Study about the Application of Statistical Process Control for Process Quality Improvement in Automotive Industry

Article Preview

Abstract:

SPC (Statistical Process Control) is one of the Lean Manufacturing techniques, but especially Six Sigma, being a method of improving the quality of the manufacturing process, which allows the identification of errors before their production, with the help of which a process can be supervised and when needed, it is possible to carry out an intervention of regulation, respectively of correction of the process, before being nonconformities. The paper presents a study regarding the use of SPC at a company in the automotive field in order to improve the quality of the manufacturing process for a knuckle. Thus, a number of 25 samples were taken, each sample containing a number of 5 pieces. After sampling, a series of techniques and statistical data were used, respectively diagrams and control sheets, which allowed the determination of the process capability by using MiniTab software.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

169-174

Citation:

Online since:

February 2020

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2020 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] J. Kvinn, Statistical Process Control in the Automotive Industry, 2018 Information on: http://thesisacknowledgement.net/statistical-process-control-in-the-automotive-industry/.

Google Scholar

[2] P. Bacoup, C. Michel, G. Habchi, and M. Pralus, From a Quality Management System (QMS) to a Lean Quality Management System (LQMS), J.Total Qual. Manag. 30 (2018) 20–42.

DOI: 10.1108/tqm-06-2016-0053

Google Scholar

[3] J.C. Toledo, F.L. Lizarelli, M.B. Santana, Success factors in the implementation of statistical process control: action research in a chemical plant, Int. J. Prod. 27(2017) 473-489.

DOI: 10.1590/0103-6513.220816

Google Scholar

[4] R. Godina, C. Pimentel, F. J. G. Silva, J. C. O. Matias, Improvement of the statistical process control certainty in an automotive manufacturing unit, Procedia Manuf. 17(2018) 729-736.

DOI: 10.1016/j.promfg.2018.10.123

Google Scholar

[5] J.G. Requeijo, J., Cordeiro, Implementation of the statistical process control with autocorrelated data in an automotive manufacturer, Int J Ind Syst Eng. 13(2013) 327-341.

DOI: 10.1504/ijise.2013.052280

Google Scholar

[6] P. Gejdoš, Continuous Quality Improvement by Statistical Process Control, Procedia Econ. Financ. 34(2015) 565 – 572.

DOI: 10.1016/s2212-5671(15)01669-x

Google Scholar

[7] S. Pranay S. Parmar, A. Vivek A. Deshpande, Implementation of Statistical Process Control Techniques in Industry: A Review, JETIR, 1(2014) 271-285.

Google Scholar

[8] S. Sousa, N. Rodrigues, E. Nunes, Application of SPC and quality tools for process improvement, Procedia Manuf. 11(2017) 1215 – 1222.

DOI: 10.1016/j.promfg.2017.07.247

Google Scholar

[9] I. Madanhire, C. Mbohwa, Application of Statistical Process Control (SPC) in Manufacturing Industry in a Developing Country, Procedia CIRP, 40(2016) 580 – 583.

DOI: 10.1016/j.procir.2016.01.137

Google Scholar

[10] S.J. Hu Statistical Process Control for Correlated Processes: Case Studies In Automotive Manufacturing, Int. J. Simul. Model, 16 (1996) 218-223.

Google Scholar

[11] D. R. Prajapati, Implementation of SPC Techniques in Automotive Industry: A Case Study, Int. J. Emerging Technol. Adv. Eng, 2(2012) 227-241.

Google Scholar

[12] Minitab Statistical Software Features – Minitab. Software for Statistics, Process Improvement, Six Sigma, Quality–Minitab. Information on http://https://www.minitab.com/en-us/products/ minitab/.

DOI: 10.1002/9781119975328.advert

Google Scholar