Data-Driven Digital Twin Requirements for Additive Layer Manufacturing

Abstract

Digital twin and additive layer manufacturing plays a vital role of the fourth industrial revolution. Digital twin is the ideal solution for data-driven optimisation of additive manufacturing challenges. It is helpful in understating, analysing, and improving 3D printing machining process variables and consequently reducing the number of trial-and-error and component’s non-conformance and shorten product development lead time. Furthermore, the development of genuine digital twin still requires more research efforts to develop a thorough understanding of its concept, data management framework, and development techniques. Therefore, this paper aims to capture important data-driven digital twin requirements for additive layer manufacturing through a systematic approach by identifying the requirements, analysing technologies and processes for digital twin development. The main novelty of this research is applying a holistic approach to build digital twin of additive manufacturing process by capturing the requirements from both literature review and world-class aerospace industrial experts. Overall, the captured requirements will not only serve industries as a basis for implementing digital twin for additive manufacturing and modernize existing data management systems but also opens new research areas in the digital twin domain.