In the present study, forward and reverse mapping problems of the tungsten inert gas (TIG) welding process have been solved using radial basis function neural networks (RBFNNs), which is required to automate the welding process. The performance of an RBFNN depends on its structure and parameters. Here, a few approaches are proposed to optimize its structure and parameters simultaneously. A binary-coded genetic algorithm (GA) has been used for the said purpose. The GA strings carrying information of the networks might have varied lengths, and consequently, it becomes difficult to implement the conventional crossover operator. To overcome this difficulty, a new scheme has been adopted here. The performances of the developed approaches are tested to conduct both forward and reverse mappings of a TIG welding process. Cluster-based approaches are found to perform better than the non-cluster-based ones.

During the course of development of Mechanical Engineering, a large number of mechanisms (that is, linkages to perform various types of tasks) have been conceived and developed. Quite a few atlases and catalogues were prepared by the designers of machines and mechanical systems. However, often it is felt that a clustering technique for handling the list of large number of mechanisms can be very useful, if it is developed based on a scientific principle. In this paper, it has been shown that the concept of fuzzy sets can be conveniently used for this purpose, if an adequate number of properly chosen attributes (also called characteristics) are identified. Using two clustering techniques, the mechanisms have been classified in the present work and in future, it may be extended to develop an expert system, which can automate type synthesis phase of mechanical design. To the best of the authors' knowledge, this type of clustering of mechanisms has not been attempted before. Thus, this is the first attempt to cluster the mechanisms based on some quantitative measures. It may help the engineers to carry out type synthesis of the mechanisms.

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