Aplicação de cartas de controle nas análises de rotina do laboratório de qualidade do leite da Embrapa Gado de Leite

Abstract

The control chart is a graphic tool used by "Statistical Process Control" (SPC). This graphic displays the tolerance range which establishes upper (UCL) and lower (LCL) control limits in addition to a center line statistically established for the process. This tool, besides determining the stability of the process, is useful to distinguish between common and special causes. This study aimed implement control charts in the Milk Quality Laboratory (LQL) at Dairy Cattle Research Center (Embrapa). The control charts of check-samples results are used to monitoring the automated equipment repeatability. These check-samples, applied in routine analysis, are those prepared in the laboratory using raw cow milk. For this purpose it has been collected 10 L of raw milk constantly stirred in the sampling process. This volume was subsequently fractionated in 40 ml polypropylene flasks, containing specifics preservatives used for somatic cells (SCC) and total bacterial (TBC) count analysis. One set (20 samples), randomly selected, of this check-samples were subsequently analyzed in the automated equipment. The results obtained have then been used to get the mean, UCL and the LCL. The check-samples used in the routine analysis have been inserted one of them at every each 60 customer samples analyzed and generate control charts with the results. The control charts was developed by LQL, using the software "Excel", and compared with the control charts generated by the software "Minitab", using 3 sigmas around the mean. The control chart for component fat is stable when is used 10 % control limits. The process became more strict when is used the 3 sigmas limits and enable mistakes risks. The protein control chart was highlighted the need to outliers evaluation. The lactose control chart has been the need an in-depth knowledge of the process, thus avoiding breaks in the routine analysis based on graphical display behavior. The total solids control chart shown the robustness of the tool when compared with others already validate in the market. The both tools used for the SCC control chart retained the regularity over time. In this specific control chart it was possible to stress the importance of the analyst visually checking to trigger corrective action when notice changes and trends in the chart. The carryover effect in the routine analysis impact the CTB Control Charts and has shown the necessity to check outliers samples occurrences. Using control charts it was possible verify the behavior displayed by the check samples in the analytic process run, which allows spot deviations, and assisting in decision making. Whereas the control charts was developed using the software “Excel”, an easy-to-use and low-cost tool, it is very robust and viable.