad
equa
te_QA
MAIN
AMSInhe
rent_d
esign
FAA_Inadeq
uate_res
ource
s
Inappro
priate_
Process
es
MFG_OP_Commun
icatio
nInfra
ction
FAA_Boeing
FAA_Oversi
ght
Inadeq
uate_
design
OrgProc
ess
Pre_flig
ht_Prep
aration
Causal Factors
Num
ber o
f Ana
lyse
s
EIS Prototype – Pareto ProductsProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Number of Analyses for Products
5855
50
40
2624 23 23
19
0
10
20
30
40
50
60
70
ASMM_1 SWAP_7 SWAP_6 ASMM_1_2 AM_1 SVS_1_4 SWAP_1 ASMM_3_6 SWAP_4
Product
Num
ber o
f Ana
lyse
s
Contributions from Thesis ResearchProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Developed methodology to compare numerous case studies in an EIS.
Meetings with technical monitor and NASA managers to develop and refine. Exposure to top-level management at public companies and government agencies.
5 Papers and Presentations
Produced deliverables for NASA contract.
Optimization, Sensitivity Analysis, Gap Analysis, Graphical Displays and Graphical User Interface for NASA managers and executives to utilize.
Bayesian Belief Network Genetic Algorithm
Future ResearchProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Extensions to EISExtension of Tools (“IF”, “What-If” and Sensitivity Programs C. Bareither)
Enterprise Information System
Optimization Techniques and Budgetary Linkages
Integration of EIS into other areas at NASA and FAA
EIS ReviewNumerous FAA Technical CentersAircraft Owners and Pilots AssociationChief System Engineer, FAA National Airspace Architecture and Systems Engineering FAA Washington ARTCC MITREEmbry-Riddle Aeronautical University NASA Pratt & Whitney
Gained feedback on relevance, effectiveness and meaningfulness of EIS from NASA managers and executives.
RESULT = Development of EIS Prototype with 20 ASRM models
Problem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Resulting Papers and PresentationsProblem
Statement
Historical
Accident
Rate
Risk Mgmt.
Literature Survey
ASRMV1 DSSV2 EIS
Projects#1 KD#2 GAP#3 SA#4 Opt.
Research
Further Remarks
Present Papers and PresentationsGreenhut, N. and Luxhøj, J. “Gap Analysis of Developed Models for an Aviation Technologies Decision Support System.” Industry, Engineering, Management Symposium. March 2003. Cocoa Beach, FL.Greenhut, N., Luxhøj, J. and Andres, D. “Graphical Enhancements to the Executive Information System (EIS) for the Aviation System Risk Model (ASRM).” Aviation Technology Integration Organization. September 2004. Chicago, IL.Greenhut, N., Luxhøj, J. and Coit, D. “Integer Program and Birnbaum'sImportance Measure for Aviation Technology Decision Support System (DSS)” INFORMS. October 2004. Denver, CO.Greenhut, N., Luxhøj, J. and Bariether, C. “Feedback Support for Gap Analysis of Aviation Technologies” Industry, Engineering, Management Symposium. March 2005. Cocoa Beach, FL.
Papers and PresentationsGreenhut, N., Luxhøj, J. and Bariether, C. “’What-If’ and Sensitivity Analysis for the Aviation System Risk Model” IIE National Meeting, IERC. May 2005. Atlanta, GA.