Abstract
Digital twin (DT) and additive manufacturing (AM), also known as 3D printers, are most important practices in industry 4.0. 3D printers are the best candidate for manufacturing geometrically challenging products due to the increase in customized product. However, there are limitations and issues regarding product quality and process optimizations. Owing to a digital twin technology's ability to provide maximum benefits to the manufacturing field, especially additive manufacturing, it is considered one of the suitable technologies to integrate with. In recent years, digital twin gets more attention from both academia and industry. However, there are implementation challenges of digital twin technology. Thus, identifying and understanding these challenges are significant. Many challenges are mapped out from research papers and work in academia in this paper through narrative literature review. Identified challenges have been classified into eight key categories to formulate the future research direction. It is important to investigate the identified challenges and provide possible solutions to elevate the functionality of the digital twin model and improve additive manufacturing productivity and efficiency, ultimately achieve smart manufacturing.