Workplan

FIREMAN will be structured around five interrelated technical Work Packages (WPs) in addition to one WP for management and one for dissemination and exploitation of results, which directly stem from the general project objectives. Each WP will be coordinated by a WP leader and task leaders guided by concrete objectives with a clear time roadmap. The inter-dependencies between the WPs and the holistic approach of the FIREMAN workplan are illustrated in the following figure:

WP1 will ensure the accurate fulfilment of FIREMAN objectives. This horizontal WP will track the progress of the overall project to guarantee coherent outputs in time. WP2 will detail the system architecture and use cases, thoroughly analyse their requirements and define key performance indicators. It is expected to define a fundamental starting point for the subsequent thorough investigations in WP35.

WP3 will focus on the collection and acquisition of heterogeneous data captured by many sensors embedded into various devices and machines in the physical world. This WP will further investigate secure ultra-reliable data transfer and communication while network architecture aspects will be also considered. Aggregated sensor data combined with data fusion, mining, and interpretation will enable efficient control and awareness of the physical processes. This is the objective of WP4 where advanced machine learning techniques will be developed to convert the pre-processed raw sensor data to useful information and allow for preliminary analysis and short-term operational decisions.

WP5 will focus on employing big data analytics and artificial intelligence for statistical analysis and knowledge processing to detect/predict/prevent rare events and propose techniques for actuator response. In WP6, the project aims to demonstrate in real demos how the proposed techniques investigated in WP35 can enable the achievement of the project objectives.

FIREMAN aims to guarantee high impact at all levels, namely, technological, academic, societal, and economical. To this end, a detailed dissemination plan will be traced and executed along the project within WP7 where the consortium will promote the widescale adoption of the proposed solutions.

Consortium

The FIREMAN consortium comprises 6 partners located in 4 European countries, consisting of 3 universities, 2 research centers and 1 automotive company. The composition of FIREMAN consortium has been carefully selected in order to include all necessary competences and resources to carry out research at the intersection of wireless IoT connectivity and machine learning towards end-to-end predictive and automated industrial systems. Complementary skills among the partners have been chosen to span the sufficient space of cross-disciplinary expertise required by FIREMAN to successfully carry out the project objectives and create impact.

Lappeenranta University of Technology

Lappeenranta University of Technology (LUT) is the FIREMAN project coordinator. LUT is involved in all WPs. Besides management and dissemination, LUT is involved in the system architecture, physical system modelling, data acquisition and sampling strategies, data aggregation transmission and compression, visualization of rare events, as well as in the integration tests in its industrial settings (e.g., bearing condition monitoring, pump, blower and compressor faults and wind turbine maintenance).

Athens Information Technology

Athens Information Technology (AIT) leads the FIREMAN technical management activities. Prof. Papadias is the Technical Coordinator of the project. AIT leads WP5, and in particular Task 5.1 where most of the research on developing novel beyond state-of-the-art machine learning and data mining methods for detecting rare events that imply the need for predictive maintenance in smart industry will be carried out. AIT leads also Task 2.3 in WP2, with a focus on deriving theoretical properties on the processes generating events for the algorithms of Task 5.1 to be able to reliably detect them.

Centre Tecnològic de Telecomunicacions de Catalunya

Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) is the WP3 leader in FIREMAN. CTTC coordinates the research activities of WP3 as well as contributes to both Task 3.1 and Task 3.3 with data modelling and data transmission protocols, respectively. In addition, CTTC contributes to WP2 by defining scenarios and KPIs, to WP4 by designing data fusion algorithms, and to WP6 by working closely with SEAT in the pilot activities. CTTC actively contributes to the project’s dissemination activities. 

Trinity College Dublin

Trinity College Dublin (TCD) leads WP4 and Task 4.2, focusing on developing distributed filtering approaches for data reduction and machine learning techniques for dimensionality reduction. TCD leads Task 5.3, focusing on maintenance schedule optimization. TCD is part of Task 7.1 leveraging CONNECT’s powerful networks, industrial partnerships and additional multipliers channels to raise the visibility of FIREMAN.

University of Oulu

University of Oulu and, in particular the Centre for Wireless Communications (CWC), leads the activities of WP6 as well as Task 4.1, and contributes to WP2-WP7 of FIREMAN. UOULU is involved in the physical system modelling, data gathering (event based and clustering), in developing stochastic data aggregation and compression and coordinates the activities for deployment in industrial settings.

SEAT

 

SEAT will provide a key manufacturing challenge for which innovative solutions based on Internet of Things and Artificial Intelligence will be required. The challenge will be related to predictive maintenance of production machines (such as, painting robots, presses, etc.) and will consist in how to automatically detect and predict when a given machine will stop working. SEAT will define the requirements of the predictive maintenance use case and will provide production data so that other partners of the project can develop the best solutions. Then, SEAT will integrate, test, and validate the proposed solutions in its facilities, in controlled environments. In addition, SEAT will contribute to the dissemination of results by posting updates about FIREMAN in social networks and giving talks and presentations about the project in top-level industrial congresses, fairs, and industrial events (such as, Internet of Manufacturing, Advanced Factories, IoT Solutions World Congress, Mobile World Congress, etc.), in Volkswagen Group guild meetings, and in universities and research centers to strengthen the importance of collaboration between academia and industry. All in all, SEAT will contribute in all technical WPs as well as in the dissemination activities by defining the plan for the exploitation of FIREMAN results in WP7.

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