Diagnostic system instrumentation

Consider again a batch polymerization process where the process is characterized by the sequential execution of a number of steps that take place in the two reactors. These are steps such as initial reactor charge, titration, reaction initiation, polymerization, and transfer. Because much of the critical product quality information is available only at the end of a batch cycle, the data interpretation system has been designed for diagnosis at the end of a cycle. At the end of a particular run, the data are analyzed and the identification of any problems is translated into corrective actions that are implemented for the next cycle. The interpretations of interest include root causes having to do with process problems (e.g., contamination or transfer problems), equipment malfunctions (e.g., valve problems or instrument failures), and step execution problems (e.g., titration too fast or too much catalyst added). The output dimension of the process is large with more than 300 possible root causes. Additional detail on the diagnostic system can be found in Sravana (1994). 

The specific diagnosis according to a diagnostic system (DSM-IV, ICD-10 or other established classification instrument). 

Operational and maintenance plans should be prepared for the computer system and its associated measurement and control instrumentation. Operational plan review will focus on system reliability, performance, diagnostic records, instrument and system I/O calibration, and the provision of critical data to support the batch record. Procedures for controlling the system (e.g., system management, security, and process operations) should be reviewed to verify that they are current, in place, and being followed. For each procedure required for the system there should be documented evidence that the relevant operatives have been trained in its use. All procedures must be written and approved according to the site procedures for writing and approving SOPs. 

Roche Diagnostic Systems, Mira Instrument, 1 Sunset Avenue, Montclair, NJ 07042. 

Level 2, for the control of abnormal operation and the detection of failures, is to be reinforced (for example by more systematic use of limitation systems, independent from control systems), with feedback of operating experience, an improved human-machine interface and extended diagnostic systems. This covers instrumentation and control capabilities over the necessary ranges and the use of digital technology of proven reliability. 

To achieve effective monitoring and diagnostics of turbomachinery, it is necessary to gather and analyze both the mechanical and aerothermal operating data from the machines. The instrumentation and diagnostics must also be custom tailored to suit the individual machines in the system, and also to meet the requirements of the end users. The reasons for this are that there can be significant differences in machines of the same type or manufacturer because of differences in installation and operation. 

Each of the subsystems can, apart from the others, make a significant diagnostic contribution. For example, the instrumental cell isolation and sample handling component could be used with DNA-based or other non-MS systems for detection and/or identification. As another example, the principles underlying pattern drift compensation can apply to MALDI MS and even non-MS detection systems such as capillary GC of fatty acid methyl esters. 

T. Schulte, personal communication, Becton Dickinson Diagnostic Instrument Systems, Towson, Maryland 1989. 

The decision for each example is expressed as an "action-next state" pair. The "action" is a reference to executable Radial code, which consists of a sequence of Radial statements. These statements may contain references to external programs in various languages (this will be discussed further later). The "next state" describes the context to which control is to pass after the action is completed. For diagnostic expert systems, such as TOGA, the next state will usually be the "goal" state of the module. This passes control back to the calling module. For procedural expert systems, such as robotics and instrumentation control applications, the control will be transferred between several states within a module to Implement looping. 

---