Canada – Germany Industrial AI Solutions Matchmaking Event ... · Platforms and Services •...

Canada – Germany Industrial AI SolutionsMatchmaking Event – June 9, 2020

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Dr. Geneviève TanguayVice-President Emerging Technologies National Research Council Canada (NRC)

Mr. Ghislain RobichaudCounsellor Science and Technology, Global Affairs Canada, Embassy of Canada, Berlin

Dr. Rainer MüssnerDivision Cooperation with North and South America, German BMBF

National Research Council Canada – GermanyJennifer E. Decker

National Research Council Canada (NRC), Germany

• NRC is Government of Canada's largest federal R&D organization

Mandated to take research from the lab to the marketplace, where it can enhance people's lives and address some of the world's pressing challenges

NRC engages in multiple forms of collaboration and projects span a very broad spectrum of activities and industries

• NRC in Germany is a point of entry for researchers and businesses in Germany who are interested in R&D collaborations with the NRC, or with innovative Canadian companies

6NATIONAL RESEARCH COUNCIL CANADA

NRC Research Centres and Expertise

7NATIONAL RESEARCH COUNCIL CANADA

DIGITAL TECHNOLOGIES • Digital TechnologiesEMERGING TECHNOLOGIES • Advanced Electronics and Photonics

• Herzberg Astronomy and Astrophysics• Metrology • Nanotechnology• Security and Disruptive Technologies

ENGINEERING • Construction• Energy, Mining and Environment• Ocean, Coastal and River Engineering

LIFE SCIENCES • Aquatic and Crop Resource Development• Human Health Therapeutics• Medical Devices

TRANSPORTATION • AerospaceAND MANUFACTURING • Automotive and Surface Transportation

NRC Challenge and Supercluster Programs

• Challenge programso Artificial Intelligence for Designo High Throughput and Secure Networks for Remote/Northern communitieso Disruptive Technologies for Cell and Gene Therapieso Materials Discovery for Clean Fuelso Pandemic Responseo https://nrc.canada.ca/en/research-development/research-collaboration/programs/challenge-programs

• Supercluster Support programso Advanced Manufacturingo Canadian Digital Technology Supercluster Collaboration programo Sustainable Protein Productiono Oceano Artificial Intelligence for Logisticso https://nrc.canada.ca/en/research-development/research-collaboration/programs/supporting-canadas-

innovation-superclusters8NATIONAL RESEARCH COUNCIL CANADA

https://nrc.canada.ca/en/research-development/research-collaboration/programs/challenge-programs

https://nrc.canada.ca/en/research-development/research-collaboration/programs/supporting-canadas-innovation-superclusters

CONTACT DETAILS

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National Research Council Canada, GermanyJennifer E. DeckerEmail: [email protected]: +49 89 21 99 57 66

Listing of NRC Research Centres including areas of expertise and facilities:https://nrc.canada.ca/en/research-development/research-collaboration/research-centres

NRC Directory of science professionals:https://nrc.canada.ca/en/corporate/contact-us/nrc-directory-science-professionals

NRC Germanyhttps://nrc.canada.ca/en/research-development/nrc-facilities/national-research-council-canada-germany

NATIONAL RESEARCH COUNCIL CANADA

https://nrc.canada.ca/en/research-development/research-collaboration/research-centres

https://nrc.canada.ca/en/corporate/contact-us/nrc-directory-science-professionals

https://nrc.canada.ca/en/research-development/nrc-facilities/national-research-council-canada-germany

DLR ProjektträgerBarbara Hellebrandt, Senior Scientific Officer

Your reliable partner for research, education and innovation

Structure and Submission Process in Germany• German consortium• minimum one company, particularly small and medium-sized enterprise (SME) and

one university or non-university research institutions• More partners possible, also on a self-funded basis

• Two-step procedure• „Expression of Interest“ not relevant in German process• First step: project outline („Skizze“), submission deadline Sept. 11, language

German or English, max. 15 pages, plus International Consortium Project Proposal (provided by NRC)

• Evaluation of proposals in Germany and Canada, selection of proposals• Second step: submission of formal application for funding (AZA, AZAP, AZK), only

proposals that have been evaluated positively and selected for funding

• For further information please contact the project funding agency, contact: Barbara Hellebrandt and Claudia Gruner

DLR-PT | June 09, 2020

National Research Council Industrial Research Assistance Program (IRAP)Andrew BauderIndustrial Technology Advisor / National Program Coordinator for Germany

Industrial Research Assistance Program

• Canada’s leading innovation assistance program for SMEs• Accelerates growth of SMEs by providing

• Business and technical advisory services• Linkages• Financial assistance

• Delivered by highly experienced network of more than 250 Industrial Technology Advisors (ITAs) located across Canada

• International programs help connect Canadian SMEs to global value chains

• Collaborative funding programs• Partnership development activities

13NRC IRAP

Eligibility for Canadian SMEs

• Incorporated, for-profit SMEs located in Canada• Fewer than 500 employees• Objective to grow through innovation

• Projects should focus on developing innovative products, processes, or technology-based services

• Project should have high commercial potential• Project should have an obvious advantage and added value

resulting from the collaboration between the partners

14NRC IRAP

Canadian Consortia and Deadlines

• Canadian consortium must include• SME + research institution + NRC researcher

• Lead of Canadian consortia must register by July 3• Qualified registrations will receive an EOI form to be submitted

by July 10• Qualified EOI applicants will be invited to submit an International

Consortium Project Proposal (to be completed with German partners) by September 11

15NRC IRAP

CONTACT DETAILS

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Andrew BauderNational Research Council Industrial Research Assistance [email protected]

NRC IRAP

mailto:[email protected]

National Research Council National Program Office (NPO)Russell GirardChallenger Officer / National Program Office

Eligibility for Canadian Research Institutions

• Post-secondary institutions and research and technology organizations

• Collaborative research and development, prototype development intended to support research, development, adoption and/or adaptation of innovative or technology-driven new or improved products, services or processes

• NRC researchers must be performing work to support the advancement of NRC’s challenge programs or superclustersupport programs objectives

18NRC IRAP

https://nrc.canada.ca/en/research-development/research-collaboration/programs/challenge-programs

https://nrc.canada.ca/en/research-development/research-collaboration/programs/supporting-canadas-innovation-superclusters

CONTACT DETAILS

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Russell GirardNational Research Council National Program [email protected]

NRC IRAP


QUESTION & ANSWER SESSION

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NATIONAL RESEARCH COUNCIL RESEARCHES

GERMAN RESEARCH INSTITUTES

22

Fraunhofer Institute for Ceramic Technologies and Systems IKTSDr. Ulana Cikalova

COMPANY DESCRIPTION

24Fraunhofer Institute for Ceramic Technologies and Systems IKTS

Developments for NDT

Product identification and process tracking

Process control with ceramic luminescent materials.

Testing of CFRP and GFRP

Quality assurance of fiber-reinforced plastics in development, manufacturing and application.

Condition monitoring

Monitoring of public buildings and infrastructures.

Sensor integration

Structurally integrated sensors for automotive industry, wind energy and aviation.

Expertise: evaluation of permeability and residual stressSize of technical team: 5 person

Prototyping: c.e. Barkhausen Noise Demonstrator

COLLABORATION:AREAS OF INTEREST Development of pre-commercial technologies using material

evaluation by Barkhausen Noise (BN) method

Extension of the material characterization capability of the BN method for complex and miniaturized geometries and for the determination of the permeability and residual stress of ferromagnetic materials.

Application of AI-based algorithms thereby considerably improving calibration and thus also application to processes with changing and unknown material properties.

The application of material characterization using the BN method in new manufacturing processes, such as additive manufacturing (AM).

Development of BN to advance characterization and monitoring of case-depth hardening, electric steel and nondestructive measurement of material hardness.


https://mav.industrie.de/allgemein/revolution-in-der-werkzeugherstellung/#slider-intro-4

Novel minimazed BN probe

By SLM produces object

Artificial neural network

COLLABORATION:PROJECTS OF INTEREST

Idea for specific AI project


Dem

onst

rato

r

AI organization

Detection: AISensor DevelopmentReal Barkhausen Noise

Germany: SURAGUS/IKTS

Synthetic Barkhausen NoiseSimulation

Canada: RMC

Mechanical Samples ConditionsApplication market:- Additive Manufacturing- …

Canada: Applier 1 / NRCGermany: Applier 2

CONTACT DETAILS

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Organisation Name: Fraunhofer IKTSYour Name: Ulana CikalovaEmail Address: [email protected] Number: +49 351 88815-517Company web site: https://www.ikts.fraunhofer.de/en.html

Fraunhofer Institute for Ceramic Technologies and Systems IKTS

https://www.ikts.fraunhofer.de/en.html

ISW - Institute for Control Engineering of Machine Tools and Manufacturing UnitsDr.-Ing. Akos Csiszar

COMPANY DESCRIPTION

ISW - The Institute for Control Engineering of Machine Tools and Manufacturing Units• Research institute of the University of Stuttgart• Approx. 50 researchers (Mech, Elec and SW Engineers)• Main focus on control engineering – from planning to the tool• 50 years of experience in working closely with industrial partners

on R&D Projects

29ISW – University of Stuttgart

COLLABORATION:AREAS OF INTEREST

• Applied AI• Automated Planning and Decision Making

• Classical search and planning systems• Reinforcement learning

• Data Driven Modelling• Learning models from data using supervised learning methods for applications in

control engineering

• Production Technology• Control technology for CNC machines and other production systems• Real-Time Communication Systems (incl. TSN)• Simulation of Production Systems (also used as training environment for AI)



The AutoCAM Project- Automated Planning for Computer

Aided Manufacturing- Goal: reduce the engineering

workload in case of small lot size production

- Create manufacturing plans for CNC machining, automatically, from 3D models using AI methods


CONTACT DETAILS

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ISW – University of Stuttgart

Dr.-Ing. Akos CsiszarE-Mail: [email protected]: +49 711 685-84621Website: www.isw.uni-stuttgart.de

ISW – University of Stuttgart

http://www.isw.uni-stuttgart.de/

wbk Institute of Production Science @ Karlsruhe Institute of Technology (KIT)Jonas Hillenbrand, M.Sc.

COMPANY DESCRIPTION

34wbk Institute of Production Science

Machine Learning & Data

Analysis

Data acquisition

and process control

Simulation and

optimization

Digitalization and

networking

Process monitoring &

process control

Optimization of the

operating behavior

Interfaces for modular

production systems

Platforms and Services• Transfer domain knowledge to global

digital services• (Re-) Configuration of production systems

Machines and Processes• Autonomous machines• Value stream kinematics• Fields of application: Cutting, additive

manufacturing, forming

Machine dynamics &

vibration behaviour

Sensor system

development

Geometry optimization

and dimensioning

Intelligent components and sensor systems• Linear axis systems• Clamping device• Drives

Condition & wear

optimization

Research Group: Machine Tools and MechatronicsOur Staff: 3 Professors, 74 Acad. Researchers, 24 Administration


Research Focus on AI assisted Machine Tools Our Vision: The Autonomous Machine Tool


RF Agent

RF algorithmobservations

1) Highest Availability

2) Least Operation Cost

3) Longest Operation

4) …

reward

action

policy

• maintenance costs make up large proportion of operating costs

• a lot of status information is already available for mapping the machine status (Sensors, ERP, maintenance logs, etc.)

reinforcement learning agent assists maintenance planning:• maintenance problem is addressed as optimization

problem / target cost function• machine decides itself about maintenance actions• reduces inspection costs• machine automatically finds best composition of the

maintenance program

REINFORCEMENT LEARNING BASED MACHINE MAINTENANCE

CONTACT DETAILS

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wbk Institute of Production ScienceJonas [email protected]+49 1523 950 2582wbk.kit.edu

wbk Institute of Production Science

Otto-von-Guericke UniversityPaul Geoerg

COMPANY DESCRIPTION

Otto-von-Guericke UniversityMagdeburg, Germany

Faculty of Process- and Systems Engineering

Fire Safety EngineeringPedestrian dynamics Simulation of Crowd Motion, Fires and ExplosionsQuantitative Risk Analysis of Processes

38Otto-von-Guericke University

https://www.vst.ovgu.de/en/


39Otto-von-Guericke University


40Otto-von-Guericke University andNRC Fire Safety

Status-quo

Proposed solution

CONTACT DETAILS

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Otto-von-Guericke UniversityPaul [email protected]+49 391 67-58919https://www.vst.ovgu.de/en/

NRC Fire SafetyMax [email protected]+1 514 718 0152https://nrc.canada.ca/en/research-development/nrc-facilities/fire-safety-testing-facility

Otto-von-Guericke University

https://www.vst.ovgu.de/en/

https://nrc.canada.ca/en/research-development/nrc-facilities/fire-safety-testing-facility

wbk Institute of Production ScienceKarlsruhe Institute of Technology (KIT)Dr.-Ing. Frederik Zanger

COMPANY DESCRIPTION


Our strength is comprehensive research in production engineering along the entire value chain!The institute is made up of three main fields of research:

Manufacturing and Materials TechnologyMachines, Equipment and Process AutomationProduction Systems

containing knowledge and experience of selected production technology areas like Lightweight Manufacturing,Electric Mobility, Additive Manufacturing, Industry 4.0 and Sustainable Production.This enables us to explore topics as a whole and develop them in a target orientated way.The Matrix organization enables individual topics to benefit from a huge wealth of knowledge by integratingthem in the current research areas and facilitates a quick and in-depth processing of future orientated cross-sectional areas.

75 researchers35 basic research projects45 Cooperative research projects68 years of professional experience


Manufacturing:• Laser Powder Bed Fusion (LPBF)• Machining• In Process Monitoring• Advanced Process Chains• FEM-Modelling• Material Development

AI:• Defect Detection• Surface Engineering• Optimization of Process Strategies

Considering Disturbances• Process Chain Optimization



Additive components produced by Laser Powder Bed Fusion (LPBF) must bemachined to produce functional surfaces and tolerances. The requiredconstructional oversize depends largely on the resulting componentdistortion. Distortion can occur during additive manufacturing due to thermalgradients as well as during finishing by machining due to the release ofresidual stresses. Regardless of the reason, component distortion causeshigh manual effort in the finishing of additively manufactured components.Process sensor technology and mechanism knowledge are to serve asinput variables for an AI algorithm to be developed to simplify and acceleratethe product creation process, starting with the design, via additivemanufacturing to finishing, and to avoid expensive tolerances.


CONTACT DETAILS

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wbk Institute of Production ScienceDr.-Ing. Frederik [email protected](+49) 1523 950 2633https://www.wbk.kit.edu/

wbk Institute of Production Science

https://www.wbk.kit.edu/

CANADIAN RESEARCH INSTITUTES

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CARLETON UNIVERSITYAsli Eran – Research Contracts and Agreements OfficerIndustry and Partnership Services

49CARLETON UNIVERSITY

1942 Founded

965Faculty Members

39 PhD Programs

Carleton is a dynamic, interdisciplinary research-intensive university with a creative international approach to research that has led to many significant discoveries and collaborations in science and engineering, business, public policy and the arts.

50% in $2-year compounded increase in external Research Funding

1,000 +Active Research

Projects

80 +Research Centers

50 + Disciplines

# 2Most Sustainable

University in Canada

COMPANY DESCRIPTION


CARLETON UNIVERSITY

Carleton University is among the Top Research Universities - Winners Circle- in Canada and actively involved in Artificial Intelligence, with over 125 researchers from 4 faculties, 23 research labs, 13 university departments and institutes (including cross-appointments) actively engaged immensely varied research, with applications as far-ranging as :

Machine learning Accurate algorithm predications, Computer security and

wireless-based systems. Intelligent Transportation Systems Wearable technologies

Cognitive Science Robotics & Artificial Intelligence Robotic and mechatronic systems

analysis and design Real-Time Operating Systems Adaptive and Learning Systems

Some of our AI Collaborators

https://researchinfosource.com/top-50-research-universities/2019/top-research-universities-by-tier


51CARLETON UNIVERSITY

At Carleton University, we are applying AI and Machine Learning theory to real-world problems and developing the technologies and procedures of tomorrow – from robotic surgery, to autonomous space exploration, to intelligent information systems, homes, and vehicles.

Carleton University, with its more than 125 Faculty Members and 23 Research Labs involved in AI, is interested in becoming an Academic Partner in the Canada – Germany 3+2 collaborative call with the following expertise:

• Applications of artificial intelligence,

• Evolutionary computing to software engineering

• Agent-based systems, • Object-oriented design and

languages,• Network management and

supervision

• Learning with • complex outputs, • Active learning, • Heterogeneous

learning, • Learning graphical

models

• Robotic analysis, design, and control,

• Machine and biological locomotion,

• Mechatronics, • Linear and nonlinear

control, and simulation, • Virtual reality

CONTACT DETAILS

52

Carleton University

Asli Eran, Industry and Partnership ServicesEmail: [email protected]: +1 613 520 2600 – 4411https://carleton.ca/ips/

CARLETON UNIVERSITY

https://carleton.ca/ips/

Royal Military College of CanadaProf. Thomas W. Krause

COMPANY DESCRIPTION

Research and Development in electromagnetic and magnetic nondestructive evaluation methods including:• Eddy Current• Pulsed Eddy Current• Magnetic Barkhausen Noise• Magnetic Adaptive Testing• Passive MagnetometryNational and International CollaboratorsKey Products: Nondestructive Inspection Systems and MethodsTechnical Team: Senior Research Associate, Post Doctoral Fellow, Visiting Scientist, 6 graduate students

54Royal Military College of Canada - Nondestructive Evaluation Development Group

Magnetic Barkhausen noise (BN) analysis using AI & machine learningfor assessment of ferromagnetic steel condition and properties, including microstructure, hardness, stress and permeability.BN is sensitive to:

- Grain size, - Texture, - Inclusions

(e.g. carbon, impurity elements)- Strength and Hardness- Elastic stress - Plastic deformation


55Royal Military College of Canada - Nondestructive Evaluation Development Group Krause et al. , Micromagnetic Techniques, ASM Handbook Vol. 17, 2018


Nondestructive characterization & evaluation of ferromagnetic steel properties:• Microstructure• Magnetic permeability• Case depth hardening• Electrical steel core loss• EmbrittlementSteel materials including:• Steel pipe• Plate/sheet steel• Additive manufactured steel

56Royal Military College of Canada - Nondestructive Evaluation Development Group

www.thetrustedinsight.com/

https://www.sgs.com/en/industrial-manufacturing

CONTACT DETAILS

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Organisation Name: Royal Military College of CanadaYour Name: Thomas KrauseEmail Address: [email protected] Number: 613 541 6000 ext 6415Company web site: https://www.rmc-cmr.ca/en/physics-space-science/thomas-krause

Company Logo

Royal Military College of Canada - Nondestructive Evaluation Development Group

GERMAN SMALL OR MEDIUM-SIZED ENTERPRISES (SMEs)

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TROUT GmBHMartin Bussas

COMPANY DESCRIPTION

TROUT GmbH’s business model is based on R&D contracting in the areas of automotive and medical technology and on establishing a product range.With years of experience in biometric data processing, TROUT has extensive knowhow in incorporating artificial intelligence (AI) and machine learning (ML) in their innovative products and solutions.Two notable examples are VitaB where machine learning is used to acquire vitality parameters and to classify cognitive condition; and NivaB where non-invasive determination of blood glucose is performed by impedance spectroscopy with the application of neuronal networks.

60TROUT GmbH

https://trout-gmbh.de/en/vitab-2

https://trout-gmbh.de/en/nivab-2


Artificial Intelligence becomes more and more important in medical and energy industry and is having great potential for the future design of systems. We would like to start a project in these areas together with a strong partner.Another area is the Autonomous Materials Discovery (AiMade). In an ongoing project we enable a system of chemical reaction with a software based on Machine Learning to become an autonomous and self-regulating plant for the synthesis of chemical products.Here the synthesis of stilbene building blocks is studied.

61TROUT GmbH


TROUT gained considerable expertise in data processing during automotive and medical technology developments which focused on machine learning and AI. Applications: Vibration analysis and analysis of acceleration values in vehicles, Evaluation of structure-borne noise for predictive maintenance, Prediction of sound insulation of complex materials, Heartbeat detection with radar and deep learning methods

62TROUT GmbH

CONTACT DETAILS

63

TROUT GmbHMartin [email protected]+49 561 810497-11www.trout-gmbh.de

TROUT GmbH


DatenBergMaximilian Backenstos

Simplify complex production processes with DatenBerg (= Mountains of Data in German)

We offer software for manufacturing companies to:1) Identify quality deviations2) Find root-causes automatically3) Predict quality and get notified about deviations

65DatenBerg

What we did so far – some examples:

Chocolate Compounding Body in white


What we bring to the table:Experience out of over 15 manufacturing data analysis projects in food, chemicals, metal parts, injection molding, tunneling,….+ Experience in funding proposals (2x granted H2020 supports)

Open for:- New applications of DatenBerg software (e.g. maple sirup

manufacturing, mining, seafood processing)- Research collaborations for smart data usage (with and without AI) in

manufacturing sites

66DatenBerg


1) Transfer Learning across manufacturing sitesHow can we transfer the knowledge of one manufacturing (e.g. injection molding) site to another?Can this help to ramp up one production site in another country faster and more efficient?

2) AI for SME manufacturing companies What tools do they need and how can we offer them in a scalable and cost-efficient way?Are there differences between German manufacturing SME’s and Canadian ones in terms of requirements?

3) Sharing is caring – providing data to B2B customerWhat added-value can be generated by providing data across the value chain?What analysis tools/infrastructure would be necessary to share data?

67DatenBerg

CONTACT DETAILS

68

DatenBerg GmbHMaximilian [email protected]+4915140768753www.datenberg.eu

….or let us connect on LinkedIn!

DatenBerg

http://www.datenberg.eu/

CANADIAN SMALL OR MEDIUM-SIZED ENTERPRISES (SMEs)

Aurelien Balondona, P.Eng., MBB

http://www.baune.ca/


COMPANY DESCRIPTION

Canadian (Alberta) technology company, baüne® is a solutions integrator of smart ecosystems, pioneering with a combination of emerging technologies such as edge computing, physical web, internet of things, remote management system, big data, mobile payments, artificial intelligence and blockchain.

Baüne is a Member of the Intel® IoT Solutions Alliance. This is a global ecosystem of more than 900 industry leaders, offering its Members unique access to Intel® technology, expertise, and go-to-market support—accelerating deployment of best-in-class solutions.

71Baüne Ecosystem Inc.


• Hardware: Gateways/Communication Devices, Wearables, Embedded Systems

• ICT Future Project: AI, Digital Health, Blockchain, • Mechatronics: Internet of Medical Thing, Cyber Security & Cloud,

Big Data Analytics, System Integration• Software: Platform-as-a-Service (PaaS), Mobile Apps, Data

Analysis• Value Chain: Design/R&D/Engineering


COLLABORATION:PROJECTS OF INTERESTThe situation: Healthcare - tracking/identifying abnormal temperature, touchless dispensation and frictionless services

The problem: During this unprecedent time, the healthcare point of care locations are in need to become safer places to give assistance to the patients. Healthcare professional while helping the ill must also take care of their own safety and health, meaning the must change conventional behaviors and restructure daily practices to reduce risk of contacting virus. Although the healthcare system have programs to mitigate the spread of infections, the need of digital transformative solution with touchless and frictionless technologies are more prevalent than ever.

The solution: Technologies like NÜPA with touchless and frictionless products and services 24/7-365 days. It is an IoT Intelligent Kiosk with thermometry technology, touchless dispensation, real-time report, healthcare monitoring, mobile app friendly, 3A compliant screen, using machine learning as a core technology and privacy compliant.


CONTACT DETAILS

74

Baüne Ecosystem Inc.Aurelien Balondona, P.Eng., [email protected]

Baüne Ecosystem Inc.





Braintoy Inc.Amit Varma

COMPANY DESCRIPTION

Made a machine learning platform to rapidly build and deploy production ML.

Amit Varma Dr. Padma Paul Kwame Asiedu

Team has 50+ years cumulative experience in industrial software and AI/ML.

76Braintoy Inc.


Model factory in a governed mlOps pipe

1. Are you a developer who builds industrial AI applications?

2. Are you an organization that wants production ML?

3. Are you a researcher who uses ML for rapid prototyping?

77Braintoy Inc.


Sample project/s for collaboration:

• Predictive risk-based maintenance of assets, manufacturing defects, equipment failure etc.

• Prescriptive recommendation engines.• Optimization of processes, facilities, or workforce.

You have a defined use case or are already using AI/ML.

78Braintoy Inc.

CONTACT DETAILS

79

Braintoy Inc.Amit [email protected]+1.403.971.2648https://www.braintoy.ai/

Braintoy Inc.

https://www.braintoy.ai/

NTWIST Inc.Chowdary Meenavilli

COMPANY DESCRIPTION

81NTWIST Inc.


82NTWIST Inc.

Partnership Opportunities:

Industrial Adoption

Technology Commercialization

AI Research


83NTWIST Inc.

CONTACT DETAILS

84

NTWISTChowdary [email protected]+1-780-807-4023www.ntwist.com

Company Logo

NTWIST Inc.

AnalytikaWill Munoz

COMPANY DESCRIPTION

86

Innovative Industry 4.0 Solutions

Machine Learning Experts

AI Disruptors

Agile Delivery & Project Management Proficiency

Lean Cost-Effective Approach

End-to-End Solutions

COLLABORATION:AREAS OF INTERESTIn terms of this specific program, what are your organization’s AI and/or Manufacturing areas of interest for domestic and/or international collaboration?

87

Industrial Digital Twins

Smart Energy Management and Optimization

Manufacturing Processes Optimization via AI Vision

Industrial Safety improvement via AI Vision & IoT

PROJECTS DELIVERED IN

Inventory Shelf Control & Management via AI Vision


88

CONTACT DETAILS

89

AnalytikaWill [email protected]+1(403)463-2128www.analytika.ca

Company Logo

Applied Brain Research Inc.Peter Suma, co-CEOwww.AppliedBrainResearch.com

http://www.appliedbrainresearch.com/

COMPANY DESCRIPTION

• What: Tools & experts in Dynamic AI. AI compiler, algorithms & world leading team • For: Learning, recognizing, predicting, control and anomaly spotting of time-varying signals • Environments: data center, edge and embedded (car, drone, sensor & phone)• Customers: automotive, semiconductor, military, energy, software, national research labs. Example solutions:

• Patented AI network for learning and predicting multi-dimensional temporal signals, up to 1Mx better than LSTM, with mathematical proof, application to all temporal AI (ASR, video, drone & robot control, sensor signal processing…)

• State-of-the-Art (SotA) ultra-low power ASR for cloud provider• SotA vision processing for automotive manufacturer• Autonomous, low-power drone on-board flight & inspection task control system for infrastructure inspection• Traffic predictor for automotive manufacturer, beat company SotA• Complex dynamics AI learning system for national defence

• Expertise• Dynamic AI processing algorithms modelled after brain circuits (asynchronous, massively parallel, low-power,

dynamic)• First principles AI algorithms & compiler research, design, development• AI software & hardware chip design

• Size of Technical Team: 19 in our experienced AI R&D team (10 AI PhD’s, 4 Masters Engineers, 5 undergrad engineers)

91Applied Brain Research Inc.


• Car makers seeking to lower power and raise accuracy for onboard AI systems for vision, sensor processing, traffic prediction and control

• Car, phone, drone, robot, process control makers & military looking for SotA autonomous control system R&D

• Sensor makers looking for more powerful and significantly lower-power embedded AI hardware and software solutions for signal processing (learning, predicting, anomaly detection, system control)

92ORGANISATION NAME


• All dynamic AI systems projects: Using AI to process signals in time in the data center or embedded in a device.

• The learning, predicting, anomaly-spotting and autonomous systems control for all devices (car, phone, drone, robot, sensor, process control, etc..)

• Advanced SotA autonomous control system development projects

93ORGANISATION NAME

CONTACT DETAILS

94

Applied Brain Research Inc.Peter Sumaco-CEOPeter.Suma@AppliedBrainResearch.com1-416-505-8973www.AppliedBrainResearch.com

ORGANISATION NAME


http://www.appliedbrainresearch.com/

ContextereCarl ByersCTO & Chief Strategy Officer

Contextere ML Platform for MRO

96Contextere


97Contextere


Intelligent Guidance and Digital Work Enablement for Improved Production Processes

Potential Collaborators:• SMEs with condition monitoring IOT/Sensor technologies• Research organizations focused on human-machine integration in

production environments• Manufacturers with extended value chains

98Contextere

CONTACT DETAILS

99Contextere

Carl ByersCTO & Chief Strategy Officer

[email protected]+1.613.851.1712www.contextere.comwww.linkedin.com/company/contextere/

Deeplite Inc.Davis Sawyer, Co-founder & CPO

101Deeplite Inc.

Montreal HQFounded April 1st 2018 (Incorporated August 2019) within TandemLaunch incubator program11 employees (8 AI experts)

Deeplite Intro


102

We use AI to make other AI smaller, faster and more energy efficient

in the cloud and at the edge

Drones, IoT & Surveillance

Robotics & Industrial Automation

Life-critical Medical Devices

Connected & Autonomous Vehicles

Deeplite Inc.


103

Smart Manufacturing Computer Vision use case• ARM Cortex-M4 (256KB of on chip memory, 1MB of flash)• MobileNetv1 CNN trained on proprietary binary classification dataset• Target optimization metrics are model size (in MB) and accuracy

Deeplite Inc.

link to technical blog

https://community.arm.com/developer/ip-products/processors/b/ml-ip-blog/posts/unlocking-ai-on-arm-microcontrollers-with-deep-learning-model-optimization

CONTACT DETAILS

104

Deeplite Inc.Davis [email protected]

Deeplite Inc.

Giatec Scientific Inc.Aali R. Alizadeh, CTO

COMPANY DESCRIPTION

• Established in 2010, Giatec offers IoT solutions to the concrete industry.

• Giatec’s flagship product, SmartRock sensor, has been used in 6,000 projects worldwide to monitor concrete curing and hardening.

• 20 people in the R&D team with expertise in concrete science, software (mobile and cloud) development, and electronic design, manufacturing and AI (4 in data science and machine learning).

• With millions of datapoints collected from SmartRock sensors, Giatec developed Roxi, the first AI program to detect anomalies and predict concrete performance.

106ORGANISATION NAME


• Machine learning applications in the construction industry • Wireless sensors • Antenna design • End-to-end IoT solution architecture • Low-power (battery operated) gateways



• To expand the capabilities of Roxi, we need to access more data from local concrete producers in different countries.

• The wireless SmartRock sensors utilize BLE with limitation on the depth of installation inside concrete. We are interested to explore areas of improvement in the BLE signal range.

• From IoT perspective, we are interested to collaborate on the development of robust local hub solutions to collect sensor and jobsite data.


CONTACT DETAILS

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Giatec Scientific Inc.Aali R. Alizadeh, [email protected]

ORGANISATION NAME

http://www.giatec.ca/

Pleora Technologies Inc.Jonathan Hou

Our Company

Founded in 2000 with a vision to utilize Ethernet technology to simplify high-performance video transport

Experts in high-reliability, low-latency hardware and software solutions for intelligent imaging applications and AI

Founding member of GigE Vision standard

Simplifying vision development an deployments

111Pleora Technologies

COLLABORATION:AREAS OF INTERESTMachine Vision, automation & integration with Industry 4.0


Level 0: Human Controlled

Level 1: Early Automation

Level 2: Modern Factory

Level 3: IT / OT Integrated

Level 4:Digitally Transformed

Level 5: Lights Out

Manual processes for visual inspection and handwritten reports

Central PC architecture in MV architecture for traditional computer vision

Networked cameras and wired networking infrastructure to integrate with factory systems like ERP

Inclusion of AI algorithms in embedded devices

Embedded learning in conjunction with existing PC architecture connected over GigE Vision networks

Replacing PCs with embedded learning devices, leveraging distributed architecture

Start leveraging wireless protocols in parallel with WiFi 6 and 5G

Leverage multiple sensor types (3D, hyperspectral) to augment inspection

Leveraging the intersection of GigE Vision and OPCUA networking protocols to allow embedded device and sensor communication (M2M)

Use of 5G and WiFi6 technologies for networking

Cloud-based systems to manage learning and training data


The Pleora AI Gateway is a platform for deployment of “plug-ins” for machine vision and AI applications. We are looking for collaborators to develop application-specific use cases for IIoT, Manufacturing and Medical Imaging to bridge the gap between sensors and Industry 4.0.


CONTACT DETAILS

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Pleora Technologies Inc.Jonathan Hou, [email protected]+1 613 270 0625www.pleora.com

Company Logo

Pleora Technologies

http://www.pleora.com/

PolyAlgorithm Machine LearningFrederick Speckeen, Business DevelopmentWaterloo, Canada

COMPANY DESCRIPTION

Welcome to PolyML!• small, specialist team of machine learning, mathematics and data science professionals.

• >100 human years combined experience.

• specializing in challenging and complex data.

• >25 different, highly tuned, traditional and proprietary machine learning algorithms.

• Specialists in handling complex data: data series, sequence data, spectrographic data, unstructured textual data in multiple languages, continuous data…

Core TeamDr. Gaston Gonnet, Chief Scientist https://en.wikipedia.org/wiki/Gaston_Gonnet

• Oxford English Dictionary(1984); Founder of Open Text, Maplesoft, Prof. Emeritus ETH, Zurich, H, Darwin->OMA

Tim Snider, CTO• MSc Waterloo; OED(1984); specializes in extracting valuable data from highly disparate and complex data sets

John Stewart, VP Development• B.Mathematics Waterloo; architecting, developing and deploying machine learning solutions.

Range of Experience• manufacturing, extraction processes, banking, insurance, agriculture, legal and bioinformatics

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https://en.wikipedia.org/wiki/Gaston_Gonnet


Our areas of interest are collection of vibration, acoustic and spectral data, its analysis, and the creation of highly accurate, predictive models used in manufacturing for: • predictive maintenance; • yield optimization; and • quality prediction.

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1. Bespoke ML solutions for individual companies – manufacturing floor2. Development of ML control systems for equipment manufacturers• Metal stamping• Combined stamping and welding processes• Robotic welding of traditional metals• Robotic welding of Gen3 metals• Automated tooling processes

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CONTACT DETAILS

119

Polyalgorithm Machine Learning “PolyML”

Fred Speckeen, Business DevelopmentEmail: [email protected].+1 226.791.4041

www.polyml.com


http://www.polyml.com/

RUNWITHIT Synthetics Inc.Myrna Bittner, CEO Co-Founder

COMPANY DESCRIPTION

RWI Synthetics specializes in a new cornerstone of AI – Synthetic Intelligence. We create environments that bring to life complex systems involving infrastructure, technology and people, to derisk and accelerate innovation and design.• RWI models systems in sectors including city infrastructure,

policy and disaster response, utilities, renewables, energy, digital TV, invehicle, IoT, digital systems

• In 2020, RWI won the EPRI (Electric Power and Research Institute) Incubatenergy Labs Challenge with RWI’s Synthetic Energy Futures – a modelling environment that facilitates the design and response of grid decentralization and electrification based on a human-centric approach

• RWI’s Synthetic Intelligence “Inflector Engine” is a culmination of 20 years of AI IP. The team is currently 14 specialists in data science, software and modelling.

121RUNWITHIT Synthetics Inc.

The application of RWI’s Synthetic Modelling in Manufacturing includes the following:• Agent-based modelling for human/machine interface design

(proposals underway for IraSME R&D Project with a German University and manufacturer)

• Corporate Alliance in Mexico with a member of the Alfa Group –manufacturing sector in steel, chemicals, automotive, etc

• Development underway of optimization of volatile manufacturing processes and scheduling through Synthetic Twinning (aka Digital Triplets)

RWI’s Synthetic Models:• Accelerate the of complex system trial and validation, • Enable strategic future scenarios to be explored and optimized• Furnish insight into every aspect of even novel scenarios.




Synthetic Twinning – Adding the ability to explore future scenarios– such as new products, processes, technologies and capabilities to digital twinning information. RWI’s Synthetic Models create reactive responsive entities that can be utilized to explore all types of novel scenarios, without relying on historical data. These Models capture emergent behavior for analysis that escapes mathematical based simulations.

Synthetic Optimization – RWI’s Synthetic Models facilitate intelligent optimization of complex systems including volatile production scheduling, asset availability and maintenance, supply chain coordination. RWI has begun work in this area with partners in manufacturing and defence and is looking to participate with other partners.


CONTACT DETAILS

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Runwithit Synthetics Inc.Myrna Bittnermyrna@runwithitsynthetics.com1-780-999-3755www.runwithitsynthetics.com

RUNWITHIT Synthetics Inc.

http://www.runwithitsynthetics.com/

OTHER PITCH

Canadian Standards Association (CSA)Dr. Pascal Hervé

COMPANY DESCRIPTION

• CSA Group is a global organization dedicated to safety, social good and sustainability. We are a leader in Standards Development and in Testing, Inspection and Certification around the world including Canada, the U.S., Europe and Asia.

• 2000 employees worldwide – 39 Offices – 13 Countries• CSA Mark is accepted by jurisdictions throughout North America• Over 3.000 accredited certification programs

127CSA Group


128CSA Group

Requirements Design Implementation Verification Release ResponseTraining Maintenance

Gap Analysis (Guidance Documents, Standards, NIST Framework)

Security Design & Testing ANSI/CAN/UL 2900

Organizational Cybersecurity

Maturity Evaluation

Threat ModelingAttack Surface Analysis

Bench Testing

Security Controls TestingSoftware Cyber Bill of Materials

Robustness / Fuzz TestingVulnerability Identification

Penetration TestingSecurity Risk Analysis, Threat

Modeling, Attack Surface Analysis

ISO 14971, IEC 62304AAMI TIR 57,

NIST SP 800-30IEC 80001

CSA EXP200*

Testing & Evaluations

CSA Security Lab Accreditations

62443-2-4

Holistic Cybersecurity Support Throughout SW&HW Entire Lifecycle

Industrial Control System (ICS) Network and System Security IEC 62443

ANSI/CAN/UL 2900-1ANSI/CAN/UL 2900-2-1

Security Development Lifecycle IEC 62443-4-1 ISO 17025, 62443-4-1

ANSI / ANAB

CSA Group(*) CSA Group Standard Draft

https://store.csagroup.org/ccrz__ProductDetails?viewState=DetailView&cartID=&portalUser=&store=&cclcl=en_US&sku=CSA%20EXP200:19


• Objective: Mitigate the risk of a cyber attack arising from the deployment of Industrial AI

1. Securing AI from thread e.g. where AI is a component in the ICS system that needs defending.

2. Controlling against AI e.g. where AI is the ‘problem’ or is used to improve and enhance other more conventional attack vectors.

3. Practicing AI to enhance security measures against attack from other things e.g. AI is part of the ‘solution’ or is used to improve and enhance more conventional countermeasures.

AI Industrial Standard Creation Training and Education

129CSA Group

CONTACT DETAILS

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CSA Group Bayern GmbHDr. Pascal Hervé[email protected]+49 151 24042069csagroup.org

CSA Group


https://www.csagroup.org/

Thank you · Merci · Danke

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