Description
In engineering, system integration is defined as the process of bringing together the component subsystems into one system and ensuring that the subsystems function together as a system.
Systems Design & Integrated System Health Management (ISHM) Technologies
Dr. Francesca A. Barrientos
Complex System Design & Engineering Group Discovery and Systems Health Technical Area Intelligent Systems Division NASA Ames Research Center
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 1
ISHM for Exploration Systems
The art and science of managing off-nominal conditions systems may encounter during their operational life either by designing out failures early on, or designing in the capability to safeguard against or mitigate failures • Key enabler for crew self sufficiency and even autonomy • True ISHM has never been achieved • Key limitation: ISHM typically retrofitted onto subsystems after the vehicle has been designed or even built
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 2
ISHM Challenge for Exploration Missions
ISHM design must be part of the overall design process and viewed as a system engineering discipline, encompassing a range of technologies & methods
Vehicle ….. Propulsion Subsystem Sensor Communications Subsystem Sensor Health Data Acquisition Line Power Subsystem Sensor ….. …..
ISHM
….. Fault Detection , Isolation , and Recovery (FDIR) Command Line
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
3
Facing the Challenge of ISHM Design
• Early influence on system design to guide choice of health management methods and technologies
– Eliminate/reduce likelihood of failure by design through part selection and built-in redundancy – Prognosis in conjunction with preventative maintenance – Fault management with diagnosis and recovery technologies
• •
Failure modes & effects analysis activities for ISHM
– Feed fault information into the design process to create simulations of faults and improved designs to deal with faults
The initial design must be examined in the context of the full system life cycle
– Include all stakeholders (ops, maintenance, etc.) in the design – Solution optimized in terms of well-defined Figures of Merit (FOMs)
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
4
The current state of ISHM Design
• Insufficient interaction during the design process between failure analysis activities and design processes to prevent or mitigate these failures Limited interaction between reliability analyses and design processes Little interaction between operational training simulations and assessments of operational dependability and design process Operations and maintenance costs and risks become much larger than initially projected during Phase A initial design No formal tools and methodologies to allow program managers and engineering designers to formulate a clear understanding of the impact of the decisions on the downstream phases such as operations and maintenance on the systems design, and vice versa
• • • •
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
5
ISHM Design Goal
“DESIGN IN” THE ISHM CAPABILITY FROM THE BEGINNING! • Good news: Current interest is strong!
– First international forum on Integrated Systems Health Engineering and Management held in November – CEV/CLV
• •
Bad news: We lack methodologies & tools to achieve this! Some successful attempts
– Requirements: Specify ISHM “shall” statements at beginning of project • Joint Strike Fighter (5% of requirements are HM related) • Boeing 777 • CEV and CLV (planned) – Trade Studies: Integrate ISHM design with system-level design and do trade studies with ISHM as a design attribute • Northrop/NASA ARC SA&O effort for 2nd Gen RLV program • Honeywell/QSI SA&O and modeling effort – Integrate operations and maintenance considerations into design: • Boeing 777
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
6
The ISHM Design Paradigm:
Changing the Way ISHM Design is Done
ISHM
Risk lists, Failure Modes Reliability Models Sensor selection Maintainability Feature selection Testability
FUNCTIONAL MODELS
Functional Requirements Qualitative Analysis Risk Analysis Functional FMEA
PRA/QRA FTA/ETA FMEA
Advanced Studies
Preliminary Analysis
Definition
Design
Development
Operations
Proposed Design Paradigm Shift #1: Integrate ISHM design into very early
functional design stage (including failure and reliability analyses)
Feasible Concepts
Feasible Concepts
Functional Baseline
Build
Deploy
Proposed Design Paradigm Shift #2: Assess impact/tradeoffs of ISHM Figures
of Merit (FOMs) on system level FOMs from all stakeholders throughout mission lifecycle
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 7
Key Challenges for Paradigm Shift
• Embedding ISHM design into early functional design requires high-level modeling and analyses
– Models of system components and design parameters are not yet available – Integrating health management for complex systems requires capability to model functionality of individual subsystems as well as their interactions
•
Conducting failure, reliability and risk analyses during functional design stage
– Need mathematical techniques for risk assessment and resource allocation under uncertainty must be incorporated with high-level analyses
•
Design of ISHM is multidisciplinary and multi-objective by nature
– Need mathematical framework to achieve effective analysis & optimization – Designing an ISHM that encompasses all subsystems of a space mission is the result of interaction among engineers and managers from different disciplines with their own domain expertise
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
8
Candidate Design Methods
• Risk and Reliability Based Design Methods
– PRA, FTA, FMEA/FMECA, reliability block diagrams, event sequence diagrams, safety factors, knowledge-based methods, expert elicitation
• Design for Testability Methods • Formal design theory and methodology
– Function-based design and modeling – Mathematical techniques:
• Uncertainty modeling, decision-based design, risk-based design, design optimization, etc.
– Design for X methodologies
• Design for ISHM, Design for maintainability, Design for failure prevention, …
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
9
CSDE group R&D efforts
• Function-based modeling and failure analysis • Risk assessment by portfolio management and optimization • Multi-objective and multi-disciplinary system analysis & optimization
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
10
Function-Based Design, Modeling & Failure Modes Analysis for ISHM Design
• • Develop “functional model” of vehicle and ISHM subsystems Standardized representation enables retrieval of design knowledge based on common functionality
• •
Correlate historical and potential failure modes with functionality Functional model as living document during system lifecycle from design through operations
NASA RMC VI 6-8 December 2005 11
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
The ISHM System Functional Blueprint
Ex: Design of the ADAPT testbed at NASA ARC • Used to discover interfaces and interactions between functions • Used to add required functionality for ISHM (detect, sense, activate, etc.) • Used to discover functional failures and add safeguards
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
12
Function-Based Failure Modes Analysis
Project, SoS Project ISS Spacecraft Thermal PVATCS PVR Flex Hose PFCS Check Valve Temp Sensor Cable Shield Cold Plate Propulsion Power SSU DC-DC Conv. Lead Capacitor PVCE Capacitor LDI Diode 8-String CCAs Elec. Wire SAW DCSU Power Supply Diode Capacitor Component Controller electric wire Board diode Vacuum Seal lead capacitor Elec.Wire capacitor Heat Fin
E.E. (secondary voltage from aternate power channel) Control/Data Import E.E. E.E. Failed Components DC-DC Converter Voltage Import Control Actuate Control Control/Data Guide E.E. CCA (circuit card assembly Condition LDI Current, Voltage Primary Power Return E.E. (SAW strings 1 and 2) E.E. (SAW strings 3 and 4) E.E. (SAW strings 5 through 82) Import E.E. Guide E.E. PVCE Import E.E. Guide E.E. Measure E.E. Mix E.E. Regulate E.E. Distribute E.E. Measure E.E. Mix E.E. Guide E.E. Export E.E. E.E. (SAW)
System
SubSystem
Assembly
SubAssembly
Component
Component 2
• Developing templates for functional models
• Generating database of functions for S/C • Mining Failure Databases • Developing a Software Query Interface
Sequential Shunt Unit (SSU)
Shunt/Unshunt Import E.E. Guide E.E. Measure E.E. Current E.E. (Primary Power Bus)
..........
............
..........
Measure E.E.
Guide E.E.
Export E.E.
Components in colored boxes have failures identified from reports
Subfunction Guide Guide/Stop Guide Store/Supply Store/Supply Flow electrical electrical electrical electrical electrical Sub-assembly 8-String CCAs LDI DC-DC Converter DC-DC Converter PVCE
SSU Failures
Failure Mode Arc Discharge
Primary Identifier RPCM Breakdown Breakdown RBI Abrasive Wear Wear Arc Discharge BreakdownBaseplate Electrical Overstress Overstress
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
13
FFMEA Design Interface (w/ UMR)
Resource allocation to minimize risks due to functional failures
• Use of formal risk-based design and optimization techniques for ISHM risk assessment
– Risk-informed trade study framework to account for risk & uncertainty in early design: RUBIC design – Framework for quantifying risk due functional failures and allocating resources for risk reduction during concurrent design – Starting from the functional model, RUBIC optimally allocates resources to mitigate risks due to functional failures • Ex of resources: hours spent on analysis, redesign, dollars allocated, acquiring more reliable components, adding redundancy, etc.
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
15
Resource Reallocation to Minimize Risk and Uncertainty due Functional Failures
Column # 1st 2nd 3rd 4th 5th 6th 7th 8th 2nd 3rd
Subsystem Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller
Function Import Electrical Energy Export Electrical Energy Guide Electrical Energy Regulate Electrical Energy Guide Electrical Energy Condition Electrical Energy Guide Electrical Energy Convert Electrical E. to Rotational E. Convert Rotational E. to Electrical E. Export Thermal Energy
Resource Allocation <<1% 4% <<1% 36% 6% 17% <<1% 9% 13% 10%
Total Allocation to Controller Subsystem: 64%
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
16
RUBIC Prototype Development
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
17
System Analysis & Optimization (SA&O)
• SA&O Framework (based on prior work done for 2nd Gen RLV)
– Select a set of Figures-of-Merit – Select a set of models---such as cost, safety, operations, reliability, false alarm rates and maintainability---that generate FOMs – Determine the tools to implement the models – Determine the data flow requirements between the models Mass Risk – Perform trade studies
Power
•
Current Enhancements:
– – – –
Schedule Cost
Multi-objective & multi-disciplinary optimization Performance Data flow/exchange environment (implemented in Model Center) Automation for rapid trade analyses Ability to feed back into functional design stage:
• Add new functionality to enable ISHM to operate as an integrated system? • Change functionality to enable maintainability, performance, reduce risk?
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 18
ISHM System Analysis & Optimization
Model center implementation
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
19
Multi-Disciplinary, Multi-Objective Optimization for ISHM Design
• ISHM design can be formulated as an optimization problem
– ISHM Design Variables – ISHM Objectives (Figures of Merit) – ISHM Design Constraints: Feasibility Constraints + Hard Requirements
•
Multi-objectives/constraints in each sub-system
– Functionally separable Fi,j and exclusive fj – S Metric to encourage convergence; H Metric to encourage diversity
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
20
Summary & Conclusions
• • • ISHM is a key enabler for exploration systems Towards ISHM as a systems engineering discipline and co-design with vehicle systems Complex System Design & Engineering Group Research
– – – – Function based failure modes analysis Risk and uncertainty based design ISHM system analysis and optimization (SA&O) Current Involvement:
• CEV, CLV for Constellation/ESMD • IVHM and Aging Aircraft for Aviation Safety/ARMD
An ISHM design paradigm shift is required for a successful and sustainable exploration endeavor
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 21
Questions, Comments, Suggestions
Complex Systems Design & Engineering Group
Intelligent Systems Division, NASA ARC
Francesca Barrientos
[email protected]
Irem Tumer, Group lead
[email protected]
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
22
doc_251542959.pdf
In engineering, system integration is defined as the process of bringing together the component subsystems into one system and ensuring that the subsystems function together as a system.
Systems Design & Integrated System Health Management (ISHM) Technologies
Dr. Francesca A. Barrientos
Complex System Design & Engineering Group Discovery and Systems Health Technical Area Intelligent Systems Division NASA Ames Research Center
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 1
ISHM for Exploration Systems
The art and science of managing off-nominal conditions systems may encounter during their operational life either by designing out failures early on, or designing in the capability to safeguard against or mitigate failures • Key enabler for crew self sufficiency and even autonomy • True ISHM has never been achieved • Key limitation: ISHM typically retrofitted onto subsystems after the vehicle has been designed or even built
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 2
ISHM Challenge for Exploration Missions
ISHM design must be part of the overall design process and viewed as a system engineering discipline, encompassing a range of technologies & methods
Vehicle ….. Propulsion Subsystem Sensor Communications Subsystem Sensor Health Data Acquisition Line Power Subsystem Sensor ….. …..
ISHM
….. Fault Detection , Isolation , and Recovery (FDIR) Command Line
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
3
Facing the Challenge of ISHM Design
• Early influence on system design to guide choice of health management methods and technologies
– Eliminate/reduce likelihood of failure by design through part selection and built-in redundancy – Prognosis in conjunction with preventative maintenance – Fault management with diagnosis and recovery technologies
• •
Failure modes & effects analysis activities for ISHM
– Feed fault information into the design process to create simulations of faults and improved designs to deal with faults
The initial design must be examined in the context of the full system life cycle
– Include all stakeholders (ops, maintenance, etc.) in the design – Solution optimized in terms of well-defined Figures of Merit (FOMs)
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
4
The current state of ISHM Design
• Insufficient interaction during the design process between failure analysis activities and design processes to prevent or mitigate these failures Limited interaction between reliability analyses and design processes Little interaction between operational training simulations and assessments of operational dependability and design process Operations and maintenance costs and risks become much larger than initially projected during Phase A initial design No formal tools and methodologies to allow program managers and engineering designers to formulate a clear understanding of the impact of the decisions on the downstream phases such as operations and maintenance on the systems design, and vice versa
• • • •
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
5
ISHM Design Goal
“DESIGN IN” THE ISHM CAPABILITY FROM THE BEGINNING! • Good news: Current interest is strong!
– First international forum on Integrated Systems Health Engineering and Management held in November – CEV/CLV
• •
Bad news: We lack methodologies & tools to achieve this! Some successful attempts
– Requirements: Specify ISHM “shall” statements at beginning of project • Joint Strike Fighter (5% of requirements are HM related) • Boeing 777 • CEV and CLV (planned) – Trade Studies: Integrate ISHM design with system-level design and do trade studies with ISHM as a design attribute • Northrop/NASA ARC SA&O effort for 2nd Gen RLV program • Honeywell/QSI SA&O and modeling effort – Integrate operations and maintenance considerations into design: • Boeing 777
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
6
The ISHM Design Paradigm:
Changing the Way ISHM Design is Done
ISHM
Risk lists, Failure Modes Reliability Models Sensor selection Maintainability Feature selection Testability
FUNCTIONAL MODELS
Functional Requirements Qualitative Analysis Risk Analysis Functional FMEA
PRA/QRA FTA/ETA FMEA
Advanced Studies
Preliminary Analysis
Definition
Design
Development
Operations
Proposed Design Paradigm Shift #1: Integrate ISHM design into very early
functional design stage (including failure and reliability analyses)
Feasible Concepts
Feasible Concepts
Functional Baseline
Build
Deploy
Proposed Design Paradigm Shift #2: Assess impact/tradeoffs of ISHM Figures
of Merit (FOMs) on system level FOMs from all stakeholders throughout mission lifecycle
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 7
Key Challenges for Paradigm Shift
• Embedding ISHM design into early functional design requires high-level modeling and analyses
– Models of system components and design parameters are not yet available – Integrating health management for complex systems requires capability to model functionality of individual subsystems as well as their interactions
•
Conducting failure, reliability and risk analyses during functional design stage
– Need mathematical techniques for risk assessment and resource allocation under uncertainty must be incorporated with high-level analyses
•
Design of ISHM is multidisciplinary and multi-objective by nature
– Need mathematical framework to achieve effective analysis & optimization – Designing an ISHM that encompasses all subsystems of a space mission is the result of interaction among engineers and managers from different disciplines with their own domain expertise
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
8
Candidate Design Methods
• Risk and Reliability Based Design Methods
– PRA, FTA, FMEA/FMECA, reliability block diagrams, event sequence diagrams, safety factors, knowledge-based methods, expert elicitation
• Design for Testability Methods • Formal design theory and methodology
– Function-based design and modeling – Mathematical techniques:
• Uncertainty modeling, decision-based design, risk-based design, design optimization, etc.
– Design for X methodologies
• Design for ISHM, Design for maintainability, Design for failure prevention, …
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
9
CSDE group R&D efforts
• Function-based modeling and failure analysis • Risk assessment by portfolio management and optimization • Multi-objective and multi-disciplinary system analysis & optimization
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
10
Function-Based Design, Modeling & Failure Modes Analysis for ISHM Design
• • Develop “functional model” of vehicle and ISHM subsystems Standardized representation enables retrieval of design knowledge based on common functionality
• •
Correlate historical and potential failure modes with functionality Functional model as living document during system lifecycle from design through operations
NASA RMC VI 6-8 December 2005 11
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
The ISHM System Functional Blueprint
Ex: Design of the ADAPT testbed at NASA ARC • Used to discover interfaces and interactions between functions • Used to add required functionality for ISHM (detect, sense, activate, etc.) • Used to discover functional failures and add safeguards
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
12
Function-Based Failure Modes Analysis
Project, SoS Project ISS Spacecraft Thermal PVATCS PVR Flex Hose PFCS Check Valve Temp Sensor Cable Shield Cold Plate Propulsion Power SSU DC-DC Conv. Lead Capacitor PVCE Capacitor LDI Diode 8-String CCAs Elec. Wire SAW DCSU Power Supply Diode Capacitor Component Controller electric wire Board diode Vacuum Seal lead capacitor Elec.Wire capacitor Heat Fin
E.E. (secondary voltage from aternate power channel) Control/Data Import E.E. E.E. Failed Components DC-DC Converter Voltage Import Control Actuate Control Control/Data Guide E.E. CCA (circuit card assembly Condition LDI Current, Voltage Primary Power Return E.E. (SAW strings 1 and 2) E.E. (SAW strings 3 and 4) E.E. (SAW strings 5 through 82) Import E.E. Guide E.E. PVCE Import E.E. Guide E.E. Measure E.E. Mix E.E. Regulate E.E. Distribute E.E. Measure E.E. Mix E.E. Guide E.E. Export E.E. E.E. (SAW)
System
SubSystem
Assembly
SubAssembly
Component
Component 2
• Developing templates for functional models
• Generating database of functions for S/C • Mining Failure Databases • Developing a Software Query Interface
Sequential Shunt Unit (SSU)
Shunt/Unshunt Import E.E. Guide E.E. Measure E.E. Current E.E. (Primary Power Bus)
..........
............
..........
Measure E.E.
Guide E.E.
Export E.E.
Components in colored boxes have failures identified from reports
Subfunction Guide Guide/Stop Guide Store/Supply Store/Supply Flow electrical electrical electrical electrical electrical Sub-assembly 8-String CCAs LDI DC-DC Converter DC-DC Converter PVCE
SSU Failures
Failure Mode Arc Discharge
Primary Identifier RPCM Breakdown Breakdown RBI Abrasive Wear Wear Arc Discharge BreakdownBaseplate Electrical Overstress Overstress
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
13
FFMEA Design Interface (w/ UMR)
Resource allocation to minimize risks due to functional failures
• Use of formal risk-based design and optimization techniques for ISHM risk assessment
– Risk-informed trade study framework to account for risk & uncertainty in early design: RUBIC design – Framework for quantifying risk due functional failures and allocating resources for risk reduction during concurrent design – Starting from the functional model, RUBIC optimally allocates resources to mitigate risks due to functional failures • Ex of resources: hours spent on analysis, redesign, dollars allocated, acquiring more reliable components, adding redundancy, etc.
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
15
Resource Reallocation to Minimize Risk and Uncertainty due Functional Failures
Column # 1st 2nd 3rd 4th 5th 6th 7th 8th 2nd 3rd
Subsystem Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller Motor Controller
Function Import Electrical Energy Export Electrical Energy Guide Electrical Energy Regulate Electrical Energy Guide Electrical Energy Condition Electrical Energy Guide Electrical Energy Convert Electrical E. to Rotational E. Convert Rotational E. to Electrical E. Export Thermal Energy
Resource Allocation <<1% 4% <<1% 36% 6% 17% <<1% 9% 13% 10%
Total Allocation to Controller Subsystem: 64%
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
16
RUBIC Prototype Development
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
17
System Analysis & Optimization (SA&O)
• SA&O Framework (based on prior work done for 2nd Gen RLV)
– Select a set of Figures-of-Merit – Select a set of models---such as cost, safety, operations, reliability, false alarm rates and maintainability---that generate FOMs – Determine the tools to implement the models – Determine the data flow requirements between the models Mass Risk – Perform trade studies
Power
•
Current Enhancements:
– – – –
Schedule Cost
Multi-objective & multi-disciplinary optimization Performance Data flow/exchange environment (implemented in Model Center) Automation for rapid trade analyses Ability to feed back into functional design stage:
• Add new functionality to enable ISHM to operate as an integrated system? • Change functionality to enable maintainability, performance, reduce risk?
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 18
ISHM System Analysis & Optimization
Model center implementation
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
19
Multi-Disciplinary, Multi-Objective Optimization for ISHM Design
• ISHM design can be formulated as an optimization problem
– ISHM Design Variables – ISHM Objectives (Figures of Merit) – ISHM Design Constraints: Feasibility Constraints + Hard Requirements
•
Multi-objectives/constraints in each sub-system
– Functionally separable Fi,j and exclusive fj – S Metric to encourage convergence; H Metric to encourage diversity
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
20
Summary & Conclusions
• • • ISHM is a key enabler for exploration systems Towards ISHM as a systems engineering discipline and co-design with vehicle systems Complex System Design & Engineering Group Research
– – – – Function based failure modes analysis Risk and uncertainty based design ISHM system analysis and optimization (SA&O) Current Involvement:
• CEV, CLV for Constellation/ESMD • IVHM and Aging Aircraft for Aviation Safety/ARMD
An ISHM design paradigm shift is required for a successful and sustainable exploration endeavor
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC NASA RMC VI 6-8 December 2005 21
Questions, Comments, Suggestions
Complex Systems Design & Engineering Group
Intelligent Systems Division, NASA ARC
Francesca Barrientos
[email protected]
Irem Tumer, Group lead
[email protected]
Complex Systems Design & Engineering Group Intelligent Systems Division, NASA ARC
NASA RMC VI 6-8 December 2005
22
doc_251542959.pdf