ZDMP Assets - SubCall View

IPR Documents

The assets of the the ZDMP project will be available for use in the ZDMP subcalls when launched. In preparation for this, the project will release information on these components and below is the current status of the IPR concerning these assets that we believe is most relevant to the subcalls. An extended version of this information, largely relevant to project partners, is also available [make a link to the full page]. The information is described in EU H2020 terms, one of the sponsors of the project and there are multiple articles on the web discussing this, and we estimate most subcall bidders will be familiar with this environment. However, in short the major concepts are:

  • Background: Tangible or intangible input (data, know-how, information) which is held by the project partners prior to their accession to the project. Includes IP as copyright, patents/ patent applications (filed prior to access to project). Examples: prototypes; cell lines; database rights, licences with the right to sublicense.

  • Augmented Background: Enhancements to the Background material made within the project but largely inseparable (aka dependent on the Background). Thus, broadly it is a combination of Background+Results. NB this is note the same as Sideground which is produced in the project time-frame but outside of the project:

  • Results, also known as Foreground: All results which are generated under the project – whether or not protectable. Such results may include copyrights, design or patent rights, trademarks or others, and belong to the partners who have generated them.

Discovery
N/A
C2NET Collaborative Network Manager User Interface (CNM-UI)
Not RTD Tasks associated
C2NET Collaborative Network Manager component (CNM)
T10.4 - Extended Implementation - Potential application in WP10 – zApps for the Use Case 4 - Construction
Business Model Design and Exploitable Results Methodology - MECENUM
T3.2 – Market and Business Opportunity Analysis
T3.3 – Business Models / Business Cases
T3.5 – Exploitation, Strategy and Plans: Individual and Joint
Socio-Economic Impact Assessment - FITMAN (FP7 604674)
T3.4 – Societal/Economic Value and IPR Management
Requirements Setting Methodology
T4.1: Requirements Analysis
T4.3: Architectural Principles and Design
T4.4: Functional Specification
ITI Deploy&Forget WSN
T5.1 - Data Acquisition
Cumulocity IoT
T5.1 - Data Acquisition and IIoT
Data Acquisition and IIoT
T5.1 – Data Acquisition and IIoT
Data Source Registry
T5.1 – Data Acquisition and IoT
Data Source Adapters
T5.1 – Data Acquisition and IoT
Data Source Manager
T5.1 – Data Acquisition and IoT
Secure Installation
T5.2 - Robust Industrial Network Support
ITI Secure Communication
T5.2 - Robust Industrial Network Support
Secure Authentication/Authorisation
T5.2 Robust Industrial Network Support
vf-OS Control: Security
T5.2 – Robust Industrial Network Support
FTPM Portal - Maximum
T5.3 - Data Harmonisation
Multivariate SPC
T5.3 - Data Harmonisation
Olingvo
T5.3 - Data Harmonisation run-time
Data capture strategy of the sensors installed in the machining heads
T5.3 – Data Harmonisation
Ford 4.0 platform
T5.3 – Data Harmonisation
Ford Niagara Data Capture
T5.3 – Data Harmonisation
Forecast algorithms for detecting the Tool
T5.3 – Data Harmonisation
Forecast algorithms for head break detection
T5.3 – Data Harmonisation
ICE Data Platform (IDP) – Runtime
T5.3 – Data Harmonisation
Semantic Reasoner
T5.3 – Data Harmonisation
ICE Data Platform (IDP) – Design Time
T5.3 – Data Harmonisation and Interoperability
CREMA Monitoring and Alerting Component (MON)
T5.4 - Orchestration, Monitoring, and Alerting
Monitoring
T5.4 – Orchestration, Monitoring & Alerting
ARGOS
T5.4 – Orchestration, Monitoring and Alerting
ICE Process Designer
T5.4 – Orchestration, Monitoring, and Alerting
Distributed Computing Component
T5.5 – Autonomous Computing
Autonomous Computing Component
T5.5 – Autonomous Computing
Distributed Computing Component
T5.5 – Autonomous Computing
Application Builder
T5.5 – Distributed & Autonomous Computing
SINGULARITY
T5.5 – Distributed and Autonomous Computing
Autonomous and distributed computing
T5.5 – Distributed and autonomous computing
ITI AI Analytics Runtime
T5.6 - AI Analytics Runtime
Data Analytics
T5.6 – AI-Analytics Designer
Machine Learning Server
T5.6 – AI-Analytics Designer
SDK service connector
T6.1 – SDK Applications and service builder
OCTOPUS
T6.2 - Secure Business Cloud
FIPS
T6.2 – Secure Business Cloud
Marketplace
T6.2 – Secure Business Cloud
Marketplace - Backend
T6.2 – Secure Business Cloud
Storage
T6.2 – Secure Business Cloud
Security Designer (SD)
T6.2 – Secure Business Cloud
Human Collaboration
T6.3 – Human Collaboration Environment
Data Source Manager
T6.3 – Human Collaboration Environment
Data Source Manager
T6.3 – Human Collaboration Environment
Services and Message Bus
T6.4 - Services and Message Bus
Legacy system hub – C2NET
T6.4 - Service and message bus
Apama Streaming Analytics
T6.4 - Services and Message Bus
Universal Messaging
T6.4 - Services and Message Bus
WebMethods Integration Server
T6.4 - Services and Message Bus
ICE ZDMP Application Run-Time
T6.4 – Platform Integration and Federation
ICE ZDMP Application Run-Time
T6.4 – Platform Integration and Federation
ICE ZDMP Portal
T6.4 – Platform Integration and Federation
ICE ZDMP Portal
T6.4 – Platform Integration and Federation
MashZone
T6.4 – Services and Message Bus
API Management
T6.5 – Inter-platform Interoperability
Adamos Service Plugin
T6.5 – Inter-platform Interoperability
ICE ZDMP Interplatform ‘Future Platform’
T6.5 – Interplatform Connectivity
C2NET Optimization
T7.1 - Preparation Stage: Start-up Optimisation
vf-OS IO Toolkit Generator
T7.1 - Preparation Stage: Start-up Optimisation
Statistics software for surface inspection defect analysis and visualisation
T7.1 - Preparation Stage: Start-up optimisation
Prediction and Optimisation Designer
T7.1 Preparation Stage: Start-up optimisation
CET START-UP OPTIMIZATION (CETSTARTOP)
T7.1 – Process Optimisation Run-time
Toolboxes for time series modelling analysis and KPI extraction
T7.2 Production Stage: Equipment Performance Optimisation
Characteristics extraction and quality threshold definition
T7.2 – Production Stage: Equipment Performance Optimisation
Toolboxes for time series modelling analysis and KPI extraction
T7.2 – Production Stage: Equipment Performance Optimisation
Characteristics extraction and quality threshold definition toolboxes
T7.2, T7.4, T8.1, T8.3
CET DIGITAL TWIN (CDT)
T7.3 – Production Stage: Material and Energy Efficiency
T8.1 - Characterization and Modelling
Active learning tool
T7.4 - Process Quality Assurance
Multi-stage modelling
T7.4 - Production Stage: Material and Energy Efficiency
CET DATA PROCESSOR (CETDATA)
T7.4 – Process Assurance Run-time
CET MODEL DEPLOYMENT MANAGER (CETMDM)
T7.4 – Process Assurance Run-time
VSYS AI quality predictor
T8.2 – Pre Production: Product Quality Prediction
VSYS AI Image Classifier
T8.3 – Production: Non-Destructive Product Inspection
VSYS AI Image Labeller
T8.3 – Production: Non-Destructive Product Inspection
VSYS FeaturesAnalysisSuite
T8.3 – Production: Non-Destructive Product Inspection
VSYS MVD MachineVisionDesigner
T8.3 – Production: Non-Destructive Product Inspection
VSYS Silhouette Suite
T8.3 – Production: Non-Destructive Product Inspection
ITI Product Assurance Run-Time - Supervision
T8.4 - Production Supervision
Sensors design and application
T9.2 - Traditional Implementation
Cloud data algorithms
T9.4 - Traditional Implementation
E-CORE platform
T9.4 - Traditional Implementation