Data Collection and Management for Digital Twins

Several technologies have been recently introduced to enhance the availability of real-time data streams from industrial processes and services, coupled with significant advancements in computing capabilities. The increased visibility of system conditions in real-time has stimulated the development of methods to optimize the system performance in the short term. Central to these advancements is the tight integration of digital models with physical production systems, making the study and development of digital twin (DT) architectures critical. This chapter presents a state-of-the-art review of DT evolution focusing on data collection and the elaboration of data into digital models. Additionally, this chapter addresses the research gaps and implementation challenges that must be overcome to achieve widespread adoption of DTs in the industry.