Recent Research Projects



ServTech is in the center of different European and international networks of excellence.

Header image: © Andrew Rich, iStock

In various consortia with leading industry and research organisations in Europe, ServTech has been awarded significant research funding from the European Commission for large-scale research projects. These include FP7 IP projects, such as the Management of Dynamic Manufacturing Networks (IMAGINE), and Horizon 2020 projects, such as An Integrated Platform for Managing the Product-Service Lifecycle (ICP4Life), and QUALITOP, and ONCOSCREEN.

ServTech’s expertise lies in:

  • Service Engineering methodologies for advanced service-based applications,
  • the use of business process management techniques in conjunction with SOA,
  • Business process compliance techniques for regulatory purposes,
  • on-demand declarative languages and techniques for user empowerment, and
  • Event analysis and processing for service-enabled applications.

ServTech aims to pool, coordinate, and consolidate research activities in service science and innovation all across Europe. It focuses on real-world challenges that require the use of multiple conceptual, methodological and substantive approaches.

Research & Development Projects

ServTech has been successful in obtaining research funding from European sources.
In addition to a number of journal and conference publications, all research results from these projects are openly available to the public through a list of research reports, called deliverables in EU jargon. They are also available on the respective project websites.

HORIZON 2020

ONCOSCREEN

From January 2023, ServTech will be involved in a new 48-month project, ONCOSCREEN. The project will be implemented by a multidisciplinary consortium of 38 partners, including technical solution providers, hospitals, ministries of health as policy makers, legal and ethical experts, and insurance companies. It will actively involve end-users and citizens in all phases of implementation through targeted workshops.

The ONCOSCREEN project was motivated by the observation that Colorectal Cancer (CRC) is accountable for 12.4% of all deaths due to cancer and only 14% of EU citizens participate in screening programmes. To improve this serious situation, there is an urgent need for accurate, non-invasive, cost-effective screening tests based on novel technologies and increased awareness of the disease and its detection. In addition, personalised approaches to screening are required that take into account genetic and other socio-economic variables and environmental stressors  leading to different disease presentations. ONCOSCREEN responds to these challenges by developing a risk-based, population-level stratification methodology for CRC. It will consider genetic prevalence, socio-economic status, and other impact factors. The project will complement this methodology by

  • developing a set of novel, practical, and low-cost screening technologies with high sensitivity and specificity,
  • using AI to enhance existing CRC screening methodologies, enabling early detection of polyps and providing personalised risk status stratification, and 
  • providing a mobile app for self-monitoring and CRC awareness.

In addition, ONCOSCREEN is developing an Intelligent Analytics Dashboard for policy makers to facilitate effective policy making at regional and national levels. These solutions will be tested and validated through a multi-level campaign. For the clinical solutions in particular, a clinical validation study is planned with the participation of 4100 enrolled patients. In order to ensure the adoption of the developed solutions by health systems, their cost-effectiveness and financial viability will be assessed. 

QUALITOP

In January 2020, ServTech launched a new research and innovation project in the medical sector: QUALITOP. This project aims to monitor multidimensional aspects of QUAlity of Life after cancer immunotherapy. It will design and develop a European digital smart medical platform that uses big data analytics, AI, and simulation modelling to efficiently and effectively collect and aggregate masses of quality-of-life data on patients who have undergone cancer immunotherapy treatment. The platform will help to monitor the health of these patients, perform causal inference analyses, generate harm reduction for patients, and store, re-use, and improve and disseminate medical knowledge.

ICP4Life

In December 2018, ServTech completed the EU Horizon 2020 project ICP4Life (An Integrated Collaborative Platform for Managing the Product-Service Engineering Lifecycle). In this project, the Blueprint approach, originally developed in the FP7 project IMAGINE, was extended to the needs of customised product-service systems by incorporating IoT sensors and smart devices and deploying these technologies on the shop floor, collecting data for predictive analytics. In addition, ServTech has developed a new Product-oriented Configuration Language (PoCL) for customising digital products. This is a user-centric language that provides interactive 3D CAD/CAM capabilities to help customers collaborate with product designers and engineers to explore digital product and service configurations.

7th Framework Programme

ServTech participated as a scientific coordinator in the EU Framework 7 Integrated Project IMAGINE (Innovative End-to-end Management of Dynamic Manufacturing Networks). In this project, ServTech designed a federated IT platform to support the Industry 4.0 shift from linear, sequential supply chain operations to an interconnected, open system of supply operations – known as a smart manufacturing network. This lays the foundation for how manufacturers and suppliers can collaborate to produce a range of innovative digital products. In this project, ServTech has also developed a framework of programmable abstract knowledge types that convey manufacturing knowledge – called manufacturing blueprint images (or simply blueprints). These transform conventional products into self-describing products by storing, linking, combining, and analysing the raw data collected from a product throughout its lifecycle and the processes that produce it. Manufacturing Blueprints rely on model-based design techniques to manage and inter-link product data and information (both its content and context), product portfolios and product families, manufacturing assets (people, plant machinery and equipment, production line equipment) and, in general, to help meet the requirements (functional, performance, quality, cost, time, etc.) of an entire manufacturing network. This information can be placed in a broader operational context, providing the basis for actionable manufacturing intelligence and a move towards more fact-based decisions. This creates “smart actionable data” from which knowledge can be generated and production processes can be triggered.