An intelligent control chart for monitoring of autocorrelated egg production process data based on a synergistic control strategy

Monitoring livestock production processes by means of statistical control charts can provide an important support for management. The non-stationary and autocorrelated characteristics of most data originating from such processes impede the direct introduction of these data into control charts. To deal with these characteristics Engineering Process Control strategies can be applied. Stationarity was achieved by modelling and subtracting the time dependent trend using a non-linear model. Next, the autocorrelation structure in the residual data is modelled and corrected for by means of an ARMA model. The resulting corrected stationary and independent residuals are then inserted in the traditional cusum control scheme. This combined use of Engineering Process Control strategies for modelling the unconventional statistical characteristics and Statistical Process Control strategies for constructing the control chart based on the resulting pre-processed data, is referred to as a Synergistic Control strategy. The developed cusum control chart was tested on data of two layer flocks. In both cases the control chart provided alarms for important problems in production and furthermore signalled problems that remained unnoticed by the layer managers. The amount of false alarms was acceptable. With this control scheme and the scheme of the average egg weight, control procedures for two important output parameters of the production process of consumption eggs are available. Furthermore, this strategy could provide a possible solution for other process parameters that also display non-stationarity and autocorrelation.