2023-32097 – CIFRE PhD Thesis – New scheduling, transport & storage approaches for complex manufacturing systems M/F

Regular/Temporary : Temporary
Position description :
CIFRE PhD Thesis – Development of new integrated scheduling, transport and storage approaches for complex manufacturing systems
At STMicroelectronics, we are 46,000 men and women designers and manufacturers of microelectronic technologies. We collaborate with 100,000 customers and thousands of partners. With them, we design and create products, solutions and ecosystems that address their challenges and opportunities and the need to contribute to a more sustainable world. Our advanced technologies enable smarter mobility, more efficient energy and power management, and large-scale deployment of the Internet of Things (IoT) and 5G.
The Crolles 300mm fab is growing rapidly and it is no longer possible to ignore the physical location of lots, buildings configuration and transport system constraints in the automated scheduling and dispatching system. In the coming years, lot transport system will be congested.
The aim of this thesis is to reduce equipment inefficiencies due to transport constraints.
The thesis will define the lot exchange time criticality for a tool and propose methods to dynamically categorize all equipment in fab in real time.
The dispatching rules and scheduling objective functions must be improved to properly manage physical lot location and buildings configuration without reducing efficiency on other criteria and performance computation.
This thesis will leverage on previous work done on AMHS storage modelling to propose new algorithms to dynamically improve lot storage location after process, lot cycle time, transport time and next equipment efficiency.
This thesis will be connected to other work done on global/local optimization and global scheduling.

Keywords: scheduling, optimization, transportation, AMHS, FOUP location, FOUP storage, improve equipment efficiency, lot cycle time reduction

Operational Research / Mathematics / Computer science / Data science
Education level required : 5 – Master degree
Language / Level :
French : 3- Advanced
Language / Level :
English : 2- Business fluent
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