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Innovative Modeling Approaches for Production Systems to raise validatable efficiency

Objective

The rise of the system complexity, the rapid changing of consumers demand require the European industry to produce more customized products with a better use of resources.
The main objective of IMPROVE is to create a virtual Factory of the Future, which provides services for user support, especially on optimization and monitoring. By monitoring anomalous behaviour will be detected before it leads to a breakdown. Thereby, anomalous behaviour is detected automatically by comparing sensor observation with an automatically generated model, learned out of observations. Learned models will be complemented with expert knowledge because models cannot learn completely. This will ensure and establish a cheap and accurate model creation instead of manual modelling. Optimization will be performed and results will be verified through simulations. Therefore, the operator has a broad decision basis as well as a suggestion of a DSS (Decision Support System), which will improve the manufacturing system. Operator interaction will be done by a new developed HMI (Human Machine Interface) providing the huge amount of data in a reliable manner.
To reach this aim, every step of the research process is covered by a minimum of two experienced consortium partners, who conclude the results of the project using four demonstrators.
The basis for IMPROVE are industrial use-cases, which are transferable to various industrial sectors. Main challenges are reducing ramp-up phases, optimizing production plants to increase the cost-efficiency, reducing time to production with condition monitoring techniques and optimise supply chains including holistic data. Consequently, the resource consumption, especially the energy consumption in manufacturing activities, can be reduced. The optimized plants and supply chains enhance the productivity of the manufacturing during different phases of production. Furthermore, the industrial competitiveness and sustainability in EU will be strengthened.
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Coordinator

TECHNISCHE HOCHSCHULE OSTWESTFALEN-LIPPE

Address

Campusallee 12
32657 Lemgo

Germany

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 508 000

Participants (12)

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TECHNISCHE UNIVERSITAET MUENCHEN

Germany

EU Contribution

€ 744 670

UNIVERSITA DEGLI STUDI DI MODENA E REGGIO EMILIA

Italy

EU Contribution

€ 372 500

MARMARA UNIVERSITY

Turkey

EU Contribution

€ 249 500

FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.

Germany

EU Contribution

€ 289 199,30

REIFENHAEUSER REICOFIL GMBH & CO. KG

Germany

EU Contribution

€ 329 800

BRÜCKNER MASCHINENBAU GMBH & CO.KG

Germany

EU Contribution

€ 290 625

ARCELIK A.S.

Turkey

EU Contribution

€ 238 000

OCME SRL

Italy

EU Contribution

€ 272 625

TRANSITION TECHNOLOGIES SA

Poland

EU Contribution

€ 178 688

BERNECKER + RAINER INDUSTRIE-ELEKTRONIK GESELLSCHAFT MBH

Austria

EU Contribution

€ 87 843,75

XCELGO AS

Denmark

EU Contribution

€ 279 815

EURICE EUROPEAN RESEARCH AND PROJECT OFFICE GMBH

Germany

EU Contribution

€ 307 287,95

Project information

Grant agreement ID: 678867

  • Start date

    1 September 2015

  • End date

    31 August 2018

Funded under:

H2020-EU.2.1.1.

H2020-EU.2.1.5.1.

  • Overall budget:

    € 4 148 554

  • EU contribution

    € 4 148 554

Coordinated by:

TECHNISCHE HOCHSCHULE OSTWESTFALEN-LIPPE

Germany