Special Journal Issue to Highlight the Digital Twin in Design and Manufacturing

The ASME Journal of Computing and Information Science in Engineering is now accepting manuscripts for a special issue focusing on digital twin driven design and manufacturing. Authors who are interested in having their papers included in the special issue, to be published in June 2021, should submit their manuscripts by Aug. 31, 2020.

Digital twins are real-time digital replicas of a physical entity and system that enable seamless integration between digital models and physical devices, ensuring that the operation, monitoring, control, and upgrade of the system — as well as personnel training — can be performed in a cyber-physical mixture mode. Integrating such technologies as multiphysics multiscale modeling, the Internet of Things, smart sensing, machine learning and model-based control, the digital twin (DT) connects the physical world and the virtual world by plotting the entire life cycle of physical systems with real-time sensor data, while maintaining a complete digital trace.

In the era of Industry 4.0, the digital twin is becoming an important instrument in the intelligent design of products and intelligent manufacturing, permitting data-driven design and optimization, evidence-based sustainable design, real-time diagnostics and prognostics, plug-and-play customization, and modular improvement.

The upcoming special issue of the ASME Journal of Computing and Information Science in Engineering is intended to provide researchers with a collection of the latest efforts in fundamental methodologies as well as their applications in digital twin-driven design and manufacturing.

Potential topics to be covered in the issue include fundamental advances in DT technologies, such as multiphysics multiscale simulations for design and manufacturing, cyber-physical systems design, data-driven design and optimization, smart and efficient sensing mechanisms, and physics-based data-driven predictive control; and DT-enabled data-driven product sustainable design, including design for product carbon footprint and product environmental footprint, evidence-based product and process design for cleaner production and circular economy, and sustainable impact assessment for product life cycle.

The issue will also address DT-enabled intelligent design and smart manufacturing, including: DT in human-machine interaction; DT in supply chain and logistics; DT for product life cycle with Industrial Internet, Internet of Things, and cloud computing; DT for optimization of products, systems, and services; fault diagnosis, predictive maintenance, and performance analysis with data analytics and machine learning; digital human modelling in product design, assembly, and manufacturing; ultra-personalized product design and manufacturing; and advanced robotics and sustainable intelligent manufacturing system.

Papers should be submitted to the ASME Journal of Computing and Information Science in Engineering by Aug. 31, 2020, through ASME Journals Connect. Authors who already have an account should log in and select “Submit Paper” at the bottom of the page. Authors who do not yet have an account should select “Submissions” and follow the instructions. When they reach the “Paper Submittal” page, authors should then choose “ASME Journal of Computing and Information Science in Engineering” and then select “Digital Twin Driven Design and Manufacturing” from the special issue menu.

Manuscripts received after the deadline or papers not selected for inclusion in the special issue may be accepted for publication in a regular issue of the journal. Early submission is highly encouraged. Authors are also asked to email the editor, Prof. Satyandra K. Gupta, at guptask@usc.edu, to alert him that their papers are intended for the special issue.

The guest editors for the special issue are Prof. Bin He, Shanghai University, email mehebin@shu.edu.cn; Dr. Yu Song, Delft University of Technology, email Y.Song@tudelft.nl; and Prof. Yan Wang, Georgia Institute of Technology, email yan.wang@me.gatech.edu.

For more information on the ASME Journal of Computing and Information Science in Engineering, visit https://asmedigitalcollection.asme.org/computingengineering. To learn more about the ASME Journal Program, visit www.asme.org/publications-submissions/journals/information-for-authors.