SlideShare ist ein Scribd-Unternehmen logo
1 von 24
NASA PM Challenge 2011




Product Data & Lifecycle
Management (PDLM) --
Project Management Implications


                  Paul Gill
                  NASA Marshall Space Flight Center, Huntsville, AL
                  Paul.gill@nasa.gov

                  Lisa Murphy
                  Atura Integration, Huntsville, AL
                  Lisa.d.murphy@gmail.com
Goals
• NASA space flight programs and projects are now expected to plan for
  Product Data and Lifecycle Management (PDLM).
• PMs will understand more about
   • what PDLM is,
   • why they are being asked to address it,
   • how to exploit it, and
   • where to go for information and support.
• Give two ConOps: IFA and DDT&E
   • Use actual experience from CxP to illustrate challenges

[Content below to be addressed after rest of presentation is done.]
• While no PM wants to pay more than needed for manufacturing, the likelihood that proactive
   management of product definition data can avoid the cost, time, and risk of recreating data for
   analysis, modeling, simulation, training, dependent designs (e.g., GSE), and facilities modifications
   may provide a more cogent motivation to exploit PDLM.
• Finally, we will review the current state of PDLM services at NASA and identify how PMs, lead
   engineers, designers, systems engineers, and procurement personnel can go about finding the
   support they need.
Concept of Operation 1:
Generic In-Flight Anomaly (IFA)
• 10 years ago we developed a Flag Ship Class spacecraft.
• Nearing the end of a very long cruise mode, the
  vehicle must be configured for planetaryarrival
   While coming out of cruise, a critical
   component experiences an operational anomaly.
• Mission team has 12 hours to fix the problem
  prior to entering into orbit or the mission will be lost.
  Built-in monitoring system on the central electronics unit indicates a
  device on the processor card is not functioning properly.
The Question at hand: What data will be needed, and how do
we plan for it a decade or more beforehand?
IFA Data Needs <4 hrs: Partial List
• As-designed/as-purchased/as-tested/as-built/as-flown
  product structure and definition
• Circuit card schematic
• Specifications (e.g., materials, acceptance testing)
•   Where (else) used
•   Location and status of spares
•   Firmware, software, parameters
•   Circuit card testing and failure history
• Impact analysis of failure (e.g., FMEA)
• Failure history of components in similar settings
• History of component/card/sub-system behavior over
  course of mission
• Trades/Design Rationale
IFA Support Requires Multiple Streams
Only one stream is Product Data
                                                           Part/assy object                                   Data from ADP for
                                                             on current                                          this specific
                                                            mission (“as                                        object on this
                                                                flown”                                               flight
             Part/Assembly                                                    Part/Assembly
                 Object                                                           Object
                                                                                (As-flown)




                                                       Assembly &
                                                                                                        DDT&E data
                                                      Verification –
               Mission                                                                                    for this
                                                      this instance
               Vehicle                                                                                    design
               Instance
                                                                                 ADP
                                                                                Object |
                                                                               Description
 System or                        Communication
  Function                          & Control
                                                                                                                      Design and
                                                                                                                     analysis data
                                                                                                  Other               for design
                                                                                               instances                history
                                                               Fabrication
                                                                    &                          (e.g., prior
                                                               Procurement                     Deliveries
                                                                                                or flights)


                                                                                                                    Data about
                                                                                                                       other
                             Data from handling or                                Delivered data                   instances of
                             operations conducted                                 from site that                   this part and
                             after DD250, e.g., VAB                               manufactured                    experience on
                                  PRACA items                                      this specific                  other missions
                                                                                        part
IFA ConOpConsiderations
• Data created by different groups at different
  physical locations, at different times, in different
  formats, and for other purposes
    And, it’s ten years later
• Need a small, particular subset of all data about this
  part – and need it in context
      From different contractors, different centers
      From different points in a long development cycle
      From communities with different vocabularies
      From tools now superseded by later versions
   How many IFA scenarios does your Project have?
Q: What is 13 GB?
A: The amount of memory required to open the top-level 3D
   CAD model of the Crew Module (only) at Orion’s Preliminary
   Design Review (PDR)




Here’s a hint
ConOp 2: Development Data Deluge
• Before we have an IFA, have to get through DDT&E
• We are seeing some very large amounts of data created
  during Design & Testing alone
          Scale of product, types of analysis & testing, procurement
           strategy all affect this – but no one is immune
• Illustrative Cases from CxP
          Core Input for Analysis: OML
          Analysis, Testing & Simulation Deluge
          Sample Documents & CAD Models: Ares & Orion at PDR

Documents: Ares 1 PDR reviewed ~500 documents and two drawings
   With ~38,000 documents in Ares Windchill Project Folders
CAD: 16 months later at Orion PDR, LMSSC delivered ~11,000 discrete 3D models for
Service Module, Crew Module, Launch Abort System
    LMSSC had ~250,000 versions, iterations, or variants in their Windchill vault
ConOp 2: DDT&E
Reviews
    Data does nothing but grow over phases
Integrated Stack OML
    Challenging to integrate CAD models from different
     suppliers
    Designs at different maturities
    Not a design object; uses pre-release models
    Requires special CAD settings and practices
Analysis, Testing & Simulation
    Volumes of data created for and used for analysis,
     verification, and testing
DDT&E: Ares/Orion OML
    MSFC Ares Vehicle Integration responsible for
    integrated stack OML 3D CAD envelope model
        • in Low-, Medium-, and High-Fidelity versions for each
          Design Analysis Cycle (DAC)
    Proliferation of demand for OML or data from
    OMLfor other design & analysis uses, including:
    J2 LH2 blade ejection cone                             Sensor locations
    Acoustic wind tunnel 4% model                          GNC node points
    Clearance analysis simulation                          Inboard profile
    IU/SA compartment for Human Factors                    IS-gimbal
    Protuberance dimensions                                Thrust oscillation models
    Fairing panel separation dynamic                       RoCs nozzle placement
    Re-entry configuration for US                          Antenna locations


Source: list of requested models or data from OML CAD models in DAC 2 for Ares 1.
Ares1 OML Data Exchange:
    Multiple Sources & Heavily Manual
 LM                                                   Upper
                           Orion                                             Boeing
 SSC                                                  Stage
                                       Ares Vehicle
                                       Integration
                                        (@MSFC)
         JSC DDMS
                                                                                ATK
                                                      First
                       ESMD ICE                       Stage
                     Project Folders



                                                                        MSFC DDMS

         CxP LvlII
        DIO (@ JSC)
                                                      Ground              KSC DDMS
Design                                                Ops KSC
Interactions
 Manual Processing                                            Source: CxP CAD WG May 2009
More Things to Do With CAD Models
    •   3D prototyping
    •   Verify/analyze design for requirements or standards compliance
    •   Conduct “-ilities” analyses
    •   Create motion models (oscillation, rotation)
    •   Create time-based visualizations (e.g., of assembly processes)
    •   Use in models and simulations (e.g., VRML)
    •   Plan verifications & validations; prepare before & after comparisons
    •   View, manipulate, annotate, mark-up, e.g., for TIMs, Reviews
         • Mass properties: mass, CG, surface area, volume, Parts lists, used-on
    • Produce illustrations, “viewables” or other representations
         • Communications, Public Affairs, General Information
         • Training & Procedures, Documents, & Manuals
•       ICDskeleton models                        •   Dynamics models
•       Flat pattern for sheet metal parts        •   Pipe Assembly Models
•       Bulk items, (e.g. Spray-on Insulation,    •   Harness subassembly models   12
        Propellant                                •   Layout models
•       Deployed models                           •   Mass properties models
A Taste: Analysis & Testing
• LMSSC test plans included telemetry ranging from
  5 MB/sec (slow) to 20 MB/sec (fast) per channel
• Engineering Task Description Sheets (from CAIT) show
  dependencies on 507 different data packages
• Ares initiated a risk that they would not have enough
  storage for the testing data expected
  • [&&&CHECK NOTES RE SIZE OF STORAGE]
• And there would be much, much, more:
  • Imagery
  • Simulation data sets (inputs/outputs), simulation testing
    set-up/configurations
  • Assembly, Installation, & Interference checking
Why Product Data & Lifecycle
Management?
Because we need to answer questions such as:
1. How much should we risk (conversely, how much are
   we willing to pay) to ensure the relevant data exist and
   are accessible, discoverable, and understandable to
   support an IFA?
2. Where should we invest our attention and resources to
   manage data during development?
    a. What data do we need from our contractors?
    b. In what formats do different users need the data?

These concerns led to changes to NPD 7120.4 to include Product
Data and Lifecycle Management, and development of
PDLM NPR.
What’s Happened:

In 2008, Office of Chief Engineer takes lead on PDLM
1. In 2009, updated to NPD 7120.4 to include PDLM
2. Started working on PDLM NPR (approved 1/2011)
3. Interoperability work (CAD, model exchanges)
4. PDLM Steering Committee formed
Definition….
• Product Data Management (PDM). A framework that enables
  organizations to manage and control engineering and
  technical information, specifically data surrounding the
  product's design, definition, and related engineering, test,
  manufacturing, and logistics processes and is a key element of
  PLM…

• Product Life-cycle Management (PLM). The process of
  managing the entire life cycle of a product from its
  conception, through design and manufacture, to service and
  disposal. PLM integrates people, data, processes, and
  business systems and provides a product information
  backbone for companies and their extended enterprise…
Scope & Coverage
• Single Project & Tightly Coupled Space Flight Programs
• Entire lifecycle for all types of product-related data
  • [See NPR}
Recent experience has shown:
  • 3D CAD powerful, but requires special attention
      • Cannot wait until ADP to get models if you have insight-oversight
      • Collaborative design requires robust, frequent data exchange
  • Requiring same version, build of same tool not sufficient
      • Must look at who is doing what
      • Ask who needs it, why and when
  • Data exchange standards lag industry practice
      • So far, proprietary models only sure why to get all of data
  • Need to consider software along with hardware in product
    definition
PDLM NPR Summary (a)
Projects & Programs
Responsible for Process and Data Architecture
Write a Plan and update often
  • Authoritative data are identified, captured, cataloged
  • Agile, flexible, sound practices for data management
  • Critical product data receives timely attention to acquire what is
    needed, assure integrity, reflect maturity state(s) and authority
  • Know who needs what, when, format – across lifecycle
• MDAA is responsible for seeing the PMs meet requirements
PDLM NPR Summary (b)
Information Systems/Infrastructure (OCIO, Center Director)
Assure that infrastructure adequate
  • Seek to effectively re-use solutions to common problems, improve
    performance
Tools are known and providers committed to support
Security has received due attention

Project Manager – not center– is responsible for producing plan,
building commitments
  • Work with Center or other providers to come to agreement on what
    services, for whom, and how
 Continues for now distributed PDM/PLM tool model
   • No one group assigned to provide agency-wide PDLM
Practical Matters: Plans, Tools & Data
Acquisition
Content of PDLM Plan overlaps traditional Project plans
such as CM, DM, Records Management, SEMP,
program/project plans
  • Multiple uses of same applications/similar data
  • Must initiate plan early and then update regularly
  • Identify needs, project future needs, coordinate with IT supplier
Data acquisition is critical to PDLM
  • Challenging to write DRDs that support CAD data exchange
  • Need to consider the data needed during design and IV&V
  • Also what is at physical delivery of product, engineering changes
Few NASA personnel have hands-on experience with the
new data-centric, model-centric, technology direction
Generally, NASA Projects Face:
Distributed Production & Use over an Extended Lifecycle
• Need to exchange and use PRE-RELEASE product data
• Mixture of internal and external sources – Centers, primes,
  partners, universities
• High analysis demands, high
  volumes of ancillary data
• Long project life cycles
• Need for IFA reach-back
• Ten independent Centers
  with local solutions
• NASA cannot dictate
  how things are done
  at primes
Rockets as Products
Different Specifications Needed
to Get Data for Different Needs
• Do derivative designs such as
   tooling, test stands
• Sub-contract part of design
   work
• Do design integrations
• Conduct design review
• Take over design change
   authority
• Do modeling and simulations
• Do physical integration &
   verification (e.g., at test site
   or VAB)
• Re-bid production
More Reasons to Care
    • 2D drawings from NASA’s standard CAD tool (PTC Pro/Engineer
      Wildfire) are made from 3D models
    • To integrate the design of the 787 Dreamliner from their four design
      groups, Boeing
      • Had 16 Terabytes of data in their master repository
      • Packaged and delivered quarterly 150 applications for the distributed
        design teams to use
    • Some of the 24 different extensions to CAD models identified by
      MSFC CAD standard (only some of which are released):
•    Interface Control Document (ICD) skeleton   •   Deployed models
     models                                      •   Dynamics models
•    Envelope part models(e.g., OML)             •   Pipe Assembly Models
•    Flat pattern for sheet metal parts          •   Harness subassembly models
•    Bulk items, (e.g. Spray-on Insulation,      •   Layout models
     Propellant                                  •   Mass properties models
•    Generic of family table part instance
Questions?

Weitere ähnliche Inhalte

Ähnlich wie Gill.paul

Accel Partners New Data Workshop 7-14-10
Accel Partners New Data Workshop 7-14-10Accel Partners New Data Workshop 7-14-10
Accel Partners New Data Workshop 7-14-10
keirdo1
 
Oracle+cloud+computing+ +iasa+thailand+2011
Oracle+cloud+computing+ +iasa+thailand+2011Oracle+cloud+computing+ +iasa+thailand+2011
Oracle+cloud+computing+ +iasa+thailand+2011
Software Park Thailand
 
Ruszkowski.james
Ruszkowski.jamesRuszkowski.james
Ruszkowski.james
NASAPMC
 
Next-Generation Asset Tracking
Next-Generation Asset TrackingNext-Generation Asset Tracking
Next-Generation Asset Tracking
tracksoftware
 
Dc architecture for_cloud
Dc architecture for_cloudDc architecture for_cloud
Dc architecture for_cloud
Alain Geenrits
 
Cost Analysis In IT - HES08
Cost Analysis In IT - HES08Cost Analysis In IT - HES08
Cost Analysis In IT - HES08
Thomas Danford
 

Ähnlich wie Gill.paul (20)

Firstcomm construction of a DR plan
Firstcomm construction of a DR planFirstcomm construction of a DR plan
Firstcomm construction of a DR plan
 
Firstcomm construction of a DR plan
Firstcomm construction of a DR planFirstcomm construction of a DR plan
Firstcomm construction of a DR plan
 
Accel Partners New Data Workshop 7-14-10
Accel Partners New Data Workshop 7-14-10Accel Partners New Data Workshop 7-14-10
Accel Partners New Data Workshop 7-14-10
 
Collaborate 2012 - the never ending road of project management presentation c...
Collaborate 2012 - the never ending road of project management presentation c...Collaborate 2012 - the never ending road of project management presentation c...
Collaborate 2012 - the never ending road of project management presentation c...
 
Partitioning CCGrid 2012
Partitioning CCGrid 2012Partitioning CCGrid 2012
Partitioning CCGrid 2012
 
Construction of a Disaster Recovery Plan with Business Only Broadband
Construction of a Disaster Recovery Plan with Business Only BroadbandConstruction of a Disaster Recovery Plan with Business Only Broadband
Construction of a Disaster Recovery Plan with Business Only Broadband
 
Oracle+cloud+computing+ +iasa+thailand+2011
Oracle+cloud+computing+ +iasa+thailand+2011Oracle+cloud+computing+ +iasa+thailand+2011
Oracle+cloud+computing+ +iasa+thailand+2011
 
Enterprise Master Data Architecture
Enterprise Master Data ArchitectureEnterprise Master Data Architecture
Enterprise Master Data Architecture
 
Ruszkowski.james
Ruszkowski.jamesRuszkowski.james
Ruszkowski.james
 
Auto-Scaling to Minimize Cost and Meet Application Deadlines in Cloud Workflows
Auto-Scaling to Minimize Cost and Meet Application Deadlines in Cloud WorkflowsAuto-Scaling to Minimize Cost and Meet Application Deadlines in Cloud Workflows
Auto-Scaling to Minimize Cost and Meet Application Deadlines in Cloud Workflows
 
04.egovFrame Runtime Environment Workshop
04.egovFrame Runtime Environment Workshop04.egovFrame Runtime Environment Workshop
04.egovFrame Runtime Environment Workshop
 
Interfacing In Form To Argus Safety
Interfacing In Form To Argus SafetyInterfacing In Form To Argus Safety
Interfacing In Form To Argus Safety
 
Next-Generation Asset Tracking
Next-Generation Asset TrackingNext-Generation Asset Tracking
Next-Generation Asset Tracking
 
202201 AWS Black Belt Online Seminar Apache Spark Performnace Tuning for AWS ...
202201 AWS Black Belt Online Seminar Apache Spark Performnace Tuning for AWS ...202201 AWS Black Belt Online Seminar Apache Spark Performnace Tuning for AWS ...
202201 AWS Black Belt Online Seminar Apache Spark Performnace Tuning for AWS ...
 
Dc architecture for_cloud
Dc architecture for_cloudDc architecture for_cloud
Dc architecture for_cloud
 
Aps ScanView
Aps ScanViewAps ScanView
Aps ScanView
 
The DURAARK Workbench and PREMIS
The DURAARK Workbench and PREMISThe DURAARK Workbench and PREMIS
The DURAARK Workbench and PREMIS
 
Cost Analysis In IT - HES08
Cost Analysis In IT - HES08Cost Analysis In IT - HES08
Cost Analysis In IT - HES08
 
About The Event-Driven Data Layer & Adobe Analytics
About The Event-Driven Data Layer & Adobe AnalyticsAbout The Event-Driven Data Layer & Adobe Analytics
About The Event-Driven Data Layer & Adobe Analytics
 
Windows Azure Scalability
Windows Azure ScalabilityWindows Azure Scalability
Windows Azure Scalability
 

Mehr von NASAPMC

Bejmuk bo
Bejmuk boBejmuk bo
Bejmuk bo
NASAPMC
 
Baniszewski john
Baniszewski johnBaniszewski john
Baniszewski john
NASAPMC
 
Yew manson
Yew mansonYew manson
Yew manson
NASAPMC
 
Wood frank
Wood frankWood frank
Wood frank
NASAPMC
 
Wood frank
Wood frankWood frank
Wood frank
NASAPMC
 
Wessen randi (cd)
Wessen randi (cd)Wessen randi (cd)
Wessen randi (cd)
NASAPMC
 
Vellinga joe
Vellinga joeVellinga joe
Vellinga joe
NASAPMC
 
Trahan stuart
Trahan stuartTrahan stuart
Trahan stuart
NASAPMC
 
Stock gahm
Stock gahmStock gahm
Stock gahm
NASAPMC
 
Snow lee
Snow leeSnow lee
Snow lee
NASAPMC
 
Smalley sandra
Smalley sandraSmalley sandra
Smalley sandra
NASAPMC
 
Seftas krage
Seftas krageSeftas krage
Seftas krage
NASAPMC
 
Sampietro marco
Sampietro marcoSampietro marco
Sampietro marco
NASAPMC
 
Rudolphi mike
Rudolphi mikeRudolphi mike
Rudolphi mike
NASAPMC
 
Roberts karlene
Roberts karleneRoberts karlene
Roberts karlene
NASAPMC
 
Rackley mike
Rackley mikeRackley mike
Rackley mike
NASAPMC
 
Paradis william
Paradis williamParadis william
Paradis william
NASAPMC
 
Osterkamp jeff
Osterkamp jeffOsterkamp jeff
Osterkamp jeff
NASAPMC
 
O'keefe william
O'keefe williamO'keefe william
O'keefe william
NASAPMC
 
Muller ralf
Muller ralfMuller ralf
Muller ralf
NASAPMC
 

Mehr von NASAPMC (20)

Bejmuk bo
Bejmuk boBejmuk bo
Bejmuk bo
 
Baniszewski john
Baniszewski johnBaniszewski john
Baniszewski john
 
Yew manson
Yew mansonYew manson
Yew manson
 
Wood frank
Wood frankWood frank
Wood frank
 
Wood frank
Wood frankWood frank
Wood frank
 
Wessen randi (cd)
Wessen randi (cd)Wessen randi (cd)
Wessen randi (cd)
 
Vellinga joe
Vellinga joeVellinga joe
Vellinga joe
 
Trahan stuart
Trahan stuartTrahan stuart
Trahan stuart
 
Stock gahm
Stock gahmStock gahm
Stock gahm
 
Snow lee
Snow leeSnow lee
Snow lee
 
Smalley sandra
Smalley sandraSmalley sandra
Smalley sandra
 
Seftas krage
Seftas krageSeftas krage
Seftas krage
 
Sampietro marco
Sampietro marcoSampietro marco
Sampietro marco
 
Rudolphi mike
Rudolphi mikeRudolphi mike
Rudolphi mike
 
Roberts karlene
Roberts karleneRoberts karlene
Roberts karlene
 
Rackley mike
Rackley mikeRackley mike
Rackley mike
 
Paradis william
Paradis williamParadis william
Paradis william
 
Osterkamp jeff
Osterkamp jeffOsterkamp jeff
Osterkamp jeff
 
O'keefe william
O'keefe williamO'keefe william
O'keefe william
 
Muller ralf
Muller ralfMuller ralf
Muller ralf
 

Kürzlich hochgeladen

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
Earley Information Science
 

Kürzlich hochgeladen (20)

Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 

Gill.paul

  • 1. NASA PM Challenge 2011 Product Data & Lifecycle Management (PDLM) -- Project Management Implications Paul Gill NASA Marshall Space Flight Center, Huntsville, AL Paul.gill@nasa.gov Lisa Murphy Atura Integration, Huntsville, AL Lisa.d.murphy@gmail.com
  • 2. Goals • NASA space flight programs and projects are now expected to plan for Product Data and Lifecycle Management (PDLM). • PMs will understand more about • what PDLM is, • why they are being asked to address it, • how to exploit it, and • where to go for information and support. • Give two ConOps: IFA and DDT&E • Use actual experience from CxP to illustrate challenges [Content below to be addressed after rest of presentation is done.] • While no PM wants to pay more than needed for manufacturing, the likelihood that proactive management of product definition data can avoid the cost, time, and risk of recreating data for analysis, modeling, simulation, training, dependent designs (e.g., GSE), and facilities modifications may provide a more cogent motivation to exploit PDLM. • Finally, we will review the current state of PDLM services at NASA and identify how PMs, lead engineers, designers, systems engineers, and procurement personnel can go about finding the support they need.
  • 3. Concept of Operation 1: Generic In-Flight Anomaly (IFA) • 10 years ago we developed a Flag Ship Class spacecraft. • Nearing the end of a very long cruise mode, the vehicle must be configured for planetaryarrival While coming out of cruise, a critical component experiences an operational anomaly. • Mission team has 12 hours to fix the problem prior to entering into orbit or the mission will be lost. Built-in monitoring system on the central electronics unit indicates a device on the processor card is not functioning properly. The Question at hand: What data will be needed, and how do we plan for it a decade or more beforehand?
  • 4. IFA Data Needs <4 hrs: Partial List • As-designed/as-purchased/as-tested/as-built/as-flown product structure and definition • Circuit card schematic • Specifications (e.g., materials, acceptance testing) • Where (else) used • Location and status of spares • Firmware, software, parameters • Circuit card testing and failure history • Impact analysis of failure (e.g., FMEA) • Failure history of components in similar settings • History of component/card/sub-system behavior over course of mission • Trades/Design Rationale
  • 5. IFA Support Requires Multiple Streams Only one stream is Product Data Part/assy object Data from ADP for on current this specific mission (“as object on this flown” flight Part/Assembly Part/Assembly Object Object (As-flown) Assembly & DDT&E data Verification – Mission for this this instance Vehicle design Instance ADP Object | Description System or Communication Function & Control Design and analysis data Other for design instances history Fabrication & (e.g., prior Procurement Deliveries or flights) Data about other Data from handling or Delivered data instances of operations conducted from site that this part and after DD250, e.g., VAB manufactured experience on PRACA items this specific other missions part
  • 6. IFA ConOpConsiderations • Data created by different groups at different physical locations, at different times, in different formats, and for other purposes  And, it’s ten years later • Need a small, particular subset of all data about this part – and need it in context  From different contractors, different centers  From different points in a long development cycle  From communities with different vocabularies  From tools now superseded by later versions How many IFA scenarios does your Project have?
  • 7. Q: What is 13 GB? A: The amount of memory required to open the top-level 3D CAD model of the Crew Module (only) at Orion’s Preliminary Design Review (PDR) Here’s a hint
  • 8. ConOp 2: Development Data Deluge • Before we have an IFA, have to get through DDT&E • We are seeing some very large amounts of data created during Design & Testing alone  Scale of product, types of analysis & testing, procurement strategy all affect this – but no one is immune • Illustrative Cases from CxP  Core Input for Analysis: OML  Analysis, Testing & Simulation Deluge  Sample Documents & CAD Models: Ares & Orion at PDR Documents: Ares 1 PDR reviewed ~500 documents and two drawings With ~38,000 documents in Ares Windchill Project Folders CAD: 16 months later at Orion PDR, LMSSC delivered ~11,000 discrete 3D models for Service Module, Crew Module, Launch Abort System LMSSC had ~250,000 versions, iterations, or variants in their Windchill vault
  • 9. ConOp 2: DDT&E Reviews  Data does nothing but grow over phases Integrated Stack OML  Challenging to integrate CAD models from different suppliers  Designs at different maturities  Not a design object; uses pre-release models  Requires special CAD settings and practices Analysis, Testing & Simulation  Volumes of data created for and used for analysis, verification, and testing
  • 10. DDT&E: Ares/Orion OML MSFC Ares Vehicle Integration responsible for integrated stack OML 3D CAD envelope model • in Low-, Medium-, and High-Fidelity versions for each Design Analysis Cycle (DAC) Proliferation of demand for OML or data from OMLfor other design & analysis uses, including: J2 LH2 blade ejection cone Sensor locations Acoustic wind tunnel 4% model GNC node points Clearance analysis simulation Inboard profile IU/SA compartment for Human Factors IS-gimbal Protuberance dimensions Thrust oscillation models Fairing panel separation dynamic RoCs nozzle placement Re-entry configuration for US Antenna locations Source: list of requested models or data from OML CAD models in DAC 2 for Ares 1.
  • 11. Ares1 OML Data Exchange: Multiple Sources & Heavily Manual LM Upper Orion Boeing SSC Stage Ares Vehicle Integration (@MSFC) JSC DDMS ATK First ESMD ICE Stage Project Folders MSFC DDMS CxP LvlII DIO (@ JSC) Ground KSC DDMS Design Ops KSC Interactions Manual Processing Source: CxP CAD WG May 2009
  • 12. More Things to Do With CAD Models • 3D prototyping • Verify/analyze design for requirements or standards compliance • Conduct “-ilities” analyses • Create motion models (oscillation, rotation) • Create time-based visualizations (e.g., of assembly processes) • Use in models and simulations (e.g., VRML) • Plan verifications & validations; prepare before & after comparisons • View, manipulate, annotate, mark-up, e.g., for TIMs, Reviews • Mass properties: mass, CG, surface area, volume, Parts lists, used-on • Produce illustrations, “viewables” or other representations • Communications, Public Affairs, General Information • Training & Procedures, Documents, & Manuals • ICDskeleton models • Dynamics models • Flat pattern for sheet metal parts • Pipe Assembly Models • Bulk items, (e.g. Spray-on Insulation, • Harness subassembly models 12 Propellant • Layout models • Deployed models • Mass properties models
  • 13. A Taste: Analysis & Testing • LMSSC test plans included telemetry ranging from 5 MB/sec (slow) to 20 MB/sec (fast) per channel • Engineering Task Description Sheets (from CAIT) show dependencies on 507 different data packages • Ares initiated a risk that they would not have enough storage for the testing data expected • [&&&CHECK NOTES RE SIZE OF STORAGE] • And there would be much, much, more: • Imagery • Simulation data sets (inputs/outputs), simulation testing set-up/configurations • Assembly, Installation, & Interference checking
  • 14. Why Product Data & Lifecycle Management? Because we need to answer questions such as: 1. How much should we risk (conversely, how much are we willing to pay) to ensure the relevant data exist and are accessible, discoverable, and understandable to support an IFA? 2. Where should we invest our attention and resources to manage data during development? a. What data do we need from our contractors? b. In what formats do different users need the data? These concerns led to changes to NPD 7120.4 to include Product Data and Lifecycle Management, and development of PDLM NPR.
  • 15. What’s Happened: In 2008, Office of Chief Engineer takes lead on PDLM 1. In 2009, updated to NPD 7120.4 to include PDLM 2. Started working on PDLM NPR (approved 1/2011) 3. Interoperability work (CAD, model exchanges) 4. PDLM Steering Committee formed
  • 16. Definition…. • Product Data Management (PDM). A framework that enables organizations to manage and control engineering and technical information, specifically data surrounding the product's design, definition, and related engineering, test, manufacturing, and logistics processes and is a key element of PLM… • Product Life-cycle Management (PLM). The process of managing the entire life cycle of a product from its conception, through design and manufacture, to service and disposal. PLM integrates people, data, processes, and business systems and provides a product information backbone for companies and their extended enterprise…
  • 17. Scope & Coverage • Single Project & Tightly Coupled Space Flight Programs • Entire lifecycle for all types of product-related data • [See NPR} Recent experience has shown: • 3D CAD powerful, but requires special attention • Cannot wait until ADP to get models if you have insight-oversight • Collaborative design requires robust, frequent data exchange • Requiring same version, build of same tool not sufficient • Must look at who is doing what • Ask who needs it, why and when • Data exchange standards lag industry practice • So far, proprietary models only sure why to get all of data • Need to consider software along with hardware in product definition
  • 18. PDLM NPR Summary (a) Projects & Programs Responsible for Process and Data Architecture Write a Plan and update often • Authoritative data are identified, captured, cataloged • Agile, flexible, sound practices for data management • Critical product data receives timely attention to acquire what is needed, assure integrity, reflect maturity state(s) and authority • Know who needs what, when, format – across lifecycle • MDAA is responsible for seeing the PMs meet requirements
  • 19. PDLM NPR Summary (b) Information Systems/Infrastructure (OCIO, Center Director) Assure that infrastructure adequate • Seek to effectively re-use solutions to common problems, improve performance Tools are known and providers committed to support Security has received due attention Project Manager – not center– is responsible for producing plan, building commitments • Work with Center or other providers to come to agreement on what services, for whom, and how Continues for now distributed PDM/PLM tool model • No one group assigned to provide agency-wide PDLM
  • 20. Practical Matters: Plans, Tools & Data Acquisition Content of PDLM Plan overlaps traditional Project plans such as CM, DM, Records Management, SEMP, program/project plans • Multiple uses of same applications/similar data • Must initiate plan early and then update regularly • Identify needs, project future needs, coordinate with IT supplier Data acquisition is critical to PDLM • Challenging to write DRDs that support CAD data exchange • Need to consider the data needed during design and IV&V • Also what is at physical delivery of product, engineering changes Few NASA personnel have hands-on experience with the new data-centric, model-centric, technology direction
  • 21. Generally, NASA Projects Face: Distributed Production & Use over an Extended Lifecycle • Need to exchange and use PRE-RELEASE product data • Mixture of internal and external sources – Centers, primes, partners, universities • High analysis demands, high volumes of ancillary data • Long project life cycles • Need for IFA reach-back • Ten independent Centers with local solutions • NASA cannot dictate how things are done at primes
  • 22. Rockets as Products Different Specifications Needed to Get Data for Different Needs • Do derivative designs such as tooling, test stands • Sub-contract part of design work • Do design integrations • Conduct design review • Take over design change authority • Do modeling and simulations • Do physical integration & verification (e.g., at test site or VAB) • Re-bid production
  • 23. More Reasons to Care • 2D drawings from NASA’s standard CAD tool (PTC Pro/Engineer Wildfire) are made from 3D models • To integrate the design of the 787 Dreamliner from their four design groups, Boeing • Had 16 Terabytes of data in their master repository • Packaged and delivered quarterly 150 applications for the distributed design teams to use • Some of the 24 different extensions to CAD models identified by MSFC CAD standard (only some of which are released): • Interface Control Document (ICD) skeleton • Deployed models models • Dynamics models • Envelope part models(e.g., OML) • Pipe Assembly Models • Flat pattern for sheet metal parts • Harness subassembly models • Bulk items, (e.g. Spray-on Insulation, • Layout models Propellant • Mass properties models • Generic of family table part instance

Hinweis der Redaktion

  1. This is actually a SIMPLIFIED version of a diagram created by the Constellation CAD Working Group in2009 which shows sources and destinations, media, and some of the processes for getting the data used to produce the Outer Mold Line (OML) for Ares 1. It is important to note that the CAD models are all 3D, and are needed PRE-RELEASE.The OML uses design definition inputs, but it is an analysis object created from designs with a range of maturity; shortly after Orion’s PDR, ATK began CDR for first stage, while the Mobile Launch Platform had been constructedWe recognize that most projects will not experience this much diversity, but the creation of complex assemblies in different versions formats needed for analysis, simulation, and other downstream uses will require more attention than you might be used to.