Optimizing Materials for 3D Printing through Artificial Intelligence

Abstract

In recent years, additive manufacturing has become a cutting-edge manufacturing technology, enabling the creation of products that were once considered unachievable using traditional manufacturing methods.Many materials are available for additive manufacturing; however, most people find it difficult to compromise on performance. The current design of these materials relies on inefficient methods based on human intuition and do not provide optimal solutions.The emergence of new materials promises colossal advances in technology and applications. However, the traditional method, which often relies on trial and error, is unable to meet the current need for innovative materials. An emerging and increasingly popular concept is the use of artificial intelligence to explore new materials.As artificial intelligence (AI) continues to develop, materials science can contribute to and benefit from these advances. In the simultaneous race for innovation, new materials, systems and processes can be designed and optimized using machine learning (ML) techniques. These improvements, in turn, have the potential to transform into groundbreaking computing platforms. It will be useful for tomorrow's materials scientists to understand how machine learning can help develop advanced materials.We propose an innovative method that uses machine learning to accelerate the search for materials for additive manufacturing and achieve the optimal balance in terms of mechanical performance.