Knowledge-based evaluation

Chin, K. S., Wong, T. N., Knowledge-based Evaluation for the Concq)tual Design Development of Injection Molding Parts,... 

To become familiar with a knowledge-based reaction prediction system To appreciate the different levels in the evaluation of chemical reactions To know how reaction sequences are modeled To understand kinetic modeling of chemical reactions To become familiar with biochemical pathways... 

If the nature of the problem is not readily apparent, then it might be necessary to go to the rule-based level. In this case a diagnostic rule will be applied to identify the state of the plant and an action rule used to select an appropriate response. Control will revert to the skill-based level to actually execute the required actions. More abstract functions such as situation evaluation and planning will only be required at the knowledge-based level if the problem cannot not be resolved at the rule-based level. 

Perform task analysis and classify skill, rule or knowledge-based behaviors involved in the scenario being evaluated. 

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. 

Sotriffer CA, Gohlke H, Klebe G. Docking into knowledge-based potential fields a comparative evaluation of DrugScore. J Med Chem 2002 45 1967-70. 

Sravana, K. K.. Diagnostic Knowledge-Based systems for batch chemical processes hypothesis queuing and evaluation," PhD Thesis, The Ohio State University (1994). 

D5mamic models create a framework to integrate the knowledge bases that exist within a pharmaceutical firm s functional divisions for the purposes of evaluating an NCE s potential. The approach establishes practical boundaries on the realm of possible outcomes from a commercial assessment, providing a solid foundation for reasonability checks of the financial potential for an NCE. As... 

Wu and Joseph [35] incorporated fuzzy logic into a knowledge-based control system for control of composite curing. They used the fuzzy logic to interpret the sensors and adjust the amount of control reaction on a simulated process. Even though the limitations of the simulator used did not allow full evaluation of the advantages of this system, it did show that the controller could react to material and process variations and improve the process plan. 

Process owners must be capable to evaluate and interpret the effect of nonconformances and planned deviations on their systems. Process owners can evaluate the need and lead efforts for corrective or preventive action, ensuring adequate corrections and improvements are implemented. An effective QMS ensures deviations from approved processes are owned and adequately investigated by the process owner s and ultimately approved by their quality assurance counterpart. The knowledge of these events is the basis and foundation for the process owners to make a risk-based evaluation on whether or not process changes are required, documentation or training require modification, or continuous improvement efforts are warranted. 

Manzer s team had to address a challenge involving two incompatible factors. He needed a carbon catalyst that would promote the efficient and selective chlorination of carbon monoxide but that would remain inert for chlorinating the carbon catalyst surface. Through many years of experience the DuPont team has built a knowledge base and scientific network that led to the Boreskov Institute of Catalysis in Novosibirsk, Russia. Alliances with international research facilities are a major trend in external programs. The team at Novosibirsk had developed a unique series of specialty carbon materials and supports. The DuPont team evaluated variations of these specialty carbon materials, and within less than a year and a half the catalysts became operational at the DuPont Deepwater Plant. 

A separate class of experimental evaluation methods uses biological mechanisms. An artificial neural net (ANN) copies the process in the brain, especially its layered structure and its network of synapses. On a very basic level such a network can learn rules, for example, the relations between activity and component ratio or process parameters. An evolutionary strategy has been proposed by Miro-datos et al. [97] (see also Chapter 10 for related work). They combined a genetic algorithm with a knowledge-based system and added descriptors such as the catalyst pore size, the atomic or crystal ionic radius and electronegativity. This strategy enabled a reduction of the number of materials necessary for a study. 

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