Periodic Reporting for period 1 - MOIRA (MOnItoRing of large scale complex technologicAl systems)
Reporting period: 2021-03-01 to 2023-02-28
Modern technological systems increase in scale and are becoming more and more complex and sophisticated. Parallel, the revolution in electronics, digital technology and communications have drastically modified and expanded the physical diversity, scope, processing capabilities and complexity of the monitoring equipment and infrastructure used. Millions of networked sensors are being embedded in the physical world sensing, creating and communicating data. The amount of data available for capturing has been exploding and the era of Big Data is already here, as the Internet of Things (IoT) is becoming a reality. The main question which arises is how, following which steps and with which tools the data can be transformed to information and knowledge.
The technical-scientific challenges are tough: the development of novel signal processing tools for the monitoring of industrial processes based on machine learning methods applied on heterogeneous time series; the application of data mining technologies for the estimation of Key Performance Indicators which determine the operational profit; the conception, development and validation of methodologies for automated monitoring of cyber physical system fleets; and the multi sensor machine condition monitoring under variable operating conditions.
The MOIRA project (MOnItoRing of large scale complex technologicAl systems) brings together early stage researchers and experienced specialists from key players in academia and industry across Europe covering different scientific disciplines and industrial stakeholders from a broad range of backgrounds to optimally tackle the challenges ahead. The MOIRA Fellows will be trained in innovative PhD topics as well as receiving specific theoretical and practical education in the fields of mechanical engineering and computer science, focusing towards the online early accurate identification of abnormal incidents with minimum false alarms and missed detections.
The general objectives of the project are:
- New signal-processing techniques for the analysis of heterogeneous data structures
- New methods and technologies for the self-learning intelligent monitoring of cyber-physical systems
- New methods for large-scale diagnosis, focusing on data-driven, plant-wide monitoring
- New methodologies for information/sensor fusion, focusing on high-rated diagnosis
- Validation of methodologies for the diagnosis of individual units by fleet monitoring
- Novel data-driven, model-based and hybrid prognostic methodologies
- New methodologies for the condition monitoring of complex systems using low-quality sensors
- New forms of human cognition for the maintenance operations of autonomous machines
- Validation of new methodologies and technologies from the aerospace, mining, automotive, healthcare and packaging sectors
- Bundling knowledge and research activities in the inter/multidisciplinary fields within knowledge discovery involved in the various aspects of the condition monitoring and maintenance of large-scale, complex technological systems.
- Preparing new researchers for challenges ahead in smarter and safer means of transport by equipping them with the skills necessary to compete for high-profile positions in industry.
- Exposing the ESRs to the world of engineering in Europe and providing them with the necessary industrial anchoring.
- Providing a stimulating and balanced training program to the early-stage researchers (ESRs) that includes not just science and engineering, but the important transferrable skills they will need throughout their careers.
- Stimulating interactions to match industrial needs with academic research capacity in an exciting training programme for ESRs.
- Motivating the ESRs through research and training that is simply not available to them anywhere else in the world
- Promoting the transfer of knowledge between the project’s participants and to disseminate, communicate and exploit the research outputs to the fullest extent.
The technical-scientific challenges are tough: the development of novel signal processing tools for the monitoring of industrial processes based on machine learning methods applied on heterogeneous time series; the application of data mining technologies for the estimation of Key Performance Indicators which determine the operational profit; the conception, development and validation of methodologies for automated monitoring of cyber physical system fleets; and the multi sensor machine condition monitoring under variable operating conditions.
The MOIRA project (MOnItoRing of large scale complex technologicAl systems) brings together early stage researchers and experienced specialists from key players in academia and industry across Europe covering different scientific disciplines and industrial stakeholders from a broad range of backgrounds to optimally tackle the challenges ahead. The MOIRA Fellows will be trained in innovative PhD topics as well as receiving specific theoretical and practical education in the fields of mechanical engineering and computer science, focusing towards the online early accurate identification of abnormal incidents with minimum false alarms and missed detections.
The general objectives of the project are:
- New signal-processing techniques for the analysis of heterogeneous data structures
- New methods and technologies for the self-learning intelligent monitoring of cyber-physical systems
- New methods for large-scale diagnosis, focusing on data-driven, plant-wide monitoring
- New methodologies for information/sensor fusion, focusing on high-rated diagnosis
- Validation of methodologies for the diagnosis of individual units by fleet monitoring
- Novel data-driven, model-based and hybrid prognostic methodologies
- New methodologies for the condition monitoring of complex systems using low-quality sensors
- New forms of human cognition for the maintenance operations of autonomous machines
- Validation of new methodologies and technologies from the aerospace, mining, automotive, healthcare and packaging sectors
- Bundling knowledge and research activities in the inter/multidisciplinary fields within knowledge discovery involved in the various aspects of the condition monitoring and maintenance of large-scale, complex technological systems.
- Preparing new researchers for challenges ahead in smarter and safer means of transport by equipping them with the skills necessary to compete for high-profile positions in industry.
- Exposing the ESRs to the world of engineering in Europe and providing them with the necessary industrial anchoring.
- Providing a stimulating and balanced training program to the early-stage researchers (ESRs) that includes not just science and engineering, but the important transferrable skills they will need throughout their careers.
- Stimulating interactions to match industrial needs with academic research capacity in an exciting training programme for ESRs.
- Motivating the ESRs through research and training that is simply not available to them anywhere else in the world
- Promoting the transfer of knowledge between the project’s participants and to disseminate, communicate and exploit the research outputs to the fullest extent.
In WP1, WP2 and WP3, respectively, research on Processing of Heterogeneous Data; Fleet Monitoring; and Multi-Sensor Diagnostics & Prognostics has started up with the activities of the 15 recruited ESR's. First technical deliverables have been reported, illustrating the first technical steps taken.
WP4 focuses on the communication, dissemination and exploitation of the MOIRA results. Already 1 public technical public workshop has been organized. 1 more is planned, as well as 2 public industrial workshops. First conference and journal papers are finding their way to the community, as well as fist public engagement activities - with the latter suffering from COVID restrictions. Nevertheless, the consortium is fully committed to reach out to both scientific and non-scientific audiences to spread the MOIRA message.
WP6 on training is going well. Individual training programs are adjusted to the needs of the ESRs, while all foreseen network wide training courses are taking place. Specific attention is given to applied training.
WP5 and WP7 on management and Ethics run smoothly. Via GA meetings and SB meetings, organized twice a year, the project is followed-up closely.
WP4 focuses on the communication, dissemination and exploitation of the MOIRA results. Already 1 public technical public workshop has been organized. 1 more is planned, as well as 2 public industrial workshops. First conference and journal papers are finding their way to the community, as well as fist public engagement activities - with the latter suffering from COVID restrictions. Nevertheless, the consortium is fully committed to reach out to both scientific and non-scientific audiences to spread the MOIRA message.
WP6 on training is going well. Individual training programs are adjusted to the needs of the ESRs, while all foreseen network wide training courses are taking place. Specific attention is given to applied training.
WP5 and WP7 on management and Ethics run smoothly. Via GA meetings and SB meetings, organized twice a year, the project is followed-up closely.
The project overall will lead to progress with respect to the state of the art in many different aspects, as discussed above.
The project contributes to the re-industrialization of the European manufacturing sector by leveraging on the huge advances in Information and Communications Technology (ICT) that are driving Industry 4.0 Cyber-Physical Systems (CPSs) and the Internet-of-Things (IoT). As sensors become smaller and cheaper, more Original Equipment Manufacturers (OEMs) embed more sensor capability, generating more data. The methods developed in MOIRA will enable to transform this data into information and knowledge, rather than drowning in it.
This project is in line with the “Digital as a Driver for Growth” policy area of the EU priorities. This is to ensure that Europe’s economy, industry and employment take full advantage of what digitalization offers. This requires
investments in ICT infrastructures, such as cloud computing and big data, research and innovation to boost industrial competitiveness, and an inclusive society, with better public services and better digital skills for citizens.
The project contributes to the re-industrialization of the European manufacturing sector by leveraging on the huge advances in Information and Communications Technology (ICT) that are driving Industry 4.0 Cyber-Physical Systems (CPSs) and the Internet-of-Things (IoT). As sensors become smaller and cheaper, more Original Equipment Manufacturers (OEMs) embed more sensor capability, generating more data. The methods developed in MOIRA will enable to transform this data into information and knowledge, rather than drowning in it.
This project is in line with the “Digital as a Driver for Growth” policy area of the EU priorities. This is to ensure that Europe’s economy, industry and employment take full advantage of what digitalization offers. This requires
investments in ICT infrastructures, such as cloud computing and big data, research and innovation to boost industrial competitiveness, and an inclusive society, with better public services and better digital skills for citizens.