RESUMEN
We are pleased to present this Special Issue of TASE, including 12 extended articles selected from the technical program of the 2020 International Conference on Automation Science and Engineering (CASE2020). CASE2020 was held virtually due to the COVID19 pandemics, August 20–21, 2020, and was originally scheduled in Hong Kong, China. CASE is an offspring of TASE and is the flagship automation conference of the IEEE Robotics and Automation Society, constituting the primary forum for cross-industry and multidisciplinary research in automation. The 2020 CASE theme was Automation Analytics, a global challenge emphasized at the conference by several invited and regular sessions, as well as specific workshops. [ FROM AUTHOR] Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
RESUMEN
The COVID-19 has become a global pandemic that dramatically impacted human lives and economic activities. Due to the high risk of getting affected in high-density population areas and the implementation of national emergency measures under the COVID-19 pandemic, both travel and transportation among cities become difficult for engineers and equipment. Consequently, the costly physical commissioning of a new manufacturing system is greatly hindered. As an emerging technology, digital twins can achieve semi-physical simulation to avoid the vast cost of physical commissioning of the manufacturing system. Therefore, this paper proposes a digital twins-based remote semi-physical commissioning (DT-RSPC) approach for open architecture flow-type smart manufacturing systems. A digital twin system is developed to enable the remote semi-physical commissioning. The proposed approach is validated through a case study of digital twins-based remote semi-physical commissioning of a smartphone assembly line. The results showed that combining the open architecture design paradigm with the proposed digital twins-based approach makes the commissioning of a new flow-type smart manufacturing system more sustainable.