Metallurgical and Geometric Properties Controlling of Additively Manufactured Products using Artificial Intelligence

Abstract

This article has presented a technical concept for producing precisely desired Additive Manufactured (AM) metallic products using Artificial Intelligence (AI). Due to the stochastic nature of the metallic AM process, which causes a greater variance in product properties compared to traditional manufacturing processes, significant inaccuracies in metallurgical properties, as well as geometry, occur. The physics behind these phenomena are related to the melting process, bonding, cooling rate, shrinkage, support condition, part orientation. However, by controlling these phenomena, a wide range of product features can be achieved using the fabricating parameters. A variety of fabricating parameters are involved in the metal AM process, but an appropriate combination of these parameters for a given material is required to obtain an accurate and desired product. Zero defect product can be achieved by controlling these parameters by implementing Knowledge-Based System (KBS). A suitable combination of manufacturing parameters can be determined using mathematical tools with AI, considering the manufacturing time and cost. The knowledge required to integrate AM manufacturing characteristics and constraints into the design and fabricating process is beyond the capabilities of any single engineer. Concurrent Engineering enables the integration of design and manufacturing to enable trades based not only on product performance, but also on other criteria that are not easily evaluated, such as production capability and support. A decision support system or KBS that can guide manufacturing issues during the preliminary design process would be an invaluable tool for system designers. The main objective of this paper is to clearly describe the metal AM manufacturing process problem and show how to develop a KBS for manufacturing process determination.