Title: Implementation of the statistical process control with autocorrelated data in an automotive manufacturer
Authors: José Gomes Requeijo; Joana Cordeiro
Addresses: UNIDEMI, Faculty of Science and Technology, Department of Mechanical and Industrial Engineering, New University of Lisbon, Caparica 2829-516, Portugal ' UNIDEMI, Faculty of Science and Technology, Department of Mechanical and Industrial Engineering, New University of Lisbon, Caparica 2829-516, Portugal
Abstract: The continuous improvement on quality of products and processes is a constant concern at organisations, as a response to growing competition and demands of the market. The implementation of statistical techniques adjusted to different situations is one way to achieve this goal. The application of traditional control charts requires that collected data are independent and identically distributed. However, this is not always assured, reflecting a drastic increase of false alarms. This paper presents a methodology for the traditional univariate control charts application, when data exhibit significant autocorrelation. To obtain the residuals and predictive errors, the suggestion is to use the ARIMA methodology of Box and Jenkins. Implementation took place in the painting process from an automotive company, providing continuous adjustment of the same and statistically grounded, enabling the organisation to produce vehicles with greater quality assurance, lower costs and an advantageous position against their competitors.
Keywords: statistical process control; SPC; Shewhart control charts; autocorrelated data; ARIMA models; MCEWMA chart; EWMAST chart; automotive manufacturing; automobile industry; continuous improvement; vehicle painting; quality assurance.
International Journal of Industrial and Systems Engineering, 2013 Vol.13 No.3, pp.325 - 344
Available online: 26 Feb 2013 *Full-text access for editors Access for subscribers Purchase this article Comment on this article