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Expert System

Last updated: June 2, 2020

What Does Expert System Mean?

Expert systems are knowledge-based computer systems that have been developed to reduce erratic human influence. It makes or evaluates decisions based on rules established within the software.

Expert systems are part of a general category of computer applications known as artificial intelligence. To design an expert system, one needs a knowledge engineer, an individual who studies how human experts make decisions and translates the rules into terms that a computer can understand.

Expert system can be used in corrosion problem solving, such as:

  • Corrosion monitoring
  • Material selection
  • Equipment specification
  • Control of corrosion testing equipment
  • Training
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Corrosionpedia Explains Expert System

An expert system is a computer program that simulates the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field, such as corrosion. Expert systems are used in the field of corrosion to monitor and evaluate corrosion.

Some applications of expert systems are in different aspects of corrosion, cathodic protection and assessment of cracking in light water nuclear reactors and prediction of localized corrosion of stainless steels.

Developments in computer tools for corrosion assessment and control have been quite extensive including databases. Some specific examples of computer systems for different applications are:

  • Programs for selection of materials for oil and gas applications
  • Programs for online corrosion monitoring and control
  • Database systems for evaluation of metals and non-metals
  • Use of neural networks in corrosion data reduction
  • Computer-aided packages for teaching corrosion

Currently, computer programs for corrosion assessment and control use a combination of expert systems and an object-oriented programs such as evaluation of hydrogen-induced cracking of steels, or a combination of expert systems and neural networks in corrosion data modeling and prediction.

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