Journal of Material Sciences & Engineering

Statistical Process Control Applied in the Chemical and Food Industry

Abstract

Pedro Pablo Angeles Chero

Statistical process control (SPC) is a tool to improve the quality and productivity of processes. The objective of this research was to apply statistical control charts in chemical and food industrial processes and highlight their advantages in the control of processes. For the study, the control data of the processes of 4 industrial plants was used: rectified ethyl alcohol distillation plant, asparagus processing plant, soluble coffee production plant and light liquid fuel production plant. The deductive methodology was applied, based on the type of data: variable or attribute, constant or variable sampling, evaluation of the defective fraction, number of defects, variability of processes. With this, the statistical control chart suitable for the process was selected. The results showed that in the food industry the np and p charts can be used to evaluate the defective fraction and for the number of defects, as was the case in asparagus cans, u and c graphs are used. To control variables, the charts used were XmR, XbarR, Xbar Trend, Fixed limits and XbarS. It was concluded that the control charts in the chemical and food processes is not only applicable, but it allows predicting the behavior of the process and alerts when it tends to go out of control, thus allowing improving the quality.