Digital twin-driven additive manufacturing: advancements and future prospects

Abhilash P. M., Jibin Boban, Afzaal Ahmed, Xichun Luo

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

A digital twin (DT) is a virtual replica of a physical system with two-way data communication between the cyber and physical domains. It is an innovative concept in smart manufacturing, envisioning improved efficiency, productivity, flexibility and quality control through real-time data-driven and collaborative digital systems. DT systems are enabled through technologies such as artificial intelligence (AI), human-machine interface (HMI), simulation models, augmented reality and virtual reality, online sensing, big data analytics and the Internet of Things (IoT). Additive manufacturing (AM) is a fast-growing and revolutionary technology with immense applications in aerospace, biomedical, automobile and marine applications. Some of the fundamental challenges of AM processes are part irregularities, indispensable post-processing, unanticipated process anomalies, design and metrology disintegration and a lack of standardization. Currently, considerable time and cost are being devoted to offline metrology, defect identification and process optimization. DT-driven AM is still in its nascent stage; however, the technology has demonstrated its immense potential to transform the emerging world of AM. A DT system looks to systematically address these fundamental shortcomings through computational intelligence and real-time data communication. Key application domains include anomaly detection, online condition monitoring, feed-forward process control, intelligent post-processing and process optimization. The chapter critically analyses the current state-of-the-art of DTs in AM processes and further discusses their future prospects and research directions. The chapter highlights the capacity of a DT to broaden the acceptability of AM in various industrial applications by improving robustness and efficiency.
Original languageEnglish
Title of host publicationHybrid Metal Additive Manufacturing
Subtitle of host publicationTechnology and Applications
Place of PublicationMilton Park, Oxon.
Pages196-221
Number of pages26
ISBN (Electronic)9781003803249
DOIs
Publication statusPublished - 5 Dec 2023

Keywords

  • digital twin (DT)
  • artificial intelligence (AI)
  • additive manufacturing (AM)
  • smart manufacturing

Fingerprint

Dive into the research topics of 'Digital twin-driven additive manufacturing: advancements and future prospects'. Together they form a unique fingerprint.

Cite this