Rule-based tasks

The practical implications of this experiment are that when evaluating the effects of shift work due to circadian effects, the type of task being carried out by the worker must be taken into account. For example, skill-based tasks would be expected to exhibit the performance changes characteristic of low memory load tasks, whereas performance variations in knowledge-based tasks would be expected to follow the pattern of high memory load tasks. Performance on rule-based tasks may depend on the degree of frequency of use of the rules, which in turn may determine the memory load. If these results were confirmed by further process plant studies, it would have implications for when different types of operation (involving different levels of memory load) should be scheduled to reduce circadian rhythm effects and minimize errors. 

The certainty factor approach has been among the more popular rule-based approaches to uncertainty. However, although it is easy to apply given the individual CFs, acquiring the raw CFs from the experts is often quite difficult. Further, although the formulas for CF combination are mathematically appealing, they often have no relation to the ways in which experts combine evidence to arrive at conclusions. Some of the task-specific approaches discussed later address uncertainty combination in a more intuitive way (35). 

The development vehicle used to create and test the rule base must be as flexible as possible, allowing easy alterations and expansion of the rule base with whatever displays can convey the most information. The delivery vehicle, however, should be virtually transparent to the user, conveying only as much information as needed to solve the problem at hand. Self-tuning controllers can perform their task without explicitlv informing users, but their output and status is available on demanci, and their operation may be easily limited or interrupted. 

Perform task analysis (see Chapter 4) and identify skill, rule or knowledge-based tasks or aspects of tasks (the flow diagram in Figure 2.7 may be used to assist in this classification). 

Very often, voluminous procedures gather dust in cabinets where they have lain since the system was commissioned. For simple skiU-based tasks carried out by experienced workers, no procedural support will be necessary. Other activities such as trouble shooting or diagnosis may, as discussed in Chapter 2, involve the use of formal or mformal rules which are used infrequently. In these cases some form of job aid or checklist is the most effective type of procedure. 

Rule-Based Level of Control In the context of chemical industry tasks, the type of human information processing in which diagnoses are made and actions are formulated on the basis of rules (e.g., "if the symptoms are X then the problem is Y"). 

Rules seemingly have the same format as IF.. THEN.. statements in any other conventional computer language. The major difference is that the latter statements are constructed to be executed sequentially and always in the same order, whereas expert system rules are meant as little independent pieces of knowledge. It is the task of the inference engine to recognize the applicable rules. This may be different in different situations. There is no preset order in which the rules must be executed. Clarity of the rule base is an essential characteristic because it must be possible to control and follow the system on reasoning errors. The structuring of rules into rule sets favours comprehensibility and allows a more efficient consultation of the system. Because of the natural resemblance to real expertise, rule-based expert systems are the most popular. Many of the earlier developed systems are pure rule-based systems. 

Spectral database than currently exists. However, the automated rule generator provides the tools to accomplish this task and to expand the current rule base. 

Rule-based At the middle level, these are performance tasks that involve actions governed by training and procedures that are executed consistently by different operators across a facility. These typically correspond to written procedures learned in operations and maintenance classrooms and on-the-job training. An example of a mistake associated with rule-based performance is the omission of a step in a formal written procedure. 

Due to its complexity, a truly integrated approach is required in designing a production rule base to provide the job description for the FMS dynamic scheduler. This is because the dynamic system relies heavily on the knowledge base as represented by the rule base, and an overly restrictive rule base will lead to inefficient, at times even wrong, decisions. In other words, such a structure should represent all the multilevel interactions and their possible precedence rules that relate to the manufacturing process planning and processing decisions in an FMS. This turns out to be a difficult task. 

---