In the assembly in Köping, the number of new products will increase over time. This means that the cycle times between the different products will differ. As a result, the complexity of assembly increases and it will be difficult to understand our delivery capability with the help of simple calculation methods. It will be very dependent on which product mix will be run through the assembly. As the product mix is completely dependent on what customers order, this will vary to a large extent on a daily basis and then also our delivery capability.
The project aims to create a discrete event simulation model that can simulate a certain outcome autonomously based on given input. The data can both be of such a nature that is the same day by day, but it can also be data that is different for each day. Examples of data that are the same are cycle time data and examples of data that change are product mix.
Suitable background of students:
- Mechanical Engineering. A student that has a big interest in simulations models, flow optimizations and Big Data Management
Develop a discrete event-driven simulation model that can retrieve data from external systems and which then autonomously simulates an outcome day by day via scheduling. The results will then be presented in a report on which decision-makers can act.
The assignment includes:
- Literature study
- Collect information of the assembly
- Create model and calculate the assembly flow with input data
- Document and present results
Starting date: Fall 2021
Number of students: 1
Marcus Ek/Tobias Högfeldt
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