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Maximising the throughput of production and assembly lines using symbiotic simulation optimisation

Southampton Business School

Location:  Highfield Campus
Closing Date:  Sunday 30 June 2019
Reference:  1140419PJ

Supervisory team: Dr Christine Currie, Dr Stephan Onggo and Dr Thomas Monks

A fully funded PhD position is available within the Centre for Operational Research, Management Science and Information Systems (CORMSIS) at the University of Southampton, UK. CORMSIS is one of the largest groups of OR/MS researchers in Europe and spans Mathematical Sciences and Southampton Business School. Ranked in the top 50 in the QS Rankings for Statistics and OR worldwide*, the University Of Southampton has significant expertise in simulation and optimization, both key components of this project.

We are seeking a candidate who has an aptitude for computer simulation and optimization with strong mathematical and statistical skills and an interest in applying their research to a practical problem. Excellent communication skills are essential.

Working with Ford motor company’s Powertrain Manufacturing Engineering department, this PhD project aims to realise the full benefits of Industry 4.0 on increasing manufacturing throughput through developing novel optimization via simulation techniques that work with symbiotic simulations. We define a symbiotic simulation as one that runs alongside and interacts with the real system. In Industry 4.0, such a simulation is referred to as a digital twin. The objective is to help decision makers make complex operational decisions which often require them to come up with an optimal solution within a tight time window. Hence, the experimentation or optimisation must produce solutions very quickly, keeping in mind the dynamic of the real system. 

The methods developed in the PhD project will be incorporated into simulations of production and assembly lines across the world, helping to deliver improved annual throughputs. This will allow us to evaluate our new methods in a real-world setting. It also gives the PhD student excellent experience of working at the cutting edge of both practical and academic simulation. 

Symbiotic simulation is a novel area, with scope for exciting, high-impact research. In symbiotic simulation, the simulation model automatically draws data from the real system, enabling accurate forecasting of future behaviour and testing of different options for the system set up (Xu et al. 2016). With efficient optimisation methods, suggested changes to the system can rapidly be fed back to decision-makers.  

Particularly relevant skills include a background in mathematical optimization, computer simulation, mathematical statistics, algorithms and computer programming. Candidates should have at least an undergraduate degree, but preferably a masters’ degree in mathematics, engineering, statistics, computer science or a relevant discipline.

* QS Rankings 2019 (https://www.topuniversities.com/university-rankings/university-subject-rankings/2019/statistics-operational-research)

Reference:

Xu, J. et al. (2016) “Simulation optimization in the era of Industrial 4.0 and the Industrial Internet”. J.Sim., 10, pp 310-320 (doi.org/10.1057/s41273-016-0037-6)

The link to apply is https://studentrecords.soton.ac.uk/BNNRPROD/bzsksrch.P_Search Please apply under PhD Business Studies & Management. 

When applying please specify on your application form the title of the project you are applying for. 

Informal enquiries can be made by contacting Dr Christine Currie (Christine.currie@soton.ac.uk).

Closing Date for applications: 30 June 2019

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