Figure 5: Queue based control of the quality analysis systems.
Orbit real-time database and data analysis
The processing platform with support systems discussed above generate a lot of data in form of structural information, input and control signals, detector signals, HPLC analysis, on-line software computations etc. The on-line generated data is heterogeneous, i.e. different types, asynchronous, i.e. in-line detectors vs advanced quality analysis, and distributed, i.e. generated on multiple physical detectors and different setups. A database was needed to handle real time process data and made it practical to handle for both local and plant-wide data analysis.
General tools for automatic data analysis of real-time data, on-demand at-line or off-line analysis, are important for process monitoring and process control. One example is the peak analysis of the PCC operation in the pilot-scale case study in Schwartz et al 2022. In Figure 6 the first two switches in the PCC are shown together with the automatic peak finder with associated peak measurement. The peak heights are plotted on right where peak B is the interesting product peak. As seen the three different PCC column do not behave exactly the same. They have slightly different peak heights, about 3% difference.
This kind of data analysis is based on the data stored in the database, which come from different sources in the process. In this case it was actually only from one detector on one setup, but in the general case it allows plant-wide data analysis using distributed data sources. Data analysis processing can be performed locally at the setup with the detector or at the setup needing the analysis results. An alternative suggested here is a plant-wide computational extension, in an orbitX controller, exploiting data in the database to perform more or less advanced data analysis for usage somewhere in the processing system or just for plant-wide monitoring. More advanced data analysis for data-driven modelling and machine learning are often performed off-line, but in some cases the results need to be validated in real-time. The architecture suggested here allow both off-line development and on-line validation.