June 7 th -9 th | Seattle, WA 2016 NAFEMS Americas Conference nafems.org/americas TOWARDS COGNITIVE COMPUTER AIDED ENGINEERING Stefan Suwelack 1 , Markus Stoll 2 , Annika Meyer 1 , Steffen Slavetinsky 1 , Manuel Serf 1 , Nikola Bursac 1 , Albert Albers 1 , Rolf Bendl 2 , Rüdiger Dillmann 1 and Stefanie Speidel 1 1 Karlsruhe Institute of Technology 2 German Cancer Research Center 1
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June 7th-9th | Seattle, WA2016 NAFEMS Americas Conferencenafems.org/americas
TOWARDS COGNITIVE
COMPUTER AIDED ENGINEERING
Stefan Suwelack1, Markus Stoll2, Annika Meyer1, Steffen Slavetinsky1, Manuel Serf1, Nikola Bursac1, Albert Albers1, Rolf Bendl2, Rüdiger Dillmann1 and Stefanie Speidel1
1Karlsruhe Institute of Technology2German Cancer Research Center
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June 7th-9th | Seattle, WA2016 NAFEMS Americas Conferencenafems.org/americas
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Surgeon
Cognitive
Surgical
Assistant
June 7th-9th | Seattle, WA2016 NAFEMS Americas Conferencenafems.org/americas
Knowledge Base
Factual Knowledge
Experience
Semantics
Data
describes
June 7th-9th | Seattle, WA2016 NAFEMS Americas Conferencenafems.org/americas
Cognitive Computing
• Deep Blue 1997
• DARPA Grand Challenge
2007
• Watson 2011
• AlphaGo 2016
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Cognitive Computing: Deep Learning
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“Two pizzas sitting on top of a stove top oven”
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Vision: Cognitive Simulation Assistant
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Challenges in CAE
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License Cost
SaaS
Hardware Cost CAE-Experience
CognitiveComputing
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CAD und CAE Today
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Design-
engineer
Numerical
analyst
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Cognitive CAE
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Design-
engineer
Cognitive
Simulation
Assistant
Numerical
analyst
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Simulation Apps I
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Simulation Apps II
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Generalized Cognitive Simulation App
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Model Factual CAE Knowledge
• Philosophie: Study basic categories of being
• Computer science: Knowledge representation
• Compatibility through shared
Upper Ontologies
• Well suited for
data integration
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Data ontology
What is represented by the
data?
• Information content entity
How is the data represented?
• Information structure entity
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Algorithm ontology
• Draws on existing standards,
e.g. OpenAPI model
• Based on data ontology
• Integrates different software
modules and services
• Alternative representation
by YAML/JSON
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Simulation ontology
• Representation of simulationknowledge
• Models, boundaryconditions, solvers…
• Based on existing work, e.g. HuPSON ontology, Step AP 209