Determination of Factors and Quality Control of Car Painting Based on FMEA and SPC.V2

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DOI: 10.4236/mme.2018.82011    2,932 Downloads   11,504 Views  Citations

ABSTRACT

The global automotive industry demands world-class levels of product quality, productivity, and competitiveness as well as continual improvement. To achieve this goal, many vehicle manufacturers companies use quality control tools to improve the quality of the product with zero defects and highly satisfied to the customer. Nowadays, there are a lot of quality tools applied to solve the problem quickly but it’s still the fact to find out good and efficient solving way. The study emphasizes the identification of potential failure which failures may have encountered in the production process and it will lead to car scrap, rework and influence of the internal production and quality target. After the complete study of the manufacturing process and production data-failure causes, failure rate and data etc. FMEA discover the weak processes in the form of higher risk priority number in the manufacturing of the car painting process, which required reducing by identifying and implementing of the defects and this will improve the process quality of the painting surface of the car. To analysis, the improvement of the car surface defects SPC (Statistical Process Control) tools are more efficient where can easily visible the defects trends. SPC chart is chronological graphs of process data that are used in manufactures industries to help understand, control and improve the process and that although based on statistical theory area easy for practitioners to use and interpret. In order to orient goal of zero defects of the car, surface uses the PFMEA technique to prioritize the defects and statistically analyze the roots cause of the defect and control the defects through continues improvements process.

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Rana, M. , Zhang, X. and Akher, S. (2018) Determination of Factors and Quality Control of Car Painting Based on FMEA and SPC.V2. Modern Mechanical Engineering, 8, 158-177. doi: 10.4236/mme.2018.82011.

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