Dr Christos Papanagnou
Lecturer in Logistics & Supply Chain Management
I obtained a PhD in Modelling and Control of Supply Chains and Production Processes at City University in 2007 and since then I have worked in academia, various research organisations and in industry.
I held positions as Lecturer at University of Macedonia, Aristotle University and Alexander Technological Educational Institute of Thessaloniki teaching the following modules: Value Chain Management, Operations Research, Production and Operations Management, Innovative Technologies and Control Theory.
I served in the past as Researcher and Consultant in several steel manufacturing companies investigating efficient modelling and simulation methods of shop floor and supply chain processes. My contribution focused on minimising the effects of physical and capacity constraints and the bullwhip effect (demand amplification phenomenon to upstream levels of supply chains).
I applied, with great success, advanced techniques based on control theory, data analysis, probability and stochastic systems in order to improve inventory management, distribution of products, Work-In-Process, production efficiency and productivity.
Currently, I investigate the ability of manufacturing companies to build innovative data products and services, in order to turn large data volumes (Big Data Exploration) into semantically interoperable data assets leading to considerable gains. Furthermore, I apply smart tracking and tracing techniques and explore the opportunities of Industry Revolution 4.0 and Internet of Things in manufacturing environments.
I have been an advisory member of the European Commission Technical Working Group on best environmental management practices in car manufacturing sector and stakeholder for Flexible Manufacturing SIG Workshop at Advanced Manufacturing Research Centre.
- Global Supply Chain Management (Level 7)
- Business (Level 7)
- Applied Business Research and Analysis (level 6)
Modelling and Control of supply chains: Applying control theory and modelling techniques in supply chains is a great challenge due to the diverse complexity and the great variety of open-issues that it offers. In particular, the implementation of alternative PID tuning and optimal control methods is of immense important in decentralised supply chains.
Cognitive supply chain: While the majority of organisations operate in turbulent markets resilience has been proved as a necessary condition in order organisations to become robust and sustainable. Supply chains that can be seen as cognitive autonomic nervous systems where stability is guaranteed by providing homeostasis, i.e., respond properly to changes in the environment and predict the occurrence of a given environmental stimulus to initiate the appropriate corrective responses beforehand.
Logistics and supply chain integration. As supply chains in industry are changing rapidly, organisations should opt for resilient and robust dynamic manufacturing supply networks. In this context, I am interested in researching how companies can integrate their supply chain facilities and collaborate effectively with customers and other supply chain participants by building robust global supply chains and strong relationships with the aid of multivariate time series models.
Factories of the Future. Finding feasible solutions of how companies can transform their production layout with the aid of Internet of Industrial Things (IoIT) and by following the research principles of the Factories of the Future (FoF) and Industrial Revolution 4.0.
Big Data and cloud systems for cyber supply chains. Supply chains in the future will have to deal with large data volumes of great variety and high velocity. My research involves the implementation of advanced optimisation techniques through big data analysis and use of cloud computing to enable effective decision-making, co-operation, storage capacity problems and supply sourcing
I am currently supervising doctoral students on the following topics: Sustainable Procurement, Big Data Analytics in Retail Industry, Steel volatility management in the automotive industry with the aid of financial instruments, diversification and long-term supplier relationships, and Holistic Performance Measurement in an Inventory Forecasting Context.
I would be interested in supervising future doctoral students on Supply chain integration through Internet of Things (IoT), Big Data Exploration and Predictive analytics, Performance Measurement, Quantitative methods in Supply Chain Management, Implementation of Factories of The Future, and Control Theory in supply chains and manufacturing
Qualifications and Memberships
- Fellow of Higher Education Academy (2016)
- Valued IEEE Member since 2001
- Level 3 Certificate in Leadership and Management by Institute of Leadership & Managemen
- Ph.D. in Control Engineering, City University of London. 2007. Thesis: Modelling, control and optimisation of supply chains and production processes
- MSc in Information Engineering, City University of London. 2004.
- BSc (Hons) in Computer Aided Engineering, London South Bank University. 2003.
- BSc (Hons) in Automation Engineering, Alexander Technological Institute of Thessaloniki, Greece. 2001
C.I. Papanagnou (2020). A digital twin model for enhancing performance measurement in assembly lines. In: Digital Twins Technologies and Smart Cities. Farsi M, Daneshkhah A, Jahankhani H, Hosseinian-Far A. (eds), Springer International Publishing
C.I. Papanagnou and P. Madhlambudzi (2019). Stakeholder identi
cation and salience in purchasing: An empirical study from UK hospitals, International Journal of Healthcare Technology and Management
N. Shchaveleva and C.I. Papanagnou (2018). Investigation of current perspectives for NHS Wales sustainable development through procurement policies, Public Money & Management, Vol. 38, No. 7, pp. 493-502
C.I. Papanagnou and O. Matthews-Amune (2018). Coping with demand volatility in retail pharmacies with the aid of big data exploration, Computers & Operations Research, Vol. 98, pp. 343-354
I. Ekiugbo and C. Papanagnou (2017). The Role of the Procurement Function in Realising Sustainable Development Goals: An Empirical Study of an Emerging Economy’s Oil & Gas Sector, European Journal of Sustainable Development, Vol. 6, No. 3, pp. 1-15, (https://ecsdev.org/ojs/index.php/ejsd/article/view/510 )
Y. Mladenova and C. I. Papanagnou (2016). The Impact of Big Data Analytics on Supply Chain Performance in Grocery Retailing Sector in the UK In: e-Proc. of the 28th European Conference on Operational Research, Poznan, Poland
I. Ekiughbo and C. I. Papanagnou (2016). The role of Sustainable Procurement in Corporate Sustainability within Oil and Gas sector. In: British Academy of Management (BAM) Conference 2016: Newcastle, U.K.
A. Seiler, C. Papanagnou and P. Scarf (2016). On the relationship between economic performance and the position of businesses in supply chain networks In: Proc. of the 10th conference of the Performance Measurement Association (PMA), Edinburgh, United Kingdom
C.I. Papanagnou and G.D. Halikias (2011). Stochastic state space in supply chains under AR(1) demand
profiles, International Journal of Mathematics in Operational Research, Vol. 3, No. 5, pp. 578-594
C.I. Papanagnou and G.D. Halikias (2011). Simulation and modelling methods in aluminium rolling industry, International Journal of Advanced Manufacturing Technology, Vol. 53, Nos. 9-12, pp. 993-1018
C.I. Papanagnou and P. Tzionas (2010). Simulation of supply chain dynamic behaviour by means of discrete-event tools. In: e-Proc. of the 24th European Conference on Operational Research, Lisbon, Portugal