Manufacturing SMEs sought for open call for agile robotized manufacturing under subcall of H2020 Innovation Action

REQUEST from Germany, reference: RDDE20191220001, valid from 07-01-2020 untill 31-01-2020

Research & Development
  • Start date:
    7 januari 2020
  • End date:
    31 januari 2020
  • Summary:
    A German company is looking for a manufacturing SME that would like to complete a use case on data-driven robotics via a digital twin solution funded by the DIH², a network of Robotics Digital Innovation Hubs for Agile Production. Digital twin is a computerized version of a physical asset or the poduction process based on data collected by sensors. The German company specializes in using this data for the creation, sharing and monetization of value. The partner needs to supply a use case.
  • Description:
    The German SME aims at providing data-driven solutions for agile robotized manufacturing. The contribution
    of the company to the project will be the development of a data management that enables well-informed and enhanced robotized processes in manufacturing applications. The concept of digital twin is at the heart. The sought partner needs to supply a manufacturing use case for which a digital twin, the digital version of the physical asset or the poduction process based on data collected by sensors, can be created. The multipurpose and scalable usage of the digital twin is beneficial to manufacturing SMEs when it comes to collect, share, retrieve and integrate heterogeneous data and information on robotic assets and manufacturing processes to enable competitive advantages.

    Vertically, SMEs will be able to use digital twins to acquire, expose, analyze and consume data to enrich their robotized applications. Data will be gathered using connectors while preserving the privacy of their owners. Each data owner decides which data from her/his local data catalog are exposed.

    Horizontally, data-driven digital twins shared among partners will be networked to offer a comprehensive and meaningful knowledge base and information flow within the system. Hence, manufacturing SMEs can take advantage of the previous experience of other companies in robotized manufacturing.

    The project will be funded by DIH², a Pan‐European Network of Robotics DIHs for Agile Production. The project duration is 10 month and the project budget is 248000 Euros. Call deadline is February 27, 2020, hence the EOI deadline is January 31, 2020. The call is looking for consortia of at least two and up to three eligible organisations. At least one Manufacturing SMEs/Slightly Bigger Company and one Technology Provider must be part of the consortium. The German company will take the role of Technology Provider. They are looking for a manufacturing company to supply the use case and build a consortium of two.

Partner Sought
  • Type of Partnership Considered:
    Research cooperation agreement
  • Technical Specification or Expertise Sought:

    The German company is looking for European SMEs working in the manufacturing field. The SME needs to supply a use case on which the project will be build. Data-driven robotics shall be the core solution in the use cases they want to complete in the joint project. Machine (i.e. robot, etc) and process data as well as metadata shall be accessible on the end-user side. Their integration and processing will lead to digital twins exploited to deliver advantages for efficient robotized processes in manufacturing. Therefore, targeted benefits shall be quantifiable. Algorithms for data processing can be provided by the end-users. The German company invites end-users to share their needs in their robotized manufacturing with them for a joint adjustment of the project objectives.

    SME 51-250

  • Development stage:
  • IPR Status:
  • Market keywords:
    Business products and supplies
    Hardware, plumbing supplies
    Packing products and systems
    Other manufacturing (not elsewhere classified)
  • Technology keywords:
    Automation, Robotics Control Systems
    Digital Systems, Digital Representation
    Data Processing / Data Interchange, Middleware
    Data Protection, Storage, Cryptography, Security
    Knowledge Management, Process Management
  • NACE keywords:
    Computer consultancy activities
    Other information technology and computer service activities
    Data processing, hosting and related activities
    Web portals
    Other information service activities n.e.c.
  • Advantages and Innovations:
    Digital twins, the computerized (or digital) version of a physical asset and/or the poduction process based on data collected by sensors, will semantically link various data types and information (e.g. blue prints, images, trained AI-models, work-cell settings, simulation models, billing of materials, sensor measurements, safety measures, etc.) associated with
    robotized assets as well as design, engineering and production processes. On this basis, new knowledge will be inferred and well-informed solutions derived. These include collecting relevant data for AI-based manipulations, detecting missing components in tasks planning, identifying hazards overseen by humans during robot programming, anticipating human action in human robot collaboration, predictive maintenance and strengthening Enterprise Resource Planning (ERP)/Manufacturing Execution Systems (MES).

    Through e.g. a knowledge graph the manfucaturing SMEs can learn from and take advantage of the previous experience of other companies in robotized manufacturing and contribute to growth and technology transfer in the ecosystem by sharing their own data. This will foster data-driven robotics in the manufacturing domain.
  • Type and Size of Organisation:
    Industry SME 11-49
  • Already Engaged in Trans-National Cooperation
  • Year Established:
  • Turnover:
  • Country of origin:
  • Languages spoken
    • English
    • German
    • French
  • Project Title and Acronym:
    Data-driven Robotics for Manufacturing
  • Coordinator Required
  • Deadline:
    27 februari 2020
  • Submission and evaluation scheme:
  • Prebudget:
  • Website: