The concept of 'digital twins' has gained significant traction in industrial engineering, referring to virtual replicas of physical systems that are continuously updated with real-time data. These dynamic models enable predictive maintenance by simulating potential failures before they occur, thereby reducing downtime and operational costs. However, the efficacy of digital twins hinges on the quality and granularity of the data ingested; incomplete or biased datasets can lead to inaccurate simulations, undermining their reliability. Moreover, the integration of digital twins into legacy infrastructure poses substantial technical challenges, requiring robust cybersecurity measures to prevent data breaches. Recent studies suggest that while digital twins offer transformative potential for optimizing complex processes, their successful implementation demands a holistic approach that addresses data governance, system interoperability, and human expertise. Without such considerations, the technology risks becoming an expensive but underutilized asset.
❓ 지문에 따르면, 디지털 트윈의 효과성을 결정하는 핵심 요소는 무엇인가?
A. A) 데이터 전송 속도
B. B) 사용된 데이터의 품질과 세분화 수준
C. C) 복제되는 물리적 시스템의 연령
D. D) 시스템에 설치된 센서의 수
✅ 正确答案
B) The quality and granularity of the data used
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