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Reality-Connected Machine Simulation of Heavy Machinery

The RealSim project proposal aims to connect machine simulation to reality in the framework of heavy machinery, which is an interdisciplinary application. The results of this project are expected to optimize machine performance, accurately and reliably predict machine failure, and reduce overall development and operation costs, thus, serving the Europe’s priority of green transformation and the United Nation’s sustainable development goal 9. The RealSim project will close the gaps of: (1) Onboard estimations of force and pressure components of heavy machinery; (2) Estimating deformability, cylinder friction, leakage, and valve dynamics of heavy machinery using independent nonlinear Kalman filters; (3) Employing dependent nonlinear Kalman filters in state estimators of heavy machinery; (4) Tuning algorithms for the covariance matrix of plant noise in the state estimation of heavy machinery. 

I will consolidate and leverage my research career and position as a leading researcher in the field through integration in Assoc. Prof. Mohammad Poursina’s group at the Department of Engineering Sciences of the University of Agder (UiA), Norway. Here, I will acquire hands-on experience of working with actual mechatronic systems and develop efficient control algorithms. I will improve my knowledge of fluid power designing, control theory, instrumentation, and develop efficient coding skills. I will also develop entrepreneurial skills. The skills, knowledge, and international network that I will develop during this fellowship will put me in an excellent position to achieve my long-term goal of becoming a professor with my own independent research group at an esteemed university in EU. This fellowship will help me to prepare a strong ERC Starting Grant application in the future. It will also cater my additional goal of setting-up a research-related start-up in the future.

Algebraic Theory of Information Quantities

Information theory is a discipline at the intersection of statistics, engineering and computer science. As the study of information quantities, such as compression or communication capacities, information content or measures of statistical dependency, it is one of the theoretical underpinnings of data science.

Computational problems in information theory are highly non-linear. The goal of this project is to transfer state-of-the-art methods of computational non-linear algebra to information theory, to study the inherent algebraic complexity of information-theoretical problems and to provide tools for solving them in practice. The algebraic point of view has proven to be fruitful in seemingly unrelated areas, as witnessed by a surge of recent work in algebraic statistics, in particular on likelihood geometry. However, maximizing the likelihood function is the same as minimizing relative entropy — a specific information quantity. Hence, this project also aims at generalizing the techniques developed in likelihood geometry.

One focus is on the practical computation of information quantities using numerical and differential algebraic geometry. Such quantities are defined via non-linear optimization problems and we aim to pinpoint the algebraic complexity of these problems in instances of general interest, such as common information measures. The final objective is finding fundamental laws and limits of data science imposed by non-linear inequalities constraining the entropic region. These inequalities provide, by duality, universal bounds for many of the optimization problems studied in information theory.

WHeelchair Activity Monitoring project (WHAM)

Wheelchair users (WCU) are three to five times more inactive than the general population, leading to a high risk of developing preventable secondary conditions. Although physical activity (PA) guidelines have been specifically developed for WCU, we lack systematic approaches to implement them in practice, as well as valid algorithms to monitor PA change in WCU through sensor-based solutions. Accordingly, the overall scientific aim of the WHeelchair Activity Monitoring project (WHAM) is to advance PA research and practice in WCU by developing valid digital markers for monitoring of and providing feedback on PA, paving the way for implementation and intervention. I will accomplish this through combining the complementary research fields of 1) behavioural intervention studies focusing on increasing PA in WCU (core competence University of British Columbia, UBC; outgoing phase) and 2) sensor-based PA monitoring (core competence Norwegian University of Science and Technology, NTNU; returning phase – consolidated by non-academic placement at Maastricht Instruments, which develop research prototypes including PA monitors). WHAM’s scientific aim is achieved through three objectives: 1) Measure the effect of a pragmatic exercise intervention trial on self-reported physical activity levels and cardio-respiratory fitness, 2) Develop valid algorithms for tracking PA markers in WCU, and 3) Co-create a framework that outlines how PA can be conjointly monitored and provided feedback on in WCU. This fellowship will enable me to become established as an internationally recognized researcher in the field of “physical activity and disability”, while bringing together ongoing national disjointed research activities in this field. Altogether, my overall ambition is to contribute to reducing inequalities in daily-life participation among WCU compared to the rest of the population.

EOSC Beyond: advancing innovation and collaboration for research

EOSC Beyond overall objective is to advance Open Science and innovation in research in the context of the European Open Science Cloud (EOSC) by providing new EOSC Core capabilities allowing scientific applications to find, compose and access multiple Open Science resources and offer them as integrated capabilities to researchers. To do so, EOSC Beyond supports a new concept of EOSC: a federated and integrated network of Nodes operated at different levels, national, regional, international and thematic, to serve the specific scientific missions of their stakeholders. Further specific objectives of the project are to accelerate ‘time to product’ of new scientific applications with software adapters, enable Open Science with machine composability and dynamic deployment of shared resources, support innovation in EOSC with a testing and integration environment, and align the EOSC Core architecture and specifications to integrate with European dataspaces. The project extends the state of the art of the EOSC Core and adopts a co-design methodology, including requirements elicitation, software development and validation in collaboration with different use cases from EOSC national and regional initiatives (e-Infra CZ, Czechia, NFDI, Germany, and NI4OS, South East Europe region), thematic research infrastructures from Social Sciences and Humanities (CESSDA), Life Sciences (CNB-CSIC and Instruct-ERIC), Environmental Science (ENES and LifeWatch), and Health and Food (METROFood-RI). EOSC Beyond builds on the capacities of prospective EOSC Nodes and partners with multi-annual experience in developing solutions for large-scale federated digital infrastructures and aligns with the technical architecture and requirements of data spaces from different business sectors. Ultimately, EOSC Beyond supports Open Science in modern, data-intensive, and multidisciplinary research, facilitating resource discovery, access, and reuse across scientific communities, organisations, and countries.


Harmonization of Advanced Materials Ecosystems serving strategic Innovation Markets to pave the way to a Digital Materials & Product Passport

The overarching objective of DigiPass is to enhance the digital maturity of the European communities that develop materials and intermediate products. The project will develop recommendations and clear routes toward digitalized circular business models. The overarching key result of DigiPass is to create a sustainable platform which includes support for Digital Materials & Product Passport and for collaborative innovation-by-design processes in a circular economy served by advanced materials. A business model for operating such a platform completes the overarching objective.
DigiPass is harmonizing and synergizing collected materials data sources and digital infrastructures. This will enable interoperability of data exchange, and standardization of advanced materials knowledge representation at all maturity levels. Accelerating the design, development, and production of advanced, safe, and sustainable chemicals and materials, as they are necessary for innovative products, calls for a collaborative approach involving different stakeholders to support durability, repair and overhaul, reuse, and recyclability of products. DigiPass project impacts all materials development communities over the whole circular value chain. 


Enhanced X(cross)-disciplinary Community-driven Imaging Technologies for Earth and Environmental material research

The EXCITE² Network is revolutionizing Earth and environmental material science research by consolidating a critical mass of 18 research facilities in 12 European and associated partner countries into a unified infrastructure and providing transnational access to advanced imaging technologies. This enables scientists to decipher complex processes within Earth materials at scales from nanometres to hundreds of centimetres, gaining unparalleled insight into the chemical and physical processes that govern, among others, environmental toxicity and its impact on human health, critical metal extraction for renewable energies, and the utilisation of Earth materials as long-term storage for climate-altering gases. The consortium fosters knowledge-sharing and talent attraction, bolstering the problem-solving capacity of the European Research Area. Moreover, EXCITE² is driving interdisciplinary collaboration and cross-fertilisation across academic institutions, scientific disciplines, and industry, propelling Europe towards a sustainable future. The initiative offers dedicated training programmes to a new generation of researchers within the European open science landscape, paired with access to world-class imaging facilities and expertise for problem-solving research and innovation. EXCITE² is introducing innovative service developments, such as artificial intelligence and leading-edge imaging experiments, to increase the user's problem-solving capacity. In addition, the consortium is implementing customised project valorisation strategies to maximize the impact of research outcomes in academia, society, and the economy. Citizen science projects allow the public to participate directly within the EXCITE² Network, contributing to solving EU challenges. As such, EXCITE² is paving the way towards a sustainable future, driving scientific excellence, and creating positive societal impact.

Engineering carbon quantum dots for zinc ion hybrid capacitors

Zinc ion hybrid capacitors (ZIHCs) integrate two energy storage mechanisms of battery-type electrode and capacitive electrode, bearing the advantages in energy density, power density, and safety. Until now, the cycle retention rate of ZIHC's capacity reported is still not more than 80%, restricting its development and commercial application severely. Focusing on the issue, the project aims at overcoming the limitation of traditional electrode materials and re-defining the designing concept to construct Carbon Quantum Dots (C-QDs) for ZIHCs. Advanced methods will be used to harvest carbon quantum dots from coal tar pitch (a sort of industrial solid castoff). The bulk sp2-carbon network, innumerable edge sites, profuse surface functional groups, and regular size ensures that as-synthesis C-QDs have high electrical conductivity, sufficient ion transport channels and rich adsorption sites. Moreover, the new concept of dynamic evolution is introduced for insight into the structure and interface failure of ZIHC's electrode. The interface-reconstruction mechanism and the attenuation model of capacity will be established for the first time. Further, the methods to strengthen structures of C-QD electrode will be developed based on a trade-off strategy. The ultimate goal is to improve the energy storage efficiency of ZIHCs by 20% and to increase their cycle performance more than 95% unprecedentedly. This research will develop long-running high performance ZIHCs, for contributing European energy storage industry. The ER will achieve abundant research experience and scientific skills from the project and the capability to launch her own research group in future.

IMProving User experience, Long-term sustainability and Services of EU-OPENSCREEN

EU-OPENSCREEN (EU-OS), the distributed European Research Infrastructure for Chemical Biology and early drug discovery, provides world-class services in high-throughput compound screening and medicinal chemistry to users from academia and industry. As one of the largest open-access initiative globally, EU-OPENSCREEN plays an increasingly important role in facilitating early stage drug discovery in Europe. It recently integrated fragment-based drug discovery and chemoproteomics as two new services, but the increasing complexity of modern drug discovery projects requires an even more comprehensive portfolio and integration of emerging technologies. To ensure that EU-OS continues to offer a comprehensive suite of relevant services and support a growing user community to conduct forefront research, IMPULSE will develop, validate and integrate new services in AI/ML, new chemical modalities, and innovative disease-relevant cell models combined with CRISPR-Cas9/RNAi-based genetic screening. IMPULSE will work towards the implementation of common operational and data standards to increase data reproducibility and FAIRness. Bespoke outreach and training activities will raise awareness among key user groups of its new services and advance operational excellence and reproducibility in pre-clinical drug discovery. New models for pre-competitive drug discovery with industry or charities, and growing ERIC member community will reinforce the sustainability and accessibility of EU-OPENSCREEN.

Aqua Research Infrastructure Services for the health and protection of our unique, oceans, seas and freshwater ecosystems

AQUARIUS will provide a highly comprehensive suite of integrated research infrastructures appropriate to addressing significant challenges for the long-term sustainability of our unique oceans, seas and freshwater ecosystems. For the first time, diverse research infrastructures will be combined to facilitate the work of researchers and key stakeholders focused on challenges and opportunities for both marine and freshwater systems. An impressive range of 57 research infrastructure services will be made available to include research vessels, mobile marine observation platforms, aircraft,  drones, satellite, sensors, fixed freshwater and marine observatories and test sites, experimental facilities, and sophisticated data infrastructures. AQUARIUS will support the development phase of the EU Mission to Restore our Ocean and waters by 2030, the Sustainable Blue Economy Partnership, the European Green Deal, and international climate initiatives. It will also be an essential component in achieving the European Digital Twin of the Ocean and the UN Decade for Ocean Sciences. The needs of researchers will be met through a robust and transparent system of transnational access funding Calls, facilitated by centralised user-friendly access portal. The Call programme will be informed through stakeholder engagement and brokerage events. Projects to be selected for Access must convincingly integrate multiple infrastructures and contribute to the core policy objectives of Mission Ocean, that is, to protect and restore marine and freshwater ecosystems and biodiversity; to prevent and eliminate pollution of our oceans, seas and waters; and to ensure a sustainable, carbon-neutral and circular blue economy. A thematic and geographic focus will be the hallmark of the proposed transnational Calls, aligning with the Lighthouse Regions, that is, the Baltic and the North Sea Basins, Black Sea, Atlantic/Arctic, and Mediterranean Sea along with their associated rivers.

EOSC-ENTRUST: A European Network of TRUSTed research environments

The mission of EOSC-ENTRUST is to create a European network of trusted research environments for sensitive data and to drive European interoperability by joint development of a common blueprint for federated data access and analysis. 
Countries and institutions have made significant investments in secure and trusted data environments to meet the need for research and policy-driven analysis of sensitive datasets such as people's health and socio-economic status, the habitats of vulnerable species and geo-spatial locations of protected sites. There are now a large number of such secure environments in operation - linked to national centres, individual organisations or specific research communities. This fragmented landscape poses challenges for both users and providers: researchers are faced with a large number of different systems and access procedures; providers need to manage federated access across multiple, potentially incompatible, technology and governance frameworks.
EOSC-ENTRUST brings together providers of operational Trusted Research Environments from 15 European countries with a shared goal to implement, validate and promote their capabilities through a common European framework using shared standards and common legal, operational and technical language. This blueprint for interoperability is anchored in the EOSC Interoperability Framework spanning the four dimensions of Legal, Organisational, Technical and Semantic interoperability. EOSC-ENTRUST has identified four driver projects covering Genomics, Clinical trials, Social science, and public-private partnerships to benchmark capabilities, inform blueprint design and demonstrate secure  data analysis using federated workflows.
Targeted outreach activities will expand this open network with further providers and develop policy papers and guidelines for the full range of stakeholders to create a long-term operational TRE framework within the European Open Science Cloud.


Sosiale lisenser for akvakultur

Midlene fra HAVBRUK2-Stort program for havbruksforskning fordelt på år

Midlene fra HAVBRUK2-Stort program for havbruksforskning fordelt på fylker

Midlene fra HAVBRUK2-Stort program for havbruksforskning fordelt på fagområde

Research Director

SoLic – Social license in aquaculture - has investigated conditions, mechanisms and consequences of social licenses in the aquaculture sector. A social license is understood as expectations and requirements that apply to a sector and how the public perceives that their expectations are met. Obtaining and maintaining a social license for aquaculture is a two-way process where society's knowledge of and understanding of the aquaculture industry must be strengthened, while the industry must acknowledge its social responsibility and be in dialogue with its surroundings about how they affect society, including the environment. The Solic project has contributed to putting the concept of social license and the associated theoretical foundation on the agenda in research on aquaculture in Norway. The project has also carried out the first international comparative study of social license (Norway, Tasmania (AU) and Iceland). The results from the survey here in Norway show that the population is basically positive about the industry. This also applies to areas, such as in the larger cities, where it has previously been assumed that the population has a more negative attitude. In addition, the study has given us the opportunity to look more closely at the difference between respondents who live near aquaculture production (measured at the municipal level) and respondents who do not. Here, the results show that those who live near aquaculture production generally report better knowledge of the industry and a better general impression of the industry. At the same time, we see that this proximity to the industry does not have a positive effect on all variables, and it is important to take into account that the industry operates in many different contexts, e.g. both densely populated municipalities and very rural municipalities, and with varying degrees of economic importance in the municipality. In the comparative study, we find that contextual factors must be considered significant for different perceptions of the industry. At the same time, we also find that some consistent challenges exist across the national context, and these will be important to deal with in order to improve the industry's social license at global, national and local level. This mainly applies to the perception of the industry's environmental impact, and the distribution of financial gains. Furthermore, the study shows that large sections of the population experience having limited knowledge about aquaculture, which we find correlates with attitudes towards the aquaculture industry. Here it is particularly surprising that respondents in Norway do not score higher, as the industry's production and presence is on a much larger scale here. Our analyzes show that information and knowledge are significant factors in the work with, and the assessment of, the industry's social license. We have also compared the survey results with data on economic conditions in different municipalities and on magnitude of aquaculture production in the same municipalities. We find here that the population is more positive about aquaculture the more production there is in the municipality they live in. At the same time, we find that the same respondents tend to be more skeptical about whether the economic distribution is fair.

Perceptions of an industry or its social license are shaped by many different factors, and it is sometimes difficult to know whether people's perceptions are in line with actual conditions. In Solic, we find that sustainability and the distribution of economic benefits are two topics that particularly affect perceptions in a negative direction. Based on local survey data, and detailed data on the Norwegian salmon farming industry, we therefore examine a number of indicators to measure the reality of these concepts, i.e. economic importance for the coastal communities (employment, value creation, ripple effects, etc.) and environmental pressures that are particularly visible locally; locations, emissions, disease, lice infestation, escape etc. This work is in its final phase and seeks to illuminate the extent to which these perceptions about sustainability and economic distribution can be explained by facts and actual development.

The project has also contributed to theoretical development. In the social license literature, trust-based models for understanding and explaining the level of social acceptance/social license are dominant, but these have mostly been used in other industries and contexts (primarily mining in Australia, China and other countries). We have therefore used our results from surveys in two counties in Norway to test whether the models are suitable for the aquaculture industry in Norway. We find that the trust-based models have limited explanatory power for social acceptance of Norwegian aquaculture, and we have developed and tested an alternative model for social acceptance that better explains the empirical evidence.

SoLic will investigate the determinants, mechanisms and consequences of social license in the aquaculture industry. Social license is understood as the expectations and requirements that apply to a sector and how the public perceives the fulfillment of these expectations. Earning and sustaining social license for aquaculture is a two-way process where society's knowledge about and understanding of the aquaculture industry need to be strengthened, while the industry must acknowledge its social responsibility and respond to signals from society. We suggest investigating determinants and consequences of social license, and the mechanisms behind them, on three levels: the macro, meso and micro, while also taking into account the complex mix of stakeholder interests and values. SoLic will bring together a multidisciplinary group consisting of national and international experts for this work. It will draw upon relevant academic and policy literature, a qualitative survey at the national and regional level, analyses of highly visible mediatized events, in-depth case studies at the local level, and mirroring these analyses in Norway; comparative case studies from abroad. At the macro level, we will investigate public perception of the industry, and the public’s trust in both the industry and public regulation (WP1). At the meso level, we will investigate how and to what extent specific mediatized events influence social acceptance and trust in the industry (WP2). At the micro level, we will study the local social license, ripple effects and case studies on capital income flows and their reinvestment (WP3). Findings from WP1-3 will be employed to investigate industry strategies for the industry to improve their social license and to conduct an international comparison of social license in aquaculture in Norway, Iceland and Tasmania (WP4). SoLic’s project members have excellent publication records, and are active in engaging with stakeholders both in Norway and abroad.

Social License to operate for aquaculture

Production lines and machines are getting more and more complex. Information is spread out over a physical and a digital world and is difficult to combine. To access that information, operators need to continuously switch context. The need of data visualization tools is identified, data should be relational, interactive, clear and accessible. Using the advantage of XR, data can be presented using 3D space, with intuitive UI will save time for performing tasks/trainings. Using XR just the needed information is shown for each moment, in real time and in the right place, user will have the necessary information to make decisions and to work more efficiently. 
Solutions for Virtual-, Augumented- and Mixed Reality will also be applied in non-industrial settings like education and cultural heritage. Access for visitors with disabilities to all rooms of museums within buildings with difficult access, combining virtual/real exhibitions, with multiuser interaction and real time guiding. The platform will enable the user to share a unified experience via virtual presence
Digital Twin oriented metaverses will allow for creation of metaverses for education, where users will be able to set up buildings/training rooms with different immersive experiences, as well as collaborative meeting/training rooms in which they will be able to engage students in different immersive experiences.
The application of metaverse technology will be used to design collaborative environments with rich interaction methods including voice and chat communication with real-time translations and tactile communication.
Interactive Technologies such as Augmented (AR) and Virtual Reality (VR) are set to transform the ways in which people communicate, interact and share information on the Internet and beyond. This will directly impact a larger number of European industries ranging from manufacturing, construction, engineering, to education, entertainment, media and culture, enabling new business opportunities

XARMONY - Human Augmented Reality: Museum, educatiON & industrY.
HORIZON-CL4-2023-HUMAN-01-21: Next Generation eXtended Reality (RIA)

Hydropower is one of the renewable energy sources that have the highest conversion efficiency , contributing approximately 16%–17% of the total world electricity generation. Operations’ Monitoring and Maintenance Recommendations (M&M) are an important aspect for their efficient working and life expectancy, in the sense that ineffective processes (in M&M) can result into major problems: e.g., leading to electricity generation and revenues losses, producing threats to employees and public safety, etc. The M&M processes are usually data-driven, involving the analysis of data points, such as: daily fault reports, trends of operating parameters (retrieved from sensors), and system efficiency. We present the different stages involved in the maintenance activities of hydropower plants : diagnosis, planning, objectives selection, list maintenance activities, cost estimation, tender allocation, validation and implementation, and restoration of the system. The maintenance of hydropower plants can be categorized into two parts: (a) preventive maintenance, and (b) corrective maintenance. Preventive maintenance can be further classified into planned, conditional and predictive maintenance, whereas corrective maintenance is employed in emergency situations. Based on a recent literature review on the topic1, the preventive maintenance and operation optimization recommendations are provided through various condition-based monitoring techniques, such as: Fuzzy Logic, AHP, PSO, ANN, and SOM. Whereas, the usual technologies used for enabling remote monitoring and fault analysis are: SCADA, IoT, and cloud-based monitoring systems

Hydropower Plants Operations’ Monitoring & Maintenance Recommendations through Digital Twins, empowered with eXt. Reality and eXplainable AI

Thanks to the advances in information technology, modern industrial systems are becoming increasingly intelligent and autonomous; thus, their requirements for, e.g., correctness, availability, reliability, are also increasing. Monitoring, analysis and diagnosis of such industrial systems became pivotal and fueled the development of virtualization and simulation solutions such as digital twins.
In a nutshell, digital twins are virtual representations of actual systems or processes that serve as real-time digital counterparts for, e.g., prediction, analysis, testing, simulation. Developing digital twins is a complex process. On the one hand, it includes developing digital twins at different levels of abstraction of the system to allow one focusing on different relevant aspects (e.g, behavioral, logical, physical). On the other hand, it must ensure the correctness of digital twins with respect to the system specifications and the respective level of abstraction.
This project addresses the above-mentioned challenges by i) automating the creation of digital twins for the simulation, monitoring and testing of functional and non-functional properties, ii) validating digital twins to meet the required properties and iii) developing a multi-domain and automated digital twin toolchain for the verification and validation of complex industrial systems based on digital twins. We foresee that this project will positively impact the efficiency of such systems by reducing their time-to-value and by increasing their final quality.

MATISSE - Model-based engineering of Digital Twins for early verification and validation of Industrial Systems
HORIZON-KDT-JU2022-2-RIA

Production lines and machines are getting more and more complex. Information is spread out over a physical and a digital world and is difficult to combine. To access that information, operators need to continuously switch context. The need of data visualization tools is identified, data should be relational, interactive, clear and accessible. Using the advantage of XR, where data can be presented using the 3D space, with intuitive UI (where not manuals are needed) will save time for performing tasks and trainings. Using XR just the needed information is shown for each moment, in real time and in the right place, the user will have the necessary information to make decisions and to work more efficiently.
Interactive Technologies such as Augmented (AR) and Virtual Reality (VR) are set to transform the ways in which people communicate, interact and share information on the Internet and beyond.
This will directly impact a larger number of European industries ranging from manufacturing, data life, steel, construction, engineering, to education, entertainment, media and culture, enabling new business opportunities.

Aggregated XR multiuser space for future work places

In the context of industrialization, informatization and sustainable development of the mining sector, Mine.io solution will build a novel mining digital ecosystem and a systemic structure for the implementation of Mining 4.0 in mining industrial environments. Mine.io solution will embrace the whole mining value chain and processes from resources’ exploration, extraction, and processing to waste management and mobility. The Mine.io project is designed as the next generation digital mining ecosystem. All processes are digitized using the appropriate sensors and the raw data are analyzed locally (edge computing), providing very useful information about all the operations of the mine in real time. 
The proposed integrated cloud-edge architecture will make the integration and interaction across currently disparate IoT systems and smart objects as seamless and uncomplicated as possible and support the distribution of intelligent services across all tiers of the IoT stack (i.e. from enterprise to the edge). 
To support this symbiotic hybrid architecture, Mine.io will develop smart IoT hubs (interconnected, virtualised autonomic and plug-n-play cognitive agents, found in a distributed arrangement within the mining plant) ideally suited for edge applications and customized according to specific needs for executing ML/DL (or similar AI related technologies) in the most optional way: minimizing response time and energy consumption. 
Each cognitive element may represent a subset of clusters fulfilling the same functional responsibilities (i.e. serving the same application needs).  
Mine.io infrastructure will also offer an application marketplace. Third parties can use the outcome / results of the analytic analysis procedure, to further enhance the procedures / operation / automation and supply chain management while keeping the Mine.io control app always updated and inline with future needs and milestones.

Mine.io: A Holistic Digital Mine 4.0 Ecosystem

(SO1): Establishing product-process-production system of systems model
Enabling companies to efficiently determine relations between products, processes and production systems, thereby enabling to determine impact of market and supply changes on production systems, and identifying opportunities to utilize existing assets. This is achieved using an ontology-based reference model representing entities and relations in a system of systems perspective in a product-process-production system of systems model (PPPSoS), including human skills and competences. This forms a basis for protocols deriving company-specific data models from which implementations in Enterprise IT systems can be developed.
(SO2): Predict reconfiguration needs
Enabling companies to predict needs for reconfiguration in response to disrupted supply chains or rapidly changing customer demands based on timely and early identification of internal and external company-specific change triggers and assessment of their impact on products, processes, and production at line level, factory level, and global network level. This is enabled by data in a PPPSoS model analyzed using AI techniques and organizational knowledge, where reconfiguration triggers are first identified, then based on data from various sources monitor whether triggers occur, detect when a change is triggered, and evaluate the impact on production systems.
(SO3): Prescribe the best reconfiguration alternative
Enabling companies to prescribe reconfigurations by identifying feasible reconfiguration alternatives at line level, factory level, and global network level in response to the detected change in demand and/or disruption in supply chains, using a PPPSoS model representing existing assets internal or external to a company and evaluate time, financial, and organizational aspects of the different reconfiguration alternatives applying machine learning and simulation.

Please see PDF for details.

“Matching Assets with manufacturing Tasks for Changeable & Efficient Reconfiguration”

Objective 1: Define Digitization Groundwork; 
Models based on digital twins framework will provide machines model instance that will reflect the structural, performance, maintenance, and operational health characteristics of the physical systems. 
Objective 2: Improve reliability by substantially reducing unexpected downtimes, drastically reduce maintenance costs and have a deep impact on productivity and energy efficiency; 
Produce a wide set of AI algorithms tailored to system specifications and requirements/framework used for advanced predictive maintenance process of marine equipment and machinery.
Objective 3: Enable Advanced Shipbuilding Automation; 
To provide a step change in shipbuilding automation by introducing robotics technology capable to perform a wide set of intelligent tasks (inspection, painting) autonomously or semi-autonomously on state-of-the-art cognitive aerial platforms. 
Objective 4: Safeguard Privacy and Security of Data through distributed machine learning approach; Avoid direct data leakage through local model training, addressing the fundamental problems of privacy, ownership, and locality of data. 
Objective 5: Provide a unified approach to data across operations and optimised data-driven production planning; 
Objective 6: Validate the aforementioned approaches and technologies on three demonstrators involving shipyards (NO, ES, PT) with respect to maintenance and processes optimization. 
Objective 7: Set a cornerstone for the building of standards in the Shipyard Industry at an EU and global level, ensuring best practices being shared for the benefit of the industry and the public; adhering to the Safety and Health in shipbuilding and ship repair; 
Objective 8: Boost the exploitation potential of the project’s technologies, as well as to support the dissemination of the projects outcomes by making them accessible to the scientific community, the field experts and the general public;

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