Research Group: Data Systems
About the group
The main aim of the Data Systems Group is to carry out interdisciplinary research in the area of complex, dynamic, and global supply chains planning, management and control. This includes:
- Analysis and optimisation of supply chains performances such as efficiency, robustness and resilience, and
- Multi-criteria optimisation of supply chain sustainability including all three pillars: social, economic and environmental, in the presence of uncertainty in supply chain environments and processes.
Novel decision making models for dynamic global supply chains configurations and information architectures will be developed, as opposed to mainly static, single criterion optimisation models adopted by majority of current supply chains. The new models will be applicable to various economic sectors including manufacturing, retailers, transportation, healthcare, energy production and distribution, recycling, etc.
The objectives and development aims of the research group are:
- Development of optimisation models of sustainable supply chain networks in the Industry 4.0 era which handles complex decision-making problems such as supply chain design, suppliers and technology selection, resource allocation, risk mitigations, optimisation of large scale dynamic supply chains operations. Further on, flexible information exchange in the communication subsystems of supply chains for the best performance of the parts of supply chains will be designed and optimised.
- Development of different data driven systems to handle various types and sources of uncertainty including:
- Fuzzy evolving systems for modelling dynamic supply chain systems whose structure and parameters are changing over time,
- Fuzzy causal maps for modelling uncertain knowledge of non-linear causal relations among entities in different domains of manufacturing supply chains,
- Fuzzy causal maps for modelling diagnostic and prognostic decision support systems in healthcare,
- Analysis and design of big data systems to support supply chain management.
- Analyse and track underlying developmental trends occurring within the theme of Industry 4.0 and map onto industrial partners’ supply chains, to understand current status and analyse routes forwards for technological, cultural, organisational, assimilation challenges and potential solutions.
- Analyse and accommodate contemporary supply chain change challenges, to achieve within decision-time solutions for adaptation to intra-organisational and exogenous risk resilience. Data-driven discrete event simulation and visualisation technology capabilities are utilised.
Meet the team
The group has experience in obtaining and working on research projects funded by various funding bodies, including EPSRC, FP7, MoD, KTP, Erasmus+ and programmes directly funded by industry.
- PI Ammar Al Bazi, Applied Research Type: ‘Keen Brief’, partially funded by the ERDF, purpose: to achieve best operator-machine interactions within an aerospace manufacturing facility, company: ANT Industries Ltd, Total value £31,026, duration: 1 year, status: ongoing project.
- PI Jim Rowley, Wings of the Future ATI IUK (contacted through GKN Aerospace). Simulation support to validate designs of future factory configurations for strategic components, Total value for CU £39,000.
- PI from Coventry University Dobrila Petrovic, ERASMUS, Call for proposals EAC/A04/2014, Enhancement of HE research potential contributing to further growth of the WB region / Re@WBC, Coordinator: University of Nis, Serbia, 13 partners, December, 2015 – December, 2018, Total value 992890EUR, for Coventry University, €41,863.
Our research is be driven by real-world supply chain problems and is continuing and further developing collaboration with different manufacturing companies such as Unipart, ANT Industries and Malvern Tubular Components, in the UK, Rolls Royce in Norway, KSB in Germany, Custom Drinks in Spain, etc.