Control estadístico de procesos multivariantes en la industria Alimentaria: implementación a través del estadístico t2-hotelling

there are many situations in industry, in which the simultaneous monitoring of two or more related quality variable of the production process is necessary. process monitoring problems in which several related variables are of interest are known as multivariate statistical process control (mspc). this article aims to implement the mspc in food industrial plants. this implementation consists of four elements: mspc plan, mspc training, team approach, and management involvement. mspc plan consists of two practical tools, which are method of model of mspc, and mspc diagnosis. method of model of mspc supports the practitioners to construct final historical data set. it covers the situation of using shewhart control charts, and using mspc control chart. mspc diagnosis is designed to identify the out-of-control variable in a multivariate control chart. these four elements conform a whole system that incorporates technical aspects like finance, management and organization. the mspc was implemented in the food processing plants. specifically, in a cooked flour production processing plant, a real application of three quality variables in the endosperm lamination process is analyzed. main conclusion shows that the mspc implementation guideline is feasible due to its simplicity, graphical format associated with available software, and high compromise to incorporate plant management, analyst and employees.