1. Technologies and enablers
  2. Information and communication technologies
  3. Data analytics, processing and AI
  4. Data processing
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Data processing is, generally, the collection and manipulation of items of data to produce meaningful information (https://en.wikipedia.org/wiki/Data_processing)

Associated projects

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COMPOSITION | Ecosystem for Collaborative Manufacturing Processes _ Intra- and Interfactory Integration and Automation

01-09-2016

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31-08-2019

Calltopic: FoF.2016.11

: 69 | : 3
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Description One of the most imperative problems so far is to connect supply chain data and services between enterprises and to connect value chain data within a factory so that it can meaningfully support decision-making
  Big data mining and analytics tools I Result title Big data mining and analytics tools I
  Big data mining and analytics tools II Result title Big data mining and analytics tools I Result description On one side, the collection processing and management of data, which is the Big Data Analysis task.
  Interoperability for M2M & HMI in factory environments II Result comments Connected IT and OT IoT enabled SCADA, MOM-MES, ERP (…) connectivity Humans actively connected Human Machine Interfaces Data communication and interoperability Reference docs
  Data processing Taxon title Data processing Search keywords Data processing
  Data acquisition Taxon description Data acquisition systems, abbreviated by the acronyms DAS or DAQ, typically convert analog waveforms into digital values for processing.
    Technologies and enablers
    Advanced manufacturing processes
      Recycling processes
      Comment: Part of the scrap generated by the manufacturing industry is recyclable. The recycling companies need to stay connected with the industries and to plan for the further reselling and/or disposal of the material. COMPOSITION will connect the dots in the inter-factory pilot.
    Mechatronics
      Condition and performance monitoring
      Comment: Continuous monitoring of the condition and performance of specific critical parts (equipment, infrastructure and environment) of the manufacturing system will provide feedback to the real-time brokering and message translations services allowing seamless integration of heterogeneous manufacturing components.
    Information and communication technologies
      Digital manufacturing platforms
      Comment: The COMPOSITION Integrated Information Management System will be a collaborative ecosystem where all members of a manufacturing supply chain can connect in a secure environment. The Security Framework will implement the security core mechanisms aiming to ensure the security, confidentiality, integrity and availability of the managed information for all authorised COMPOSITION stakeholders.
      IoT - Internet of Things
      Comment: The Digital Factory Model (DFM) will provide an integrated representation of the intra-factory domain at machine-level, end-user-level, and process-level. The DFM model will be used to exploit data coming from machinery, sensors and production lines and will offer interoperability in communication by providing all these heterogeneous data in a common format. The DFM is re-used in the Decision Support System, in Simulation and in the Deep Learning Toolkit. The integration of information will enable better use of the data available in the physical layer of the factories to be made.
      Human Machine Interfaces
      Comment:

      Requirements of modern production processes stress the need for greater agility and flexibility, for faster production cycles, increased productivity, less waste and more sustainable production. Human-machine interaction is put in the center, supporting the decision making process.

      Investigation of advanced HMIs for direct interaction with real-world objects. Consideration of mobile user interfaces that allow accessing crucial immediate information everywhere in the factory. Consideration will also be given to data gathering from ultra low power IoT devices such as wireless sensors where data can then be aggregated and visualised at an appropriate HMI interface. Where possible provision for self-powering these IoT devices using energy harvesting will be taken into account in order to avoid battery replacement. Flexible and dynamic data-driven solutions that can be adapted to different environments and needs.

      Results:
      Interoperability for M2M & HMI in factory environments II

      Interoperability for M2M & HMI in factory environments II
        Advanced and ubiquitous human machine interaction
        Comment: Decision makers are not at their desk the whole day. In order to reduce the probability that they miss important information, the project investigates user interface solutions for the shop floor and everywhere else in the factory, in order to provide data monitoring, control and notification systems, that help humans in interaction with machines and with the decision making process.
      Data analytics, processing and AI
      Comment: Big data analytics in cloud environments to support manufacturing scenarios.
        Data acquisition
        Comment: Data acquisition tools to instantiate virtual manufacturing processes.
        Data processing
        Comment: The platform will apply smart data processing methods for investigating the dataset in order to find logical links. It will also investigate novel complex event processing approaches.
        Data modelling
        Comment:

        The COMPOSITION project contains a Digital Factory Model Component which offers representation of factory processes and resources in a common format based on well-known standards.

      System modelling, simulation and forecasting
      Comment:

      A Simulation and Forecasting Toolkit analyses the production processes and required resources in an integrated way and extracts forecasts for possible failures. Also forecasting is provided in supply chain and logistics, especially in fill level monitoring of bins and boosts the waste management and recycling processes. Sustainable manufacturing will be assisted by a Decision Support System. The Marketplace will enable dynamic integration with actors in the supply chain.

      Results:
      Digital Factory Model II

      Digital Factory Model II
      Operating systems
      Comment: Design a technical operating system for the support connected and interoperable factories with their stakeholders and for the optimisation of manufacturing and logistics processes.
      Architecture
        Collaborative and decentralized application architectures and development tools
        Comment: The COMPOSITION project will address the issue of extended enterprises allowing the interaction and collaboration of all stakeholders in the COMPOSITION Marketplace as every business entity will be represented by agents at the ecosystem. Some of information from companies’ IIMS will be reflected at the ecosystem in a Collaborative Manufacturing Services Ontology which will be used as a central knowledge base. The Matchmaker will infer knew knowledge from the knowledge base by applying both syntactic and semantic matching in terms of manufacturing capabilities, in order to find the best possible supplier to fulfil a request. Different criteria for selection according to several qualitative and quantitative factors will be considered.
    Manufacturing strategies
      Innovation
      Comment: COMPOSITION defines innovations at factory performance level, but also at business model level. Collaboration among multi-disciplinary companies will be possible in the ecosystem.

ConnectedFactories | Industrial scenarios for connected factories

01-09-2016

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31-08-2019

Calltopic: FoF.2016.11

: 14 | : 2
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  Key enablers and cross-cutting factors Result description data storage, simulation tools, high performance computing, big data technologies, artificial intelligence, etc… Cross-cutting aspects are described through a comprehensive set of structured
  TRUMPF Smartfactory FBT Feinblechtechnik customer story Result comments Measurable success after just one year   FBT Feinblechtechnik is a flexible job shop in the sheet metal processing industry.
  Data processing Taxon title Data processing Taxon description Data processing is, generally, the collection and manipulation of items of data to produce meaningful information (https://en.wikipedia.org Search keywords Data processing

SAFIRE | Cloud-based Situational Analysis for Factories providing Real-time Reconfiguration Services

01-10-2016

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30-09-2019

Calltopic: FoF.2016.11

: 9 | : 3
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Description The advanced analytics and reconfiguration capabilities to be developed in SAFIRE will be based on mastering the big data challenges associated with manufacturing (sensor and process data), enterprise
  Open Data Use Plan Result title Open Data Use Plan Result description Development of a Data Management Plan (DMP) that details what types of data generated by the project will be open, according to 'Guidelines on Data Management in Horizon 2020'.
  SAFIRE Electrolux pilot: Cloud-driven product optimization Result comments Data acquisition Data processing Data modelling Data analytics, processing and AI Cybersecurity Privacy Safety Resilience Standards Connected Products Production engineering of product Production
  Data processing Taxon title Data processing Search keywords Data processing
  Data acquisition Taxon description Data acquisition systems, abbreviated by the acronyms DAS or DAQ, typically convert analog waveforms into digital values for processing.
  Integration level interoperability Comments OPC-UA plug-in for the data ingestion. External systems can ingest data into SAFIRE solutio by either using pre-developed plug-ins (e.g.

AUTOWARE | Wireless Autonomous, Reliable and Resilient ProductIon Operation ARchitecture for Cognitive Manufacturing

01-10-2016

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30-09-2019

Calltopic: FoF.2016.11

: 13 | : 1
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  D5.1a Pilot site set up and data collection Result title D5.1a Pilot site set up and data collection Result description D5.1 Pilot site set up and data collection (M15, M27)
  D4.3a AUTOWARE Open CPPS ecosystem development Result comments result_rcn_EC deliverableType_EC Documents, reports Standards IEC 20922 (MQTT) OPC-UA Data acquisition
  Data acquisition Taxon title Data acquisition Taxon description Data acquisition systems, abbreviated by the acronyms DAS or DAQ, typically convert analog waveforms into digital values for processing. Search keywords Data
  Standards Comments Automation Industrial Data Space (IDS). Public-subscribe OPC-UA ; OPC-UA rt.

NIMBLE | Collaboration Network for Industry, Manufacturing, Business and Logistics in Europe

01-10-2016

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30-09-2019

Calltopic: FoF.2016.11

: 16 | : 1
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  Distributed Automation: Channel Management for Production Data Sharing Result title Distributed Automation: Channel Management for Production Data Sharing
  Periodic Reporting for period 1 - NIMBLE (Collaboration Network for Industry, Manufacturing, Business and Logistics in Europe) Result description data management from this new perspective.
  Data/object model interoperability - Data exchange formats - APIs Taxon title Data/object model interoperability - Data exchange formats - APIs Search keywords Data Data
  AAA - Access, Authorisation and Authentication Taxon description Authorisation is the process of allowing an entity (humans, systems or devices) to access information systems or facilities where information and processing capabilities are being stored.
  Architecture Comments In addition, processing of the data as it flows into the platform can be performed in real-time.
    Information and communication technologies
      Programming Frameworks – Software Development Kits (SDKs)
      Comment:

      Applied Technologies:

      Spring Boo: Spring Boot is a framework for building web applications. It is built on top of the Spring Framework and follows a zero-configuration principle. The major set of microservices are build using Spring Boot as an application framework.

      Spring Cloud: Functionalities for building and integrating microservices are provided by Spring Cloud. It mainly aggregates components of the Netflix Open Source Software (Netflix OSS) project and makes them easily be integrated with

      Spring Boot applications. Components of the underlying microservice infrastructure are heavily using modules from Spring Cloud (e.g. Service Discovery, Configuration Server and Gateway Proxy).

      Spring Cloud Security: Standardized security mechanisms are implemented using Spring Cloud Security. It provides out-of-the-box integration of security modules to Spring Cloud applications. Authentication and authorization between microservices are realized by using Spring Cloud Security, which supports OAuth2 and OpenID Connect and communicates with the authentication server (i.e. Cloud Foundry UAA).

      ELK Stack Logs can be streamed to Logstash, which stores them persistently in Elastic Search. visualizations are done using Kibana, hence the ELK stack. The ELK stack is used to aggregate log output of distributed microservices in order to centrally perform analysis of generated log output.

      Cloud Foundry UAA: The Cloud Foundry User Account and Authentication (UAA) is a multi tenant identity management service, available as a stand alone OAuth2 server issuing tokens for clients. Cloud Foundry UAA acts as identity and authentication server issuing OpenID Connect tokens.

      Camunda BPM: Camunda BPM is an open source platform for business process management. Camunda BPM is used for the definition and execution of business processes (e.g. supply chain process).

      Apache Marmotta: Apache Marmotta is an open implementation of a linked data platform. Apache Marmotta will be mainly used to store catalog data and perform product-search queries. Apache Solr Apache Solr is a free-text indexing tool providing advanced search and navigation capabilities on the indexed data. Apache Marmotta uses Apache Solr for its semantic search cores composed semantic features of indexed items.

      Docker: Docker is an open-source solution for application deployment, consisting of prebuilt images running inside a container. Docker will be used for intermediate development releases and on-premises deployment.

      PostgreSQL: PostgreSQL is an open-source database system for object-relational data. PostgreSQL will mainly be used as a database technology, in order to have a homogeneous setup.

      Apache Kafka: Open Source messaging infrastructure Mainly used for private communication among components and entities.

      Data management:

      • Product life-cycle management
      • Web objects for IoT data ingestion
        FIWARE
        Comment:

        FIWARE is a reference point concerning available software components.

      Architecture
      Comment: IIRA is the main reference. IIRA is closest in terms of conceptual design for NIMBLE. RAMI is not so applicable to us because we are closer to Internet B2C or B2B platforms. Industrial Data Space is on our radar, but was not sufficiently elaborated at the time of writing the proposal. See https://cloud.effra.eu/index.php/s/NiyTZgM3kw6VCxw The NIMBLE platform is designed to ingest data stemming from edge devices into the platform. Once data has reached the platform, data are stored for future uses such as offline analytics and auditing. In addition, processing of the data as it flows into the platform can be performed in real-time. Offline analytics complements the real-time view by enabling companies to gain insights from their data leading to more efficient processes. We follow the microservice approach for the NIMBLE architecture. Each microservice offers a specific and narrowly defined functionality that is deployed as an independent service [2]. It puts emphasis on real-time application monitoring, including architectural elements and business relevant metrics, e.g. number of orders per minute [2]. In addition, this approach provides decentralized data management and decentralized data storage decisions based on a polyglot persistence method. Microservices can still be combined with monolithic enterprise applications (monolith’s APIs) built as single units, fostering the federation and collaboration of various independent services in the Cloud. Figure 1 depicts the top-level architecture, which is inspired by the microservice infrastructure presented in [3]. Figure 2 then shows the core business services of the platform in more detail. The Gateway Proxy is the public entry point to the microservice application. All user requests are received via the Gateway Proxy and routed to the appropriate service. The Service Logging aggregates log outputs of each individual microservice and makes them available via a Web interface. The Service Monitoring collects data, which are necessary to monitor failures of services; this is implemented using the Circuit Breaker pattern [4]. The Service Monitoring can be used to monitor remote calls, or in any situation where parts of a system need to be protected from failures in other parts. After the number of erroneous executions exceeds a defined threshold, all future calls are immediately returned with an error without the actual function being executed. The Service Discovery enables registration of microservices, as well as mapping between service identifier and the endpoints of instances (e.g. URL or IP address). The role of the Service Configuration is to provide configuration settings for each service. The service communication is enabled either via REST (i.e. HTTP) or by using the Messaging Service (based on Apache Kafka), which provides asynchronous and scalable communication. Finally, the User Account and Authentication (UAA) & Identity Management administrates user identities on the platform. It combines the three standard protocols: OAuth2 for delegated authorization [5], OpenID Connect for session and authentication information [6], and the System for Cross-domain Identity Management (SCIM) for user and group management [7].

Daedalus | Distributed control and simulAtion platform to support an Ecosystem of DigitAL aUtomation developerS

01-10-2016

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30-09-2019

Calltopic: FoF.2016.11

: 9 | : 1
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  Periodic Reporting for period 1 - Daedalus (Distributed control and simulAtion platform to support an Ecosystem of DigitAL aUtomation developerS) Result description data-information towards a predictive model for manufacturing; real-time data collection, analysis, decision, enforcement; optimisation in complex system of systems infrastructures; etc.
  Data processing Taxon title Data processing Taxon description Data processing is, generally, the collection and manipulation of items of data to produce meaningful information (https://en.wikipedia.org Search keywords Data processing

DISRUPT | Decentralised architectures for optimised operations via virtualised processes and manufacturing ecosystem collaboration

01-09-2016

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31-08-2019

Calltopic: FoF.2016.11

: 8 | : 3
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Description The data collected is analysed to detect complex events that trigger automated actions.
  D4.2: DATA ANALYTICS TOOLKIT Result title D4.2: DATA ANALYTICS TOOLKIT
  D2.3: The DISRUPT Platform Integration Plan Result description The plan for the DISRUPT integration is driven by the data and thus it is specified the data-driven integration plan, in which both data semantics and data synchronization are fundamental in the correct
  Data communication and interoperability Taxon title Data communication and interoperability Search keywords Data
  Business model aspects of digital platform deployment Taxon description Another difference is the central role of data for platforms, meaning that data governance is one of the essential elements of the value proposition of platforms.  

ICP4Life | An Integrated Collaborative Platform for Managing the Product-Service Engineering Lifecycle

01-01-2015

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01-01-2019

Calltopic: FoF.NMPB.2014.5

: 10 | : 6
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Description The same component will be used for managing product related data pertaining to the manufacturer, supplier and the customer.
  Periodic Reporting for period 2 - ICP4Life (An Integrated Collaborative Platform for Managing the Product-Service Engineering Lifecycle) Result description needs and no integrated methods exist for the holistic acquisition and processing of feedback information emanating from product-services.
  ICP4Life Designer Component Result comments Furthermore, it will perform a link to different specific legacy CAX tools to circulate the information flow and data sharing or management.
  Data processing Taxon title Data processing Search keywords Data processing Comments Data processing in the platform is manual and done by the user. Decisión is, in most cases, manual.
  Data acquisition Taxon description Data acquisition systems, abbreviated by the acronyms DAS or DAQ, typically convert analog waveforms into digital values for processing.

DIGICOR | Decentralised Agile Coordination Across Supply Chains

01-10-2016

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30-09-2019

Calltopic: FoF.2016.11

: 11 | : 0
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Description The platform will provide seamless connectivity to the automation solutions, smart objects, and real-time data sources across the network.
  D5.8: Data access API & Reference data store (Final Release) Result title D5.8: Data access API & Reference data store (Final Release) Result description to real-time automation data within the manufacturing facilities coming from sensors, controllers (e.g., PLCs), position encoders etc.
  D6.2: Knowledge Protection Specification Result comments Data ownership - data governance Dynamic IT connections to new supply chain partners
  Data ownership - data governance Taxon title Data ownership - data governance
  AAA - Access, Authorisation and Authentication Taxon description Authorisation is the process of allowing an entity (humans, systems or devices) to access information systems or facilities where information and processing capabilities are being stored.
  Data Liability Search keywords Data
  Semantic/information interoperability Comments In order to facilitate the flow of data to and from the middleware, the project will develop Data (harmonisation and transformation) Maps.

vf-OS | Virtual Factory Open Operating System

01-10-2016

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30-09-2019

Calltopic: FoF.2016.11

: 30 | : 0
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Description Software Development Kit (OAK) for Factories of the Future that aims to be the reference system software for collaborative manufacturing and logistics processes including its associated resources and data
  vfOS - ID5.4a - Data Analytics(M18) Result title vfOS - ID5.4a - Data Analytics(M18)
  vfOS - ID3.5a - vf-OS Process Enabler(M12) Result description Delivery will be the repackaging and production of the vf-OS Processing Engine.
  vfOS - ID5.1a - Data Infrastructure Middleware(M18) Result comments result_rcn_EC deliverableType_EC Other Data acquisition Data storage Data processing
  Data processing Taxon title Data processing Search keywords Data processing
  Data acquisition Taxon description Data acquisition systems, abbreviated by the acronyms DAS or DAQ, typically convert analog waveforms into digital values for processing.
  Standards Comments publish-subscribe middleware will provide the data infrastructure and will be fully compatible with major industry standards (i.e.
  Integration level interoperability Comments publish-subscribe middleware will provide the data infrastructure and will be fully compatible with major industry standards (i.e.

Associated results & demonstrators

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