Digital Fuzzy Welding Control in MIG/MAG Gas Metal Arc Welding

Welding is an important manufacturing process that can be automated. Its effect on the quality of products is particularly important when new materials are used in the manufacturing process. The permanent demand for higher quality of products at lower product prices dictates a permanent development of production quality assurance methods and systems. Super-control of welded products (destructive and non-destructive testing of welds) is time consuming and expensive, so new possibilities for automated welding process self-control are being investigated. One of the feasible possibilities in this domain is to design an intelligent controller of welding sources. The controller offer settings of parameters (welding energy, pulse shapes) with respect to the chosen material, weld characteristics and welding program. This is made possible by a decision system based on analysis of feedback information coming from the welding process and the knowledge database. Decision algorithm, supported by intelligent data analysis, neural network theory and fuzzy decision system is able to adjust automatically the welding parameters of automated welding cells in order to fulfil the desired technological requirements. The control and the regulation of the welding process is implemented depending on the conditions in the solidified weld which is in direct connection with the quality of the welded joint. The project will bring the results of interdisciplinary research work performed by experts in welding technology, measurement of electrical and physical quantities, intelligent data analysis, soft computing technologies, and microprocessor technologies.