The Optimal Parameters Design of Multiple Quality Characteristics for the Welding Thick Plate of Aerospace Aluminum Alloy

Abstract

The welding of different metal materials such as aerospace aluminum alloy has superior mechanical characteristics, but the feasible setting for the welding parameters of the TIG has many difficulties due to some hard and crisp inter-metallic compounds created within the weld line. Normally, the setting for welding parameters does not have a formula to follow; it usually depends on experts’ past knowledge and experiences. Once exceeding the rule of thumb, it becomes impossible to set up feasibly the optimal parameters, and the past researches focus on thin plate. This research proposes an economic and effective experimental design method of multiple characteristics to deal with the parameter design problem with many continuous parameters and levels for aerospace aluminum alloy thick plate. It uses TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Artificial Neural Network (ANN) to train the optimal function framework of parameter design for the thick plate weldment of aerospace aluminum alloy. To improve previous experimental methods for multiple characteristics, this research method employs ANN and all combinations to search the optimal parameter such that the potential parameter can be evaluated more completely and objectively. Additionally, the model can learn the relationship between the welding parameters and the quality responses of different aluminum alloy materials to facilitate the future applications in the decision-making of parameter settings for automatic welding equipment. The research results can be presented to the industries as a reference, and improve the product quality and welding efficiency to relevant welding industries.