Quality control for automotive paint process under lean Six Sigma environment
DOI:
https://doi.org/10.29105/mdi.v8i12.253Keywords:
Quality Control, Lean Six Sigma, Automotive Industry, Statistical Control ProcessAbstract
Quality control is a fundamental aspect to ensure the efficiency of manufacturing processes, especially in industrial sectors where product safety is essential for users, as is the case in the automotive sector. In this work, the aim is to make engineering researchers and students aware of the development of the quality control process of the painting area within an Original Equipment Manufacturer (OEM), under a Lean Six Sigma environment.
Lean Six Sigma is a philosophy that allows us to identify, focus and improve the quality of services and products, with an emphasis on waste elimination, focus on value-added steps and a statistical process that allows us to measure the capacity of our system to meet customer requirements trying to reach 3.4 defects per million through data-based decision making.
Quality control under Lean Six Sigma focuses specifically on the critical quality characteristics of a product, not the product itself. The final result of the product is always determined by what happens during the process, specifically it is based on prevention of defects and not control of defects. During the development of the project, the solution of a problem will be shown through the implementation of concepts and Statistical tools based on the DMAIC methodology.
References
Barbosa, B., Pereira, M., Silva, F. y Campilho. (2017). Solving Quality Problems in Tyre Production Preparation Process: A Practical Approach. Procedia Manufacturing. 11. 1239-1246. DOI: https://doi.org/10.1016/j.promfg.2017.07.250
Cunha, C. y Dominguez, C. (2015). A DMAIC Project to Improve Warranty Billing’s Operations: A Case Study in a Portuguese Car Dealer. Procedia Computer Science. 64. 885-893. DOI: https://doi.org/10.1016/j.procs.2015.08.603
Fahey, W., Jeffers, P. y Carroll, P. (2020). A business analytics approach to augment six sigma problema solving: A biopharmaceutical manufacturing cas study. Revista Computers in Industry. 116. DOI: https://doi.org/10.1016/j.compind.2019.103153
Krishna, P., Jayakumar, V., y Kumar, S. (2020). Defect analysis and lean six sigma implementation experience in an automotive assembly line. Materialstoday Proceedings. 22. 948-958. DOI: https://doi.org/10.1016/j.matpr.2019.11.139
Maia, M., Pimentel, C., Silva, F., Godina, R. y Matias, J. (2019). Order fulfilment process improvement in a ceramic industry. Revista Procedia Manufacturing. 38. 1436-1443. DOI: https://doi.org/10.1016/j.promfg.2020.01.144
Mast, J. y Lokkerbol, J. (2012). An analysis of the Six Sigma DMAIC method from the perspective of problema solving. Revista International Journal of Production Economics. 139(2). 604-614. DOI: https://doi.org/10.1016/j.ijpe.2012.05.035
Nandakumar, N., Saleeshya, P. y Harikumar, P. (2020). Bottleneck Identification And Process Improvement By Lean Six Sigma DMAIC Methodology. Materialstoday: Proceeding. 24. 1217-1224. DOI: https://doi.org/10.1016/j.matpr.2020.04.436
Pinto, G., Silva, F., Campilho, R., Casais, R., Fernandes, A. y Baptista A. (2019). Continuos improvement in maintenance: a case study in the automotive industry involving Lean tools. Revista Procedia Manufacturing. 38. 1582-1591. DOI: https://doi.org/10.1016/j.promfg.2020.01.127
Smetkowska, M. y Mrugalska, B. (2018). Using Six Sigma DMAIC to Improve the Quality of the Production Process: A Case Study. Revista Procedia – Social and Behavioral Sciences. 238. 590-596. DOI: https://doi.org/10.1016/j.sbspro.2018.04.039
Srinivasan, K., Muthu, S., Devadasan, S. y Sugumaran, C. (2014). Enhancing Effectiveness of Shell and Tube Heat Exchanger through Six Sigma DMAIC Phase. Revista Procedia Engineering. 97. 2064-2071. DOI: https://doi.org/10.1016/j.proeng.2014.12.449
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
