Contact Dr Christina Latsou

Areas of expertise

  • Computing, Simulation & Modelling
  • Digital Twinning
  • Manufacturing Systems
  • Safety, Resilience, Risk & Reliability

Background

Dr Latsou holds a BSc and MSc degree in Mechanical Engineering. Christina gained her MSc in 'Mechanical Engineering Design' from the University of Manchester in 2014 and her PhD in 'Automated Generation of Reliability Models' from Loughborough University in 2019. Her PhD research work focused on the development and application of reliability methods for enhanced reliability performance. Christina's research involved developing an automated process to generate Petri Net models from industrial representations of the system design in order to provide the capability of more timely reliability assessment in the design stage.

Research opportunities

Christina focuses on the digital transformation of manufacturing processes, with a focus on optimising complex systems and systems of systems. Her research centres on complex systems modelling, simulation, optimisation, uncertainty quantification, and improving human-machine interaction in smart manufacturing. Her primary contributions are in dynamic modelling, addressing complex challenges within the manufacturing and maintenance industries.

Current activities

Dr Latsou is a Lecturer in Smart Manufacturing based with the Centre for Digital Engineering and Manufacturing, Manufacturing Theme at Cranfield University.

Christina's main research focus is on developing advanced simulation and optimisation techniques, and digital solutions for complex manufacturing systems and supply chains with the view to enhance performance, productivity and resilience. Dr Latsou is also involved in teaching, proposal writing and supervising postgraduate MSc projects. Christina is a member of the Institution of Engineering and Technology (MIET) and a Fellow of the Higher Education Academy (FHEA).

Selected projects​:

RFID to enable ATMP Manufacturing, Cryogenic Supply Chain Scale-Up and Productivity Gains (Innovate UK-funded, March 2019 – March 2022)​

Developing a process to prioritise technologies for Through-life Engineering Services – (HEIF Call off Funding, February 2021 – July 2021)​

A unified Digital Twin framework based on an ontology approach for effective domain knowledge modelling (Babcock International Group funded, May 2021 – October 2021)​

An agent-based approach for Digital Twin development to optimise maintenance in train wheels (EPSRC funded in collaboration with Vendigital Ltd, June 2021 – December 2022)​

Servitisation optimiser tool development (SIT - Siemens Energy funded, January 2022 – June 2022)​

Proof of Concept Evaluation and Dissemination of the Forecast and Resource Planning Toolset (EPSRC IAA funded in collaboration with MoD, January 2023 – June 2023)​

A hybrid simulation-based optimisation approach to improve complex assets’ availability (Babcock International Group funded, February 2023 – September 2023)​

Clients

  • Babcock International Group PLC
  • Innovate UK
  • BAE Systems PLC
  • Siemens Energy AG
  • Ministry of Defence

Publications

Articles In Journals