ID87.1 Application of control charts for monitoring the machining process of the inside diameter of a steel cylinder Murilo T. Maia*, Elisa Henning**, Olga M. F. C. Walter***, Andrea C. Konrath + , Custodio C. Alves ++ * Production and Systems Department, Santa Catarina State University, Campus Avelino Marcante, 89219-710, Joinville-Santa Catarina, Brazil **Department of Mathematics, Santa Catarina State University, Campus Avelino Marcante, 89219-710, Joinville-Santa Catarina, Brazil ***Production and Systems Department, Federal University of Santa Catarina, Campus Trindade, PO Box 476 - 88040-900, Florianópolis-Santa Catarina, Brazil + Department of Computer Science and Statistics, Federal University of Santa Catarina, Campus Trindade, PO Box 476 - 88040-900, Florianópolis-Santa Catarina, Brazil ++ Production and Systems Department, University of the Region of Joinville, Tenente Antônio João St., Bom Retiro, PO Box 246- 89201-972, Joinville-Santa Catarina, Brazil Email: murilot.maia@gmail.com, dma2eh@joinville.udesc.br, olgaformigoni@gmail.com, andreack@gmail.com, custodio.alves@univille.net. Abstract The quality of products and processes has proven to be crucial for companies to compete in the market. The Statistical process control enables them to foresee problems in the process, thereby ensuring the quality of manufactured items. This paper aims to present a proposal for monitoring a machining process, with the help of this tool using control charts. This research arose from the need of monitoring the rectification process of the inside diameter of a steel cylinder, a component of a product manufactured in a company in southern Brazil. The parameters must follow the design specifications, so the final product will not have performance problems. Thus, for the monitoring of this process are applied Shewhart X -S control charts for three measurements performed in sections of a cylinder, analyzing them separately. To complement, a multivariate chart Hotelling's T 2 is applied to monitor simultaneously these three measurements. The two approaches are compared in terms of performance and usage aspects. The results obtained in terms of performance were similar. However, the Shewhart control chart is easier to use and simpler to interpret by staff. The results enabled the company to know the stability of the process, facilitating the decision-making on actions taken for improvement. Keywords: Statistical Process Control, Shewhart chart, Hotelling's T 2 chart, Machining process. 1 Introduction The quality of products and processes has proven to be crucial for companies to compete in the market. Statistical process control (SPC) is an efficient and powerful formal technique used for monitoring processes. It allows us to predict problems in the process, ensuring the quality of the items that are produced. SPC consists of a collection of tools for resolving problems, useful in obtaining a stable process. The control chart is one such tool, and probably the most technically sophisticated (MONTGOMERY, 2004). A control chart is a visual statistical tool that highlights the presence of special causes. It basically consists of plotting lines representing the Upper Control Limit (UCL) and Lower Control Limit (LCL), the mean or target of the process (Central Line - CL) and the observed points, which represent, in general, a statistic related to the variable of interest. If one or more points are beyond the control limits, it indicates that the process can be out of statistical control, i.e. there may be a problem in the process (SAMOHYL, 2009). The most popular univariate control chart for variables is the Shewhart control chart, which achieved success due to its simplicity. In the industrial process there are many situations that require simultaneous monitoring and control of more than one quality characteristic. Monitoring these quality characteristics independently is possible,