Integrating the digital twin concept into the evaluation of reconfigurable manufacturing systems (RMS): literature review and research trend

16Citations
Citations of this article
90Readers
Mendeley users who have this article in their library.

Abstract

With the rapid advent of new information technologies (Big Data analytics, cyber-physical systems, such as IoT, cloud computing and artificial intelligence), digital twins are being used more and more in smart manufacturing. Despite the fact that their use in industry has attracted the attention of many practitioners and researchers, there is still a need for an integrated and comprehensive digital twin framework for reconfigurable manufacturing systems. To close this research gap, we present evidence from a systematic literature review, including 76 papers from high-quality journals. This paper presents the current research trends on evaluation and the digital twin in reconfigurable manufacturing systems, highlighting application areas and key methodologies and tools. The originality of this paper lies in its proposal of interesting avenues for future research on the integration of the digital twin in the evaluation of RMS. The benefits of digital twins are multiple such as evaluation of current and future capabilities of an RMS during its life cycle, early discovery of system performance deficiencies and production optimization. The idea is to implement a digital twin that links the virtual and physical environments. Finally, important issues and emerging trends in the literature are highlighted to encourage researchers and practitioners to develop studies in this area that are strongly related to the Industry 4.0 environment.

Cite

CITATION STYLE

APA

Touckia, J. K. (2023, May 1). Integrating the digital twin concept into the evaluation of reconfigurable manufacturing systems (RMS): literature review and research trend. International Journal of Advanced Manufacturing Technology. Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/s00170-023-10902-7

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free