A Neuro-Expert Approach for Decision -Making in Welding Environment.

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

Assessment of applications for the house renovations grants system : an IT support framework

This thesis describes the development of a knowledge-based framework for supportinghuman experts from the Department of Environmental and Consumer Services of theSalford City Council in assessing applications for the current house renovation grant system(HRGS).The resulting system implements an architecture which integrates case-based reasoningprocesses with other problem solving methods. In addition, the system's architectureintegrates different types of knowledge which are required by the problem solving methods.Some of the main features of the system's architecture are its modularity and itsindependence from the implementation shell. The system was implemented using Kappa-PC which is a shell designed for implementing knowledge-based systems.The implementation followed the Client Centred Approach method. A number of lessonswere learned from the implementation process. The implementation was carried outtogether with the verification and validation of the system. The verification and validationmethods employed allowed the author to focus the evaluation on different features andcomponents of the system. A number of test cases were employed during the validation.Client's experts and other independent experts were involved in the validation of thesystem. Each validation step was followed by refinement of the main system's components.This research has demonstrated that various problem solving methods are required forperforming the different tasks of the assessment of applications for the HRGS. Theimplemented system has been reasonably successful in demonstrating that a singleframework which integrates various methods can be used for supporting human experts inassessing applications for the FIRGS. Therefore, the system has proved to perform asaccurately as human experts do for all of the tasks. The system has been described as verypromising by the Client's experts