Rule-based expert system implementation

Foulkes et al. (1988) have approached the synthesis of operating procedures from a more empirical angle. They have extended the work of Rivas and Rudd (1974) for the synthesis of complex pump and valve sequencing operations, relying on the use of logical propositions (implemented as rule-based expert systems), which capture the various types of constraints imposed on the states of a processing system. 

Ignizio, J.P, An Introduction to Expert Systems The Development and Implementation of Rule-Based Expert Systems, McGraw Hill, New York, 1991. 

To find systematically the right solvents for TMS systems it appeared desirable to establish a decision tree for solvent selection [41], Subsequently this tree was implemented into an expert system program [42], This program is based on the miscibility rules of Berg [43] who classified the solvents into five groups (Table 13). 

Evolving from efforts [22] to use the best features of trial-and-error, process model, expert system, and expert model approaches, QPA [23-25] combines KBES traits with online dielectric, pressure, and temperature data to implement autoclave curing control. QPA combines extensive sensor data with KBES rules to determine control actions. These rules determine curing progress based upon process feedback, and implement control action. QPA adjusts production parameters on-line as such—within the limits of its heuristics—QPA can accommodate batch-to-batch prepreg variations. 

As an example consider the 1990 U.S. Census classification task. Free text samples from 22 million citizens were classified by assigning industry and occupation codes, based on job descriptions given in questionnaires [14]. An expert system called AIOCS was used. The rules were laboriously derived from a training data base consisting of 132 247 cases classified by human experts. The time required for the development of this system was equivalent to 192 month/person (16 years/person). Still, accuracy is rather low (Table 1). An alternative memory based system called PACE was developed in just 4 months/person and efficiently implemented on CM-2 parallel computer. 

The heart of any expert system consists of a set of rules, sometimes referred to as a rule base or knowledge base, which has been put together by experts . The question of course arises of how to define (or find) the experts, but for the purposes of this discussion an expert is any human who has an opinion on the particular problem to be solved Expert systems are usually, but not necessarily, implemented on a computer (see, for example, the structural alert system later in this section). 

The overall expert system is made up of two major components. One component is a knowledge base consisting of a set of evaluation rules implemented using an expert system shell called EXSYS [2], presently being restructured for implementation in a more sophisticated expert system shell called GURU [5]. The second component is a set of programs implemented in PASCAL to overcome many of the limitations inherited in an expert system shell. This includes a customized user interface, incorporation of several types of data... 

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