Title and Brief Explanation (also available in SERG website)
|01/06/2020||BL2F (CI), Black Liquor to Fuel by Efficient HydroThermal Application integrated to Pulp Mill LC-SC3-RES-23-2019; 12 partners, (total grant 7M Euro)||
|01/11/2019||Commenced||WATER-MINING, Next generation water-smart management systems: large scale demonstrations for a circular economy and society; CE-SC5-04-2019 WP Leader, Grant Agreement Preparation (Total grant 17M Euro) – Coordinated by Delft University, 38 public and private partners and 4 linked third parties in 12 countries.||
|01/10/2018||Ongoing||Circular-City (CI), COST Action CA17133, Implementing nature-based solutions for creating a resourceful circular city; Digitalisation Working Group Leader; 2018-2023, 20M Euros) in partnership with a wide range of academic and industrial partners from 37 European Countries.|
Deep Purple (EU Funded H2020: H2020-BBI-JTI-2018-837998)
CONVERSION OF DILUTED MIXED URBAN BIO-WASTES INTO SUSTAINABLE MATERIALS AND PRODUCTS IN FLEXIBLE PURPLE PHOTOBIOREFINERIES
DEEP PURPLE creates a holistic consortium to transform diluted urban bio-wastes,
including mixed waste streams, organic fraction of municipal solid waste (OFMSW), wastewater (WW)
and sewage sludge (SS), into feedstock for bio-industry to obtain sustainable bio-products.
This revolutionary concept will be implemented in a novel Single-Site Multi-Platform Concept
(Biomass, Cellulose and Biogas) to replace current polluting destructive practices with new value added concepts.
The beneficial use of bio-waste is obtained by an innovative combination of optimized recovery technologies
and novel solutions: the Purple Phototrophic Bacteria (PPB) PhotoBiorefinery. The use of PPB -the most versatile
metabolism reported- ensures the adaption to fluctuating and diluted waste streams to support a stable profitable production chain. The first PPB PhotoBiorefinery in the EU (the biggest worldwide) will be validated
in different environmental, economic, logistic, and social scenarios.
|01/06/2019||Completed||Afwerx Award: Automatic quality and provenance evaluation of micro and electronic components and assembly systems, US Airforce Funded project, May 2018-Jan 2020, income $500K. Project partners SCANNA (UK), SUPPLY DYNAMICS INC (USA).|
|2016-20||Completed||SMART-Plant (CI), Scale-up of low-carbon footprint Material Recovery Techniques for upgrading existing wastewater treatment Plants; HORIZON2020 WATER-1b-2015, 26 partners (2016-2020) (Total 7.6M Euro|
|01/03/2019||completed|| HISTEED 2
DAS Funded under FASS programme, of full implmentation of the project in phase 2 to research, develop and validate an advanced Machine Learning and AI solution for screening Electrical and Electronic Devices in Luggage.
The High-Speed Scanning for detecting Tampered Electrical Electronic Devices (HISTEED)
Government Funding Council (DSA): ACC106975
The aim of this project is to explore the feasibility of a novel Image Processing and Event-Based Machine Learning technology that increases the accuracy, speed as well as the systematic scale up of screening Electronic and Electrical Devices for hand luggage.
Innovative strategies, sensing and process Chains for increased Quality, re-configurability, and recyclability of Manufacturing Optolectronics
Advances in optoelectronics technologies is causing a revolution in consumer electronic goods, solar energy, communications, LED, industrial laser, and other fields. At present, the optoelectrical manufacturing is facing significant challenges in dealing with the evolution of the equipment, instrumentation and manufacturing processes they support. The industry is striving for higher customisation and individualisation, implying that systems configurations need to change more frequently and dynamically. IQONIC will offer a scalable zero defect manufacturing platform covering the overall process chain of optoelectrical parts. IQONIC covers the design of new optoelectrical components and their optimised process chain, their assembly process, as well as their disassembly and reintroduction into the value chain. IQONIC will therefore comprise new hardware and software components interfaced with the current facilities through internet of things and datamanagement platforms, while being orchestrated through eight (8) scalable strategies at component, work-station and shopfloor level. The IQONIC technologies will be demonstrated in 4 demo sites covering a wide range of products and processes. The impact of IQONIC to the European optoelectronics manufacturing industry, but also the society itself, can be summarised in the following (with a horizon of 4 years after project ends): (i) increase of the in-service efficiency by 22%, (ii) increased flexibility with 16% faster reconfiguration times, (iii) 10% reduction in production costs through recycled components and materials, (iv) improved designs for assembly and disassembly and, (v) about 400 new jobs created and (vi) over 39 MEUR ROI for the consortium. To do that we have brought together a total of seventeen (17) EU-based partners, representing both industry and academia, having ample experience in cutting-edge technologies and active presence in the EU photonics and manufacturing.
Demonstration of water loops with innovative regenerative business models for the Mediterranean region (HYDROUSA)
H2020-EU (188.8.131.52-4): 776643
HYDROUSA will provide innovative, regenerative and circular solutions for (1) nature-based water management of Mediterranean coastal areas, closing water loops; (2) nutrient management, boosting the agricultural and energy profile; and (3) local economies, based on circular value chains. The services provided lead to a win-win-win situation for the economy, environment and community within the water-energy-food-employment nexus.
Strategies and Predictive Maintenance models wrapped around physical systems for Zero-unexpeted-Breakdowns and increased operating life of Factories
Newly built machines start their service life cycle with standard and well specified performance signatures. Components of these machines function and work as expected and a well-defined modular maintenance (preventive maintenance) for a while would fulfil the uptime/downtime plans and schedules of the companies that utilise them. The problem arises when machines and building components, or the collective performance of the components manifesting themselves as the overall performance diminish due to depreciation. Such gradual depreciation normally leads to unexpected failures of the machine or its individual building blocks. In addition to failures, such out of norm machines produce faulty or dangerously border-line products; both causing significant costs, energy waste, as well as productivity and other efficiency shortcomings in manufacturing processes. Capitalising on the findings of the Industry 4.0 evolution, Z-Bre4k will leverage the reference architecture and operating system of the FoF11/AUTOWARE , in order to develop a highly adaptive real-time Machine (network of components) Simulation platform that wraps around the physical equipment for the purpose of predicting uptimes and breakdowns – thus creating intuitive maintenance control and management systems. This will be coupled with novel strategies and a CPPS based operating system, which when deployed in the field, are expected to increase maintainability and operating life span of production systems. The foundations will be based on the convergence of Engineering Technology (ET), Operational Technology (OT) and IT towards consolidating actionable intelligence from manufacturing assets performance modelling, for leveraging predictive maintenance for increased operating life of CPPS.
Zero-defect manufacturing strategies towards on-line production management for European factories
Partners: Greece (CERTH and Atlantis Engineering), Cyprus (CETRI), UK (Brunel University and Microsemi), Switzerland (EPEL), Italy (Holonix, Interseals, Confindustria, and SIR), Spain (Datapixel), and Portugal (Inova, and Durit Metal Duro).
In this project event-based adaptive control and optimisation solution to minimise defect in the discrete automated manufacturing process. The machines and the robots will adapt to the variations in material, customer requirements and overall environmental conditions with the purpose to reduce production defect to a minimum and eventually to zero.
|2014-18||Completed||CFoot-Control: Developing on line tools to monitor, control and mitigate GHG emissions in WWTPs, (2014-2018), 6M Euros income £500K. Coordinated by National Technical University of Athens, 6 partners and 10 industrial collaborators.|
Automatic Real-Time Translation of Plant Data into Management Performance Metrics: A Case for Real-Time and Predictive Production Control - Brewery Technology
The Sustainable Loop-Infinite Manufacturing Initiative.
Further information and expression of interest click here.
|01/10/16||Commenced||Real-Time ECU Modelling and Optimisation: understanding and improving the ECU in real-time through better situation awareness and expanded sensor and actuation network architecture and data modelling.|
|02/05/15||Commenced||The problem of Harmonic Filter Burns in Coal Power Plants (JEV Malaysia).||Contact us for more detail|
|01/10/14||Commenced||High Frequency Trading: A real-time model for tracking and tracing fluctuation in prices.||Contact us for more detail|
|01/09/14||Finalised||The information systems infrastructure for human-based capability models (individual and networks).||Contact us for more detail|
|01/09/12||Finalised||EventCluster a new generation of EventTracker.||Contact us for more detail|
EventTracker can be considered as a smart recorder of events.
Analogous to a Blackbox but not only a recorder but an instrument that facilitates preliminary data and knowledge construction . [Better Situation Awreness]
Applications: Real-Time Input Variable Selection and Sensitivity Analysis.
1.Systems need to respond to externally generated stimuli within a finite-specified period (i.e. Real-Time) a Better Situation Awareness for Quick Response
2.Producing time-critical accurate knowledge about the state of the system still remains a major challenge à Innovative
3.The knowledge is critical to the safety and the integrity of the operators and equipment à Economical Gain
4.Industrial systems’ capability to capture data (SCADA) and flexibility to adjust to changing system requirements à Existing Technological Capabilities
|02/01/12||Finalised||Multiple access bluetooth device for audio conferencing and voice distrubution||Contact for Detail|
NEAR-REAL VIRTUAL ENVIRONMENT (NERVE) FOR PHANTOM LIMB PAIN: System Integration, Optimisation and Personalisation
- Motion Detection and Virtual Limb Re-Embodiment Adaptation: Personalisation and Adaptation of Movement, Visual and Propiceptive Feedback. (proof of concept) - [Achieved]
Demo (by Antoine Mallet)
Satistica Quality and Utility Inspection Device (SQUID)
Human-Based Network Capability Models:
Aim: To build a fundamental conceptual model which can predict a group of individuals’ collective (Network) capability.
in other words
SinglX: Next Generation for Production Process Monitoring and Optimisation
Sponsored by Acontrol and in collaboration with University of Coimbra
|01/11/09||Foundation||Virtual Personalised System to address Phantom Limb Pain in Patients|
|01/11/10||Finalised||Product and Services Environmental Impact Measurement Web Tool (EcoXchangeTM)|
The Theory and Modelling of Individual's Capability - Impact and Utilisation of Resources
|16/6/07||Finalised||Multiple wireless access for software applications - External Sponsorship|
|01/9/07||Finalised||Design of Vertical Internet Search Engine Using CORE algorithm|
|01/8/08||Finalised||satistica software tool standalone version - sponsored by satisticaTM||
Please contact me for a complimentary of v1.1
SinglX: Full R&D - Sponsored by EPSRC
Like in many other manufacturing control solution providers, existing solution for real-time decision support enjoys statistical analysis of input data collected from a series of data entry points throughout the plant, leading to a summary of parametric performance indicators. It seems that current shop floor performance analysis tools available in the market lack the capabilities to reduce decision making process overheads. Since they are either indicators of real time performance of the system or a simulated result of past observations. There is a need for an automatic data interpretation capability which could take pressure off managers to confidently re-schedule the production plan to improve performance and reduce cost.
One of the outcomes of this project has been a novel real-time sensitivity analysis called EventTracker (for details please view list of publications).