Digital Twin-Driven Engineering Management Systems an Integrated Approach for Predictive Decision-Making and Lifecycle Optimization in Smart Manufacturing

Abstract

With the rapid development of Industry 4.0 technologies, traditional manufacturing paradigms have been profoundly reshaped. The field of intelligent manufacturing urgently requires a data-driven engineering management framework. This paper originally proposes the digital twin-driven DT-EMS system, which builds a two-way data pipeline connecting physical assets and their virtual replicas. It supports predictive decision-making and full-lifecycle optimization, and is equipped with functions including reducing production and operation costs while boosting efficiency, as well as full-link resource allocation and quality control. Verified via a simulation case, the system delivers significant improvements over traditional management methods across three core metrics: response speed, decision accuracy, and manufacturing flexibility. The strategic embedding of digital twin technology can serve as a core engine for the future ecological transformation of intelligent manufacturing.