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EURECAT technology pitch to GENERAL MILLS
Detection – biosensors – bin picking -Artificial Intelligence:
R&D and innovation at Eurecat technology centre
S3FOOD has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824769
Ignasi Papell Garcia
Business Development Manager Food Industry - EURECAT technology centre
[email protected] +34 618 414 270
Innovationwith an impact
We promote business
competitiveness and the
wellbeing of society through
applied research and innovation.
3EURECAT video
Eurecat is a private Technology Center with experience in food and health, biotechnology,
sustainability, industrial technologies and digitalization. We work with the food industry to develop
new food products and ingredients. Smart and sustainable Food industry 4.0 aimed at creating
value in healthy, convenient and safe food products for informed, digital and conscious consumers.
Company profile / Products and services www.eurecat.org
▪ Concept and food product design
▪ Validation of the healthy effect
▪ Food technology and food safety / toxicity and ecotoxicity studies
▪ Packaging
▪ Food industry 4.0 (including sensors and photonics), Applied Artificial Intelligence,
Cybersecurity, Artificial vision, Virtual reality, Robotics and Automation, Modeling and
simulation, Materials solutions and mitigation of corrosion processes, Training.
▪ Circular Economy and Sustainability, Industrial Ecology and Environmental Impact, Integral
Water Cycle
▪ Agri-food and farming 4.0
▪ Valorization and commercialization of products and technologies, Market & Consumers
Knowledge
Innovation with an impact
Madrid
Our offer is accompanied by
the specialized knowledge of
prestigious universities and
research centres to systematize
and enhance the transfer of
technology and provide better
service to companies.
We are a quick-moving and flexible organization
with a wide network of national and
international collaborators.
Chile
Barcelona
We help companies discover new
opportunities and participate in creating
and improving products, services,
processes
and business models with an impact on
their competitiveness and social
wellbeing.
Turnover
in 2019
Comprehensive RDI servicefor businesses:
50%of our
activity is with
SME
51,3M
Business
clients1,700
6
Data corresponding to the end of 2019
A committed team,aligned with our companies
We have a results-oriented team
committed to all our projects to
offer companies excellent
service.
+650professionals
21%doctors
42%women
58%men
7
Data corresponding to the end of 2019
Integrationof multiple technologies
Industry
1. Advanced materials (metallics,
composites, polymers)
and new manufacturing processes
2. Functional printing and embedded
devices
3. Interactive and autonomous
robotics
4. Functional textiles
5. Chemical Technology
6. Innovation and product
development
Our differential
value:
Our multi-technological
capacities allow us to face
complex challenges.
Digital
1. Sensor systems and
IoT
2. Artificial intelligence
3. Big Data & Data
Science
4. E-Health
5. Cybersecurity
6. Multimedia
technologies
Biotechnology
1. Nutrition and health
2. Omic sciences
Sustainability
1. Water
2. Air
3. Soil
4. Waste
5. Energy
6. Batteries
7. Environmental
impact
8
The AI Digital Innovation in Catalonia
The CIDAI is a public-private initiative that promotes the transfer
of knowledge and the implementation of joint projects between
knowledge-generating entities (universities, research and
innovation centers), technology and service providers, and user
companies and institutions demanding innovative solutions in
applied artificial intelligence.
The CIDAI aims to accelerate the adoption of reliable Artificial
Intelligence in the business world and in society, as well as
enhance the Catalan Artificial Intelligence ecosystem as an
international reference pole by creating a connected, active and
dynamic community that involves the majority of the agents.
Coordinated by Eurecat, it is a key piece in the Catalonia AI
strategy promoted by the Government of Catalonia.
www.cidai.eu
9
Solution to GENERAL MILLS challenges
www.eurecat.org
Challenge 1: DETECTION SYSTEMS
Challenge 2: ONLINE LISTERIA DETECTION BIOSENSORS
Challenge 3: BIN PICKING SEASONING AND SAUCE
Challenge 4: AI APPLIED TO BAKERY PROCESS, ingredients parametersprocess result
Solution to GENERAL MILLS challenges
www.eurecat.org
Challenge 4: AI APPLIED TO BAKERY PROCESS, ingredients parameters process result
Solution to GENERAL MILLS challenge 4
Raw materials(water, flour…)
Tortillas Production Process
High heterogeneityof raw material
Good Tortilla
BadTortilla
manual adjustment of process and machine settings
manual recipe adjustment(percentage of mixes)
Solution to GENERAL MILLS challenge 4
Mixing-Curing
Pressing Baking Cooling
Raw materials(water, flour…)
physicochemical parameters of raw materials
Environmental parameters (temperature, humidity…)
Recipe and machine settings Quality Prediction
process operational data(torque, consumption
motors, oven temperature, humidity in the oven, conveyor speed….)
Quality production reports
Supervised/Unsupervised
Learning
UnsupervisedLearning/ Case Base Reasoning
machine settings
Smart Management Systems AI, Data analytics and IoT solutionsApplications for agri-food sector
Technologies
• Big Data Architectures
• Interoperability & Standardization
• AI including Machine Learning
• Edge & Cloud Computing
• Assets digitalization
CONOCE: - Investigate solutions based on disruptive technologies to minimize the effect of raw material
variability on the cookie making process (i.e. recommendation of line configurations based on raw material parameters, prediction quality...)
Partners:
Big Data technologies
Interoperability&
Standardization
AI techniquesEdge & Cloud
Computing
Assetsdigitalization
Smart Management Systems AI, Data analytics and IoT solutionsApplications for agri-food sector
Technologies
• Big Data Architectures (Druid, Apache Kafka, Apache Superset, Mosquitto)
• Interoperability (RAMI4.0, OPC-UA and MQTT)
• Knowledge management
• AI techniques for improving the grape pressing and fermentation process (Machine Learning and Case-Based Reasoning)
AdvanceWINE: Provide a new model, based on new technologies, for the production of sparkling wines (grape production, winemaking and bottling) capable of managing the biological process of the grape (variability and seasonality) and its influence on each of the stages of the productive cycle
Partners:
Grape ProductionManager, PlantManager, Oenologist, Operator…
Smart Management Systems AI, Data analytics and IoT solutionsApplications for agri-food sector
Technologies
• Big Data Architecture (Druid, Apache Kafka, Apache Superset, Mosquitto)
• Interoperability (RAMI4.0, OPC-UA and MQTT)
• IoT Devices based on open-hardware and open software (Raspberri Pi and Arduino)
• Edge Computing capabilities
IGNITE: Research, design and develop an efficient, flexible, secure standards-based architecture, considering ubiquitous integration solutions between the various components of the industrial value chain such as devices (machines / sensors), monitoring and control systems (PLCs / SCADAs), management systems (ERP / MES / PLM),… as well as operators
Partners:
CPSAdaptar els protocols de comunicació existents en planta
Intel·ligència embeguda per a l'optimització dels paràmetres d'execució
Integració de dades de planta i dades externes
Comunicacions estandarditzades i segures
Base de coneixement per al tractament massiu de dades de planta
Traçabilitat, control de qualitat i generació d'alertes
Visualització avançada en temps real per a la presa de decisions
Integración vertical, securización y validación completa
Modelatge estandarditzat de processos productius
Desplegament, experimentació i proves en planta
Advanced real-time visualization for decision-making
Standardized modelling of production process
Plant and external data integration
Standardized and secure communications
Deployment, experimentation and in-plant testing
Traceability, quality control and generation of alerts
Embedded intelligence for optimization of operational parameters
Knowledge base for mass processing
Vertical integration, secure and complete validation
Smart Management Systems AI, Data analytics and IoT solutionsApplications for agri-food sector
Technologies
• Big Data Architecture (Druid, Apache Kafka, Apache Superset, Mosquitto)
• Interoperability & Standardization
• Digitalization of assets (OPC-UA)
CONOCE: - Design a new flexible and distributed manufacturing model, based on an integrated value chain,
for the bottling of sparkling wine based on new technologies
Partners:
Solution to GENERAL MILLS challenges
www.eurecat.org
Challenge 1: DETECTION SYSTEMS. Photonics + hyperespectral
Challenge 2: ONLINE LISTERIA DETECTION BIOSENSORSPhotonics. R&D needed
Advanced Manufacturing
Photonics
Láser de guía de onda óptica Láser de Saphir de Titanio Láser de Microchip
Sensor ópticoMicrofluídica por
interrogación fotónicaSensor aigua-hielo
Photonics
Portable measuring ovoscope(URV’s patent)
Ovoscope designed to measure the height of the egg's inner air chamber to
determine its level of freshness and quality.
A laser light source with a sensor is able to accurately assess the magnitude of the
height of the internal air chamber.
Solution to GENERAL MILLS challenges
www.eurecat.org
Challenge 3: BIN PICKING SEASONING AND SAUCE
In-line automation with 2D picking delta robot (spider)
It offers pickings of high candences 0.6 s / picking in optimal conditions
Working area: diameter of 1.600 mm
Load 1 Kilo
2D Picking solution more robust and economical than 3D vision
Delta robots are especially suitable for use to automate assembly workand versatile handling through
high-speed operation. Its use is highly recommended in Pick & Place processes in the food and
pharmaceutical sector.
A stainless-steel option is available for food handling applications with validatedIP69K so that the robot
can be washed with industrial detergents and high-pressure hot water.
BIN PICKING SEASONING AND SAUCE
https://wetransfer.com/downloads/917ff25cd3f90f12815c992ae4763d4c20201028074200/66feaede9fa868a470a50cb6b5cec77420201028074200/a7a340
BIN PICKING SEASONING AND SAUCE
In-line
automation
with 2D picking
delta robot
(spider)
Installed by
Eurecat in 2012
https://eurecat.org/en/field-of-knowledge/robotics-automation/robótica
Advanced solutions on Industrial Robotics
BinPicking,
Palletizing
Equipment Loading,
packaging ,
Logistics,
Ensambling,
…
Automatización de fabricación de componentes
ligeros.
- Scan and Plan para la inspección de porosidades
mediante ultrasonidos de pieza de composite.
- Inspección de la orientación de las fibras en
pieza de composite.
- Inspección con cámara termográfica aplicando
calor en las piezas RTM para encontrar defectos
en la pieza de composite.
MARIETANoteworthyprojects
27
robotics
Percepción industrial
• Guiado y calibrado de robots
• Localización de objetos
• Clasificación de objetos
• Metrología y Digitalización
• Control Dimensional 2D/3D
• Verificación de
especificaciones
• Segmentación
• Visión térmica e hiperspectral
• Detección de defectos
Capacities
robotics
Automatización
de la inspección
Bin picking piezas de fundición
• Escaneo y posicionamiento de
piezas
• Planificación de trayectoria y
posicion de grasping
• Tiempo real
• Robótica industrial
Noteworthyprojects
29
robotics
Bin Picking
Escaneado de objetos y
planificación de trayectorias
• Escaneado mediante sistema láser
• Planificación de trayectorias
• Tiempo real
• Robótica industrial
Noteworthyprojects
30
robotics
Scan&Plan
Sorting para el sector del reciclado
combinando identificación de material y
robótica
Deep Learning sobre imagen hyperspectral
• 16 tipos de clases de cartón/papel
• Desarrollo de distintas técnicas de procesado
de imagen hyperspectral para asegurar
variabilidad
• Entrenamiento y validación con datos de Test
Center (Picvisa) y planta (Saica)
Noteworthyprojects
31
robotics
ECOFIBRA
Modeling and generating robot behaviors:
• Implementation of BehaviorTree.CPP library
• You can build reactive behaviors that
execute multiple Actions concurrently.
• Trees are defined using a Domain Specific
Scripting scripting language (based on XML),
and can be loaded at run-time
• GUI editor – building blocks
• It includes a logging/profiling infrastructure
that allows the user to visualize, record,
replay and analyze state transitions.
Advanced
Planning
Noteworthyprojects
Mood2be
Sharework provides the intelligence,
methods and tools required for the
effective adoption of human-robot
collaboration (HRC) in manufacturing
processes lacking automation.
The project is developing a robotic system
capable of understanding the environment
and predicting human behaviour thanks to
artificial intelligence and process data.
The technology will have the capacity to
create a robot that can work in an
environment that guarantees human
safety.
www.sharework-project.eu
Human
RobotCooperation
Noteworthyprojects
33
A collaborative mobile manipulator for:
in-Factory handling tasks, able to co-
manipulate objects with workers in a
production line
Co-operation between robots and humans
• Human tracking
• Gesture detection
• Adaptive path planning
• Safe and effective human-robot
cooperation
Mobile Manipulator
Noteworthyprojects
Video
Adaptation of novel ToF depth sensors in
autonomous robotic applications
Developing algorithms to exploit ToF
technology
• Drivers
• Visual Inertial Odometry
• Visual SLAM
• Defect detection
Novel Depth
Sensors
Noteworthyprojects
Solution to GENERAL MILLS challenges
www.eurecat.org
Challenge 1: DETECTION SYSTEMS
Challenge 2: ONLINE LISTERIA DETECTION BIOSENSORS
Challenge 3: BIN PICKING SEASONING AND SAUCE
Challenge 4: AI APPLIED TO BAKERY PROCESS, ingredients parameters process result
Ignasi Papell Garcia
Business Development Manager Food Industry
618 414 270
Av. Universitat 1. 43204 – Reus (Spain)
www.eurecat.org
Detection – biosensors – bin picking -Artificial Intelligence:R&D and innovation at Eurecat technology centre
