Digital Twin (DT) technology has evolved to contextualize real-time interactions between the physical and digital worlds. It has gained increasing attention in various research areas and industries, including the manufacturing, aerospace, and automotive industries, while facing challenges in processing and analyzing large datasets. To address these challenges, this paper proposes an edge computing-based DT (E-DT) framework and elaborates on its functional and informational aspects. The functional aspect is represented using ISO 23247 as the reference architecture, while the informational aspect is elaborated by introducing a data fusion model. Then, an E-DT for Wire+Arc Additive Manufacturing (WAAM) is developed, its performance is evaluated, and the benefits of edge computing in enhancing real-time processing and decision-making are verified. In addition, a typical non-edge computing-based DT for WAAM is implemented according to ISO 23237 for comparison. The results show that the proposed E-DT for WAAM achieved reduction in latency through faster data processing, smaller data upload volume, and more consistent data upload speed.