Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Construction Management

First Advisor

T. Warren Liao


Decision making in welding is very important for achieving a good quality welded joint for the least possible cost. Of particular interest is decision making involving the selection of process, parameters, weld procedure specification, defect analysis and trouble shooting. This research has provided a means of capturing the planning knowledge in a Neuro-Expert System in a form that is capable of learning new information, correcting old information and automating the decision-making process in a welding environment. A strategy is formulated for the representation of knowledge in the form of a neural links and the translation of rules into neural link weights. After training those weights were converted back into rules to find out the inconsistent rules and capture new rules using a new approach. The various job variables affecting the process of welding are identified in detail and a Neuro-Expert system for the selection of process, parameters and weld procedure specification is developed. The neural networks are integrated with an expert system for decision making in welding environment. Apart from providing the initial parameters of welding, the expert system is used to validate the output of the neural network and served as a user-friendly interface for the neural network. Defect Analysis is performed in welding domain by mapping the welding parameters and defect patterns in a neural network. A neural network based approach for representing the knowledge in expert system is utilized for this purpose as the modification and updating of the knowledge was easier.