Additive manufacturing expert system (AMES): A case study for effective automotive plastic parts manufacturing

Abstract

Additive manufacturing (AM), commonly referred to as 3D printing, has emerged as a transformative technology in automotive production, enabling the fabrication of complex, lightweight, and customized components. The effective execution of additive manufacturing for plastic components in the automotive industry requires specialized knowledge to optimize material selection, process parameters, and design considerations. The goal of this research is to develop and implement the Additive Manufacturing Expert System (AMES), an intelligent decision-support tool that aims to improve the efficiency and quality of automotive plastic parts production. This study performs a comprehensive review of current literature to evaluate advancements in additive manufacturing technology, focusing on their application to automotive plastic components. Fundamental domains include material properties, process optimization, and integration with automobile manufacturing processes. The AMES framework uses artificial intelligence (AI) methodologies, i.e., expert systems, to assist users in selecting the most suitable materials, procedures and designs for specific automotive applications. The report also provides a case study illustrating the implementation of AMES in the optimized fabrication of plastic parts. The results show a substantial reduction in production duration and material waste, accompanied by improved component performance. Results demonstrate a substantial decrease in production duration and material waste, accompanied by enhancements in component performance. This study emphasizes the capability of expert systems to address the knowledge deficit in additive manufacturing, offering car manufacturers an effective and scalable alternative for the production of plastic components. The results emphasize the necessity of incorporating AI-driven technologies into additive manufacturing processes to promote innovation, decrease expenses, and improve sustainability in the automobile industry.