Student Name

Rabbiya TariqFollow

Degree

Master of Science in Computer Science

Department

Department of Computer Science

School

School of Mathematics and Computer Science (SMCS)

Date of Submission

Spring 2025

Supervisor

Dr. Imran Khan, Assistant Professor, Department of Computer Science

Committee Member 1

Dr. Abdul Basit Shaikh, Assistant Professor, Department of Management

Committee Member 2

Dr. Syed Ali Raza, Assistant Professor, Department of Computer Science

Keywords

Digital Twin Framework, Lifecycle, Integration, Governance, Optimization, Scalability, Interoperability, Real-Time Synchronization

Abstract

This research introduces a new framework for developing and integrating digital twins across diverse industries and domains. Existing frameworks suffer from several limitations, including lack of standardization, limited interoperability, insufficient scalability, and inadequate governance mechanisms. These challenges significantly hinder the widespread adoption and effective implementation of digital twin technology across different sectors. The proposed Digital Twin Lifecycle Integration and Optimization (DTLIO) framework addresses these limitations through four key components: (1) a Digital Twin Definition Language (DTD) for standardized modeling, (2) a Digital Twin Integration Platform (DTIP) for seamless interoperability, (3) a Digital Twin Optimization Engine (DTOE) for performance enhancement, and (4) a Digital Twin Governance Framework (DTGF) for ensuring data quality and security. This comprehensive approach enables organizations to manage the entire lifecycle of digital twins in a standardized and tested manner. This thesis contributes to the field by providing a unified, scalable, and secure approach to digital twin lifecycle management. It addresses the critical gaps in existing frameworks while establishing a foundation for future research and development in this rapidly evolving domain.

Document Type

Restricted Access

Submission Type

Thesis

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