There has been a great deal of work done in the area of Model-Based Definition (MBD), but now we are finally starting to apply these 4 scientific principles to this data:
- Set up a hypothesis
- Design an experiment
- Test a theory
- Publish the results for public consumption.
The National Institute for Standards and Technology (NIST) is doing just this, and will present the latest findings at the Collaboration and Interoperability Congress 2015 in Washington DC on October 29, 2015.
Registration and Agenda Info here: http://www.cimdata.com/en/education/plm-conferences/2015-plmrm-ad-cic/2015-plmrm-ad-cic-about-cic
Thomas Hedberg will present the results of the following NIST projects on October 29th in Washington DC.
Title: Enabling System-of-Systems PLM with Digital Thread Support from Design to Manufacturing, Inspection, and Beyond
- Developing data curation and observation methods using system-of-systems PLM
- Identifying methodology gaps through research at NIST
- Closing the gaps with applied scientific discovery
- Summarizing metrics, results, and information from NIST studies
- Supporting widespread industrial confidence and adoption of MBE
Achieving industry’s vision to deploy Model-Based Enterprise (MBE) requires the creation of a single “digital thread.” Under MBE, there exists a Model-Based Definition (MBD), created by Engineering, that downstream functions reuse to complete Model-Based Manufacturing and Model-Based Inspection activities. The combination of the model-based definition and manufacturing and inspection data defines a digital thread. The MBE would enable real-time design and analysis, collaborative process-flow development, automated artifact creation, and full-process traceability in a collaborative product-development environment. This requires data to be put into context fit for purpose; including such data from the product lifecycle in the context to make decisions is difficult. Different data in the product lifecycle is stored in different locations with different people using the data in different ways. This is an example of how the lifecycle is starving for information, but drowning in data. A solution is needed for decision support that links all the disparate systems of the lifecycle, cultivates information, and supports data discovery and observation.
This presentation will provide a briefing on work at NIST in developing data curation and observation methods using system-of-systems PLM in support of smart manufacturing. Methodology gaps and recommendations for solutions are presented. Lastly, a summary of metrics, results, and information from NIST studies to support widespread industrial confidence and adoption of MBE is discussed.
Thomas Hedberg, Jr., P.E. is a member of the Systems Engineering group in the Systems Integration Division (SID) of the Engineering Laboratory (EL) at the National Institute of Standards and Technology (NIST). Mr. Hedberg is the project co-leader of the NIST Digital Thread for Smart Manufacturing project, which is part of the NIST Smart Manufacturing Operations Planning and Control program. Mr. Hedberg is conducting research at NIST currently in the areas of digital-product design, smart manufacturing, and lifecycle engineering through in-depth studying and analysis of specific issues and specialty areas within the mechanical engineering discipline. Mr. Hedberg earned a Bachelor of Science in Aeronautical and Astronautical Engineering degree from Purdue University and a Master of Engineering Management degree with a concentration on Systems Engineering from Penn State University. Mr. Hedberg is also pursuing a PhD currently and is a licensed Professional Engineer (PE) in the State of Arizona and the State of Maryland.
The CIC will focus on the following topics with the theme of Enabling the Model-Based Enterprise (MBE)
TOPIC AREAS presented by real users of MBD or MBE:
- MBD/MBE Vision and Downstream Integration
- High-level strategic plans
- Long-term view of the future of a Model-Based Enterprise (MBE) in large projects
- Overview of Return on Investment (ROI) in integration of large systems such as: ships, aircraft, spacecraft, ground vehicles, robotic vehicles
- Digital thread
- AME (Advanced Manufacturing Enterprise)
- JDMTP (Joint Defense Manufacturing Technology Panel)
- Using MBD/MBE to support KBE (Knowledge Based Engineering)
- Future workforce that can handle the digital-only context
- How does MBD/MBE reduce and improve engineering changes?
- Downstream consumption of MBD, such as 3D Work Instructions, CAM processing of native or neutral files, automated tolerance analysis
- MBD (Model-Based Definition)
- 3D annotations and product definition methods
- Native and neutral representations
- Advanced manufacturing methods that require a 3D model, such as: 3D printing, complex geometry composite layups, complex surfaced CSN machining
- Methods for representing (software consumption) and presenting (human consumption) MBD within a particular toolset
- Verification and Validation (V&V) of 3D model data
- PMI and 3D annotation creation and interoperability
- Culture change strategies that support moving information from the drawing into MBD
- Translation & Data Validation of PMI and 3D Annotations
- Standards in MBD and MBE
- Standard Development work in support of Model-Based Enterprise (MBE) and Model-Based Definition (MBD)
- ASME Y14.41, Y14.41.1, Y14.46, Y14.47
- QIF (Quality Information Framework)
- STEP AP242 (ISO 10303)
- Quality and Inspection
- Representative (semantic or software consumable) 3D GD&T (Geometric Dimensioning and Tolerancing)
- Supporting technology and/or data transfer
- First Article Inspection (FAI)
- Inspection – As-Designed vs As-Built Validation
- Automated consumption of design and inspection MBD
- How can suppliers comply?
- Real World Implementation
- Pilot project and case study stories using MBD, and implementing MBE
- Metrics and evaluation criteria of MBD and MBE
- Industry projects in: Ship building, Pipeline systems, Automotive, Aircraft, Spacecraft, Agricultural, Vehicle Integration, Ground Systems, Electronics
- Supply Chain
- Challenges and/or success stories
- Technology gaps
- Communicating a new way of doing business
- Verification and Validation (V&V) of As-Designed to As-Built