Although computers are used to model a variety of engineering activities, at present the main focus of computer applications are areas with well defined rules, such as sophisticated analysis, graphical and CAD applications. Activities related to the decision making process, particularly where there are no defined rules of heuristics, are very little covered by computers.

In the past Knowledge Based Expert Systems (KBESs) tried to model some of the activities related to the decision making process. Due to the restricted scope of these systems, their success was very limited.

Artificial Neural Networks (ANNs) are Artificial Intelligence (AI) applications which can, to some extend, imitate the activities of the human brain. Like human experts, artificial neural networks are capable of learning and generalising from examples and experience to produce meaningful solutions to problems even when input data contain errors or is incomplete. This makes ANNs a powerful tool for solving some of the complicated engineering problems.

The current paper will discuss some guidelines related to designing better networks to solve engineering problems.

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