Open Access
Computers and Industrial Engineering, 2024

Towards sustainable cognitive digital twins: A portfolio management tool for waste mitigation

Antonio Padovano a, Chiara Sammarco a, Nasia Balakera b, Fotios Konstantinidis b
a Department of Mechanical, Energy and Management Engineering, University of Calabria, Ponte Pietro Bucci 45C, 87036 Rende, Italy
bInstitute of Communication and Computer Systems, National Technical University of Athens, 9 Iroon. Polytechniou Str., Zografou Athens GR-157 73, Greece
Abstract
The rapid integration of Cognitive Digital Twins (CDTs) across various industries has revolutionized operational practices, leading to enhanced efficiency and improved decision-making capabilities. However, this technological advancement is accompanied by significant environmental implications, particularly regarding the management of electronic waste (e-waste) and digital waste. While e-waste primarily concerns the disposal of obsolete hardware, digital waste encompasses inefficiencies, redundancies, and unnecessary consumption of computational resources in the digital environment. This paper emphasizes the importance of understanding the lifecycle impacts of CDTs and advocates for the implementation of sustainable practices in their management. To address these challenges, we introduce Digital Twin Portfolio Management (DTPM) as a systematic framework for optimizing the CDT ecosystem. We also present the Digital Twin Triple Bottom Line as a framework for assessing the technical, economic, and environmental impacts of CDT implementations, ensuring that organizations can identify inefficiencies and align their operations with broader sustainability objectives. The findings elucidate the various types of waste generated by CDTs, establishing a critical link between digital asset management and environmental sustainability. Additionally, the study advocates for improved APM practices tailored to the unique challenges posed by CDTs, contributing valuable insights to the evolving discourse on IT portfolio management. Future research directions are also discussed, including the need for expanded case studies and longitudinal investigations to enhance the generalizability and understanding of CDT lifecycle management.
How to cite: Padovano, A., Sammarco, C., Balakera, N., Konstantinidis, F., Towards sustainable cognitive digital twins: A portfolio management tool for waste mitigation, Computers & Industrial Engineering (2024), doi: https://doi.org/10.1016/j.cie.2024.110715

LEONARDO is funded by the European Commission under the Erasmus+ programme KA-220 Cooperation Partnerships for Higher Education – No. 2023-1-IT02-KA220-HED-000164699

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