(638e) Application of Data Reconciliation, Gross Error Detection and Real Time Optimization for Continuous Pharmaceutical Manufacturing
Today pharmaceutical manufacturing still consists mainly of batch unit operations, which offer versatility and a means of tracking. However, recent focus has been on shifting the pharmaceutical manufacturing into a more continuous process in an effort to reduce the manufacturing costs and cycle times. Two of the automation tasks that must be addressed for effective continuous manufacturing are process monitoring and control. Monitoring and control are crucial to ensure consistent product quality and process economy. In order to operate at or near optimal conditions, an integrated control strategy which considers the entire production line is required.
The integrated control strategy will be encompassed in a real time process management (RTPM) system, which consists of two subsystems ? real time optimization (RTO) and anomalous events management (AEM). These two subsystems will work together to identify gross errors, detect and diagnose faults, estimate and update model parameters, and suggest appropriate action to take to maintain optimal conditions all in real time. For the optimization, steady-state and, as appropriate, dynamic real time optimization (Tosukhowong, Lee et al. 2004) will be used in order to be sure that the process operates at optimal or near optimal conditions throughout the process life cycle.
In this work, an initial reduced set of functionalities is being explored for the monitoring and control of continuous pharmaceutical manufacturing. These functionalities include the use of data reconciliation, gross error detection and steady-state real time optimization. There have been numerous applications of these concepts in the past, in particular: the use of RTO in the petrochemical industry, which have proven to be successful (Yoon and Mijares 1996); an application of RTO to the pulp mill benchmark problem (Mercangöz and III 2008); and the use of RTO in an off-gas distribution system for iron and titanium (Woodward, Srinivasan et al. 2007). However, the application to continuous pharmaceutical manufacturing has not been developed to its fullest, especially for drug finishing steps such as a tableting line. This issue is addressed in this work by applying an integrated control strategy, which includes process models for optimization and control, to a continuous tablet manufacturing line ? consisting of continuous feeders, blender, roll compactor, milling, and tablet press. We will present results of this approach for industrially inspired examples of anomalous events such as changes in the raw material properties. These feed changes may require changing the set points of the key variables associated with several of the downstream unit operations in order to insure that the tablet strength and other product properties remain within acceptable limits. The optimal values of these set points are thus determined be the RTO block.
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