BUSI2124 Introduction to Management Science for Business Decisions

• Undergraduate, Nottingham University Business School China

SMART MANUFACTURING LAB-Politecnico di Milano

As a teaching assitant, I mentored one group, with the aim at exploiting the tools and methods learned to analyze, formalize and provide a solution to the typical machine scheduling problems in the real manufacturing plants. The projects are collaborated with industries.

1. 2022-2023，Optimizaion the material flows within the GVM line and from the GVM line to the warehouse，Parker Hannifin Italy
2. 2021-2022, Optimization of SMT pick-and-place equipment for PCB assembly, Magneti Marelli S.p.A.
3. 2020-2021, Application of Lean methodology to optimize Dial Screen Printing Scheduling, Magneti Marelli S.p.A.

The following activities are carried out:

• Machine scheduling knowledge: seminars/lectures to deepen all the technological and management aspects connected to the problem under study, e.g., parallel machine scheduling, resource constrained project scheduling.
• Data collection and processing: basic data collection and processing skills in real industrial contexts will be provided and used to design and/or validate the solutions provided.
• Modelling skills, e.g., mixed interger programming(MIP) formulation skills and mathematical solver useage, simulation modelling skills.
• Data analysis and visualization skills are delivered.