Thesis Type: Postgraduate
Institution Of The Thesis: Bursa Uludağ University, Fen Bilimleri Enstitüsü, Turkey
Approval Date: 2020
Thesis Language: Turkish
Student: UTKU ERDEM KAYNAR
Supervisor: Yahya IşıkAbstract:
In the Automotive World to improve the quality of the finished product and the processes that make up the product. The most important of these trends are mostly using advanced technology to keep production processes under a certain control regime. In this study, the Early Warning System model, which promises a preventive Statistical Process Control method, has been examined. Early Warning System is a technology that aims to make corrective action to the required units as a preventive signal by signaling geometrical (gap-profile) errors that may occur on the vehicle before leaving the assembly line. In this study applied in the Measurement Center of the TOFAŞ factory, the Early Warning System, which can offer a far superior alternative to the traditional Statistical Process Control, was examined. In this study, Early Warning System and its algorithmic, theoretical infrastructure (point cloud technology, flush & gap methodology etc.) are explained. Contributions to the sector with concrete examples and its difference from traditional statistical process control are examined. The infrastructure of the system was explained using the TOFAŞ module, which is written on Polyworks, a measurement program. The contribution of this system to the academic literature and the improvements in the sector are explained with the improvements in processes (KPI).