Graphical control/analysis

The LIMS software is essentially a database for tracking, reporting, and archiving lab data as well as scheduling and guiding lab activities. Graphical and statistical treatment of data for improved process control (qv) as well as preparation of certificates of analysis (COA) for the customer are some of the other features of a comprehensive LIMS package (30). 

The process monitors and controllers typically also have the capabiUty for data logging, analysis, and display. This capabiUty has made on-line control of pilot plants, as well as commercial-scale processes, desirable. Pilot-plant appHcations for on-line control have been described (106), and the use of such systems for both monitoring and process diagnosis has been discussed (107). A number of commercially available process control programs that mn on microprocessors have been reviewed (108). Virtually all of them incorporate graphic display as an integral part of the interactive capabiUty of the program. 

The creation and analysis of process flow sheets has become much easier because of the availabihty of automated systems to draw and revise them. The goal of the use of the flow sheet as the input for process simulation and for process control is likely to be achieved reasonably soon. The use of interactive graphic displays for process monitoring and control is pervasive today. 

Evans, W.R. (1948) Graphical Analysis of Control Systems, Transactions of the AIEE, 67, pp. 547-551. 

Figure 3. Example of Graphical Output from Analysis Mode. Reaction progress for water-jacketted reactor, with Cascade coupled temperature controllers, both in self-tuning mode.

As the analysis progresses, evidence is accumulated supporting the presence or absence of defined substructures. The evidence is combined by the Reasoner module to form a belief function, which describes the degree to which each substructure is currently believed. This information is stored in the chemical database, where it is available to the Expert modules and to the Controller as it decides the course of the analysis. As the belief function evolves, the current state is displayed graphically to the user, who may halt the analysis, query the current state, and redirect the course of the analysis by supplying evidence for or against a substructure. 

Table 7.2 shows the control computer s operation in the Glaxo system. It can be seen that all aspects of the system can be initiated and tested before starting the analysis. The system is modular and can easily be configured according to users preferences. Data can be displayed in either a tabular format or as a graphical display, to suit user requirements. 

The SIMCA approach can be applied in all of the four levels of pattern recognition. We focus on its use to describe complex mixtures graphically, and on its utility in quality control. This approach was selected for the tasks of developing a quality control program and evaluating similarities in samples of various types. Principal components analysis has proven to be well suited for evaluating data from capillary gas chromatographic (GC) analyses (6-8). 

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