For any manufacturing process, one of the key challenges after a solid foundation has been built is how improvements can be made. Management has to consider how possible changes will affect both the process as a whole in addition to every individual part before implementation. The groundwork for this is to have a clear overview of every part and the possibility to investigate effects of changes. This thesis thus aims to provide a clear overview of the complex painting process at Volvo GTO in Umeå and a template for investigating how differently implemented changes will affect the process. The means for doing this is to use statistics, modeling and discrete event simulation. Modeling shall provide an approximate recreation of reality and the subsequent analysis shall take into account similarities and differences to estimate the effects of changes. Recreation of real-world data and variability is based on bootstrap resampling for multiple independent weeks of observations. Results obtained from simulation are compared to observed data in order to validate the model and investigate discrepancies. Given the results of model validation, modifications are implemented and information obtained from model validation is used to evaluate the results of the modifications. Further, strengths and weaknesses of the thesis are presented and a recommendation of altering the stance on process improvements is provided to Volvo GTO.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-197778 |
| Date | January 2022 |
| Creators | Alishev, Boris, Kågström, Oskar |
| Publisher | Umeå universitet, Institutionen för matematik och matematisk statistik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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