Digital Twin–Integrated Project Management for Next-Generation Data Center Development

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International Journal of Computer Techniques
ISSN 2394-2231
Volume 12, Issue 5  |  Published: September – October 2025
Author
Manambedu Vijayakumar Raja

Abstract

The burgeoning growth in artificial intelligence, cloud computing, and big data analytics has propelled the urgency in creating next-generation data centers that are scalable, efficient, robust, and sustainable. Traditional project management techniques, though effective in tackling massive infrastructure projects, are often ineffectual in addressing the dynamic, data-intensive issues in new data center development. This paper presents the application of Digital Twin (DT) technology in project management practices in creating a new paradigm in advancing the planning, execution, and lifecycle operations in data center projects. Through the ingestion and use of real-time data, simulation, and predictive analytics, DTs present a powerful tool in the project manager’s kitbag in optimizing resource allocation, conducting risk mitigation, and realizing sustainability targets. The paper systematically reviews the published literature on DT implementation in neighboring domains in manufacturing, constructions, and smart energy systems, and observes a significant lag in their implementation in data center project management. The paper formulates a conceptual model linking DT functionality and project management phases, and provides a forceful argument on how it can advance decision-making, stakeholder reporting, and lifecycle performance. The findings underscore DTs as a transformational enabler of next-generation data centers, and indicate directions towards greater efficiency, expense reduction, and alignment in international sustainability targets. The paper concludes by underscoring challenges, namely integration complexity, organizational resistance, and lack of standardization, and provides recommendations on future research into empirical validation and standard-setting in DT-led project management.

Keywords

Digital Twin (DT), Project Management, Next-Generation Data Centers, Sustainability, Predictive Analytics.

Conclusion

The rapid development pace in cloud computing, worldwide digital services, and artificial intelligence fostered an unstoppable demand for next-generation data centers. Their development, however, is marred by rising complexity, staggering capital costs, and sustainability issues difficult for customary project management approaches to manage. This paper presented a conceptual DT-PM model combining real-time data, predictive analytics, and simulation with seasoned project management techniques. Through interweaving DTs along the lifecycle from initiation and planning through execution, monitoring, and closure, project teams can make informed decisions, handle risks in a better way, and achieve more sustainability outputs. The argument put forth a series of value benefits, from improved cost optimization, reduced delays, and improved stakeholder communication, through lifecycle value extension after construction. At the same time, technical integration, resistance by organization, investment in cost, and lack of standardization as challenges indicate cautious implementation.Finally, DT-PM is a revolutionary route towards the provision of data centers that are efficient, robust, and in harmony with worldwide carbon reduction targets. Further research is needed on empirical verification, standardization, and inter-industry knowledge transfer in order to realize the entire potential capability of Digital Twin technologies applied in project management.

References

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