Industrial continuous processes are usually operated under closed-loop control, yielding process measurements that are autocorrelated, cross... Show moreIndustrial continuous processes are usually operated under closed-loop control, yielding process measurements that are autocorrelated, cross correlated, and collinear. A statistical process monitoring (SPM) method based on state variables is introduced to monitor such processes. The statistical model that describes the in-control variability is based on a canonical variate (CV) state space model. The CV state variables are linear combinations of the past process measurements which explain the variability of the future measurements the most, and they are regarded as the principal dynamic dimensions. A T-2 statistic based on the CV state variables is utilized for developing the SPM procedure. The CV state variables are also used for monitoring sensor reliability. An experimental application to a high temperature short time (HTST) pasteurization process illustrates the proposed methodology. Endnote format citation Show less
Statistical process monitoring (SPM) is used in food processing industries to improve productivity and product quality. SPM can also provide... Show moreStatistical process monitoring (SPM) is used in food processing industries to improve productivity and product quality. SPM can also provide information to operators on how close a process is to non-compliance to product safety limits, and carry out periodic checks of sensor accuracy at high frequency. Traditional SPM tools such as Shewhart charts are not appropriate for continuous food processes because of autocorrelation in data. Four alternative SPM techniques are presented and applied to high temperature short time (HTST) dairy pasteurization. The study attempted to achieve compliance of the HTST process operation with the recommended Pasteurized Milk Ordinance by providing a margin between the alarm limits of the monitoring chart and the safety limits. Monitoring of residuals and parameter change detection techniques ave used for monitoring processes with autocorrelated variables. Hotelling's T-2 and residuals of canonical variates techniques are used for monitoring multivariable processes. Endnote format citation Show less
