generative design: your ai partner in product development · generative design “integrated...
TRANSCRIPT
Generative Design:Your AI Partner in Product
Development
Date: Thursday, November 29, 2018
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Moderator: Kenneth WongSenior EditorDigital Engineering
Tony AbbeyColumnistFEA trainerConsultant
Keith MeintjesExecutive Consultant Simulation & AnalysisCIMdata
Carina MaurerProduct designer
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CARINA’S OPENING REMARKS
Carina MaurerProduct designer
RETAIL EXHIBITIONReuse of waste
Tool40 % decrease in weight
Parametric swingOrganic shapemade of surfaces
Ski gogglesReduction of wasteEasy to recycle
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TONY’S OPENING REMARKS
Tony AbbeyColumnistFEA trainerConsultant
TONY’S OPENING REMARKS
Traditional FEA structural simulation
Target – sign-off of existing design
Requirements – high accuracy
Occurs downstream
Generative Design using FEA
Target – explore radically new designs
Requirements – product improvement/innovation
Occurs upstream
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KEITH’S OPENING REMARKS
Keith MeintjesExecutive Consultant, Simulation and AnalysisCIMdata
CIMdata’s Mission
CIMdata is the leading independent global strategic management consulting and
research authority focused exclusively on PLM and the digital transformation it
enables.
We are dedicated to maximizing our clients' ability to design, deliver, and support
innovative products and services through the application of PLM.
Keith’s Opening Remarks
• Ideas for generative design were developed in the late 1980s
• Adoption was low, except in a few cases like gauge BIW optimization and essentially 2D structures like sheet metal and brackets
• Maturing of additive manufacturing has led to a resurgence of interest
• It is NOT simply that we can now manufacture parts we could not make before
Generative Design
“Integrated performance-driven generative design systems are aimed at creating new design processes that produce spatially novel yet
efficient and buildable designs through exploitation of current computing and
manufacturing capabilities.”
Prof. Dr. Kristina Shea (ETH Zurich)
K. Shea et al, “Towards integrated performance-driven generative design tools”, Automation in Construction 14 (2005) 253–264.
Traditional Design Process
Previous Designs(History)
Design Constraints
Performance Requirements
Design Space (Context)
Create Design (CAD)
Evaluate Design (CAE)
Issues
Valid Design
Design Iterations
Build
Generative Design Process
Previous Designs(History)
Design Constraints
Performance Requirements
Design Space (Context)
Topology Optimization
via CAE
Valid Design
Document Design (CAD)
Build
Generative Lives in a Sea of Others
Generative Design
Industry 4.0
1
2
3
4
AI and Machine Learning• Generative Design
• Advanced Materials
• Additive Manufacturing
• … alone or together will enable incredible innovation in years to come
• … aided by other process and IT technologies
Integrated in the Lifecycle Digital Thread
Requirements
PlanningConceptual
DesignProduct
Engineering Manufacturing Engineering
Simulation & Validation
Build and Produce
Sales & Distribution
Maintenance& Repair
Disposal & Recycling
Test & Quality
In-service Operation
PortfolioManagement
Information: Re-use
Re-purposeRe-mfg.Re-coverRe-cycleRe-tire
Alpha Go: AI and Machine Learning
• Go is an oriental game where tokens are placed on a grid• It is more complicated than chess• The best Go computer program could beat most players most of
the time• It “learned” from a data base of 100,000 games played by humans• Alphabet (Google) then built Alpha Go • It learned by playing against itself • It was given only the rules of the game• In a few days it could beat almost all players (and other computer
programs almost all of the time• ”By not using human data - by not using human expertise in any
fashion - we've actually removed the constraints of human knowledge.”
https://www.theverge.com/2017/10/18/16495548/deepmind-ai-go-alphago-zero-self-taught
Defining Generative Design
The Elbow Chair, designed in Autodesk Fusion 360. Image courtesy of Autodesk.
Generative Design Terms - 1
Parameter optimization
Dimensions as design variables
Shape changes
Formal optimization methods
Topology optimization
Design space defined
Topology changes
Heuristic optimization methods
Generative Design Terms - 2
Lightweighting
A wonderful all-embracing term!
Avoids implication of “the optimum”
Suggests a more robust engineering solution
But an understrength initial design – will add weight!!
WORKING WITH GENERATIVE DESIGN
Generative design with lattice structure in Frustum Generate. Image courtesy of Frustum.
Designers and optimization - 1
Is design space too tight?
Base could be wider …
Is design space too wide?
Parametric – too much search area…
Topology – redundant mesh to eliminate
Min Nom Max0.1 1.0 10.0
Designers and optimization - 2
Are these realistic loads and boundary conditions?
design space axial load bending load torsional load combined loads
Missing load cases – really bad news
Designers and optimization - 3
Are we asking the right questions?
The answer to life the universe and all that?
42 …
Are we asking too many questions?
Avoid becoming a one-person committee
With too many variables to handle …
Designers and optimization - 4
Second guess the solution – why this design?
Aim for a robust engineering solution
Not an unrealistic “optimum”
WHO IS IT FOR? HOW DOES IT WITH MANUFACTURING
Generative design with manufacturing constraint in Siemens NX. Image courtesy of Siemens PLM.
Who should use generative design?
Generative Design for all!
Play to your strengths in:
• Design
• Analysis
• Manufacturing
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Q&A
Tony AbbeyColumnistFEA trainer
Keith MeintjesExecutive Consultant, Simulation and AnalysisCIMdata
Carina MaurerProduct designer
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TONY’S CLOSING REMARKS
Tony AbbeyColumnistFEA trainer
Closing remarks
Structural analysis optimization in a renaissance at present
Topology Optimization - Generative Design
– rapid prototyping is the catalyst
exciting….
After languishing as a specialist analyst toolstructural optimization is now back in the mainstream
Traditional methods – sizing and shape
– tedious, difficult ….
Closing remarks
On my Christmas list
Realistic manufacturing simulation
Realistic stress constraints
Optimizing structural supports
Nonlinear response
Linking Topology and Parametric Optimization
Closing remarks
Tony Abbey contact details:
FEA Resource website
www.fetraining.net
www.linkedin.com/in/tonyabbey/
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CARINA’S CLOSING REMARKS
Carina MaurerProduct designer
Please submit your
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KEITH’S CLOSING REMARKS
Keith MeintjesExecutive Consultant, Simulation and AnalysisCIMdata
Thank you!
Moderator: Kenneth WongSenior EditorDigital Engineering
Tony AbbeyColumnistFEA [email protected]
Keith MeintjesExecutive Consultant, Simulation and [email protected]
Carina MaurerProduct [email protected]