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An Expert System for Corrosion Characterization using Artificial Neural
Network (ANN)
Nurarjuna Athirah binti Ramli
Supervisor: Dr. Ahmad Faisal bin Mohamad Ayob
Bachelor of Applied Science (Maritime Technology)
School of Ocean Engineering
Universiti Malaysia Terengganu
Corrosion is one of the main problems that happen in the industries related to marine
(vessels and oil & gas). Corrosion is difficult to measure and predict, which usually
require a trained-eye specialist to classify traditionally. Therefore, classification activity
tends to be expensive while a preliminary screening system can be hypothesized to
works better to be operated by non-specialist. Hence to overcome this problem, an
Artificial Neural Network (ANN) shall be trained to classify corrosion types. This
networks are forms of artificial intelligence that learn correlative patterns between
input and output information without a specific model. In this work, ANNs are
incorporated to make predictions to identify corrosion. It is hypothesized that the
resulting network shall act as an expert system which be able to provide an easy way
to perform data input, followed by confidence level checks from the neural network
as output. Ultimately, through the utilization of ANN, the characterization process for
corrosion became faster and more efficient.
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