Quantitative Risk Analysis for Aerospace Industry Intaver Institute Inc. 303, 6707, Elbow Drive S.W., Calgary AB Canada T2V 0E5 www.intaver.com Common Issues with Space System Projects • Multiple risks and uncertainties • Many uncertainties are event-driven • Historical data mining should include relevance analysis Existing Methodologies • • • • PERT Monte Carlo Simulation Bayesian approach Scenario analysis and Decision Trees Project Example Laser Interferometer Space Antenna (LISA) project Calendar Year 2002 ==> Proj ect Phasing 2003 4 1 2 3 Pre-Phase A 2004 2 3 4 Phase A 1 2005 2 3 1 FAD NASA HQ Milestones 4 1 2006 2 3 4 Phase B 1 2007 2 3 ICR/CA FAD HQ 4 2008 2 3 1 4 1 2009 2 3 4 1 Phase C/D 2010 2 3 4 2011 2 3 1 MDR SCR ESA MOU (F) PDR CDR Obs 1 PER MRR ORR Briefing Partnering Phase Acquis ition RFI SRR TRR S/C1 PER Execution Phase Prep Phase RFP D Sel RFP 2012 4 PCA NAR M is s ion Re vie w s SE&I Contractor 4 MOR LRR PSR FRR Sel Te chnology LISA T est Package (SM2) ST 7 DRS (SM2) Interferometry Measurement System System Verification Disturbance Reduction System Payload Space craft CDR Deliver to SM2 SM2 Launch Deliver to SM2 SM2 Launch LISA Demo PDR CDR Trades Subs Assy Test Model Envr R2 Model Envr R1 Trades Subs GRS TRL5 Tgt Std Assy Rqts/Architecture/Trades ITT Award ESA Definition Phase Obs e rvatory I&T Cons te llation Te s ting Launch Cam paign DRS Demo TRL6 TRL5 Model Envr R3 Testbed Demos GRS TRL6 Test PDR ITT Award CDR Design PDR CDR EM 1 Build / Test EM 1 2 3 2 3 ESA Implementation Phase EM 1 2 3 Preps Observatory I&T 1 2 3 Preps Constellation Testing LRD Launch Preps The document is courtesy of NASA/Goddard Space Flight Center 1 Heuristics and Biases in Project Management The Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel 2002 Decision makers use “heuristics”, or general rules of thumb, to arrive at their judgments. In certain instances, this will lead to systemic biases. Daniel Kahneman Examples of Heuristics in Project Management • Representativeness – unwanted appeal to detailed scenarios • Availability – access the probability of an event by the ease with which instances can be brought to mind • Anchoring – human tendency is to remain close to the initial estimate Event Chain Methodology Event Chain Methodology is a method of modeling uncertainties for different time-related business and technological processes including project management for space systems. Moment of Risk and State of Activity An activity (task) in most real life processes is not a continuous uniform procedure. Tasks are affected by external events, which transform an activity from one state to another. Event Chains Events can cause other events, which will create event chains. These event chains can significantly affect the course of the project. Monte Carlo Simulations Once events and event chains are defined, quantitative analysis using Monte Carlo simulation can be performed to quantify the cumulative impact of the events. Information regarding the uncertainties expressed as an event is supplemented with distributions related to duration, start time, cost, and other parameters Critical Chains of Events The single events or the event chains that have the most potential to affect the projects are the “critical events” or “critical chains of events.” History Matching and Relevance Analysis • Similar events or event chains are found based on historical data • Analysis based on Bayesian approach is performed and relevance parameter is calculated • Project manager defines relevance of each event or event chain for the current project • Both calculated and user defined relevance parameters are used to determine probability and impact of the events for the current project Performance Tracking with Event and Event Cha During the course of the project, the probability and time of the events can be recalculated based on actual data. Actual performance data and original estimate is used forecast duration of activity with risks Event Chain Diagrams Event Chain Diagrams are visualizations that show the relationships between events and activities and how the events affect each other Repeated Activities Common scenario for real life projects: sometimes a previous activity must be repeated based on the results of event in a succeeding activity Event Chains and Risk Mitigation Mitigation plan can be assigned to an event or event chain. These small schedules will be triggered when an event chain occurs. Resource Allocation Based on Events Event: the reassignment of a resource from one activity to another Example: if an activity requires more resources to complete it within a fixed period, this will trigger an event to reallocate the resource from another activity. Project Management Workflow using Event Cha Methodology 1. 2. 3. Define a detailed project schedule with resources and costs assigned to the activities Define a detailed risk breakdown structure and assign risks to the activities. The probability of each event can be taken from historical data. Define the activities associated with mitigation efforts and then assign costs and resources to them. Project Management Workflow using Event Chain Methodology 4. Perform a quantitative risk analysis using Monte Carlo simulations. 5. Analyze the results of the quantitative risk analysis: perform a sensitivity analysis and identify the crucial tasks and critical risks. Project Management Workflow using Event Chain Methodology 6. Perform reality checks: compare the results of analysis with outside independent expert reviews and historical experience. 7. Monitor the course of the project on a regular basis, perform repeated quantitative risk analysis, reassess the event and event chain parameters Acknowledgements Intaver Institute Inc. is thankful to Kevin N. Miller, Deputy Project Manager/Resources, Laser Interferometer Space Antenna (LISA) Project, NASA/Goddard Space Flight Center, for providing data necessary to illustrate the methodology discussed in the paper.