Digital Twin Applications in Smart Manufacturing

Dear Colleagues,

Digital twin (DT) has recently attracted much attention worldwide as a newly emerging and fast-growing technology. The product is the core of smart manufacturing, and the improvement of product processing, manufacturing mode and product quality are related to the success of the transformation and upgrading of the whole manufacturing industry. In traditional smart manufacturing, the integration and management of physical space data and information space data in the manufacturing process are lacking, the data are fragmented and, thus, closed-loop feedback cannot be achieved, and it is impossible to establish an accurate intelligent control system model. How to apply DT theory and technology to better serve the smart manufacturing of products has become a key issue that needs to be urgently solved.

Smart manufacturing is a typical complex system which is very suitable for observation and research using DT theory. DT covers the whole life cycle and value chain of products, and establishes digital archives from raw materials, design, process, manufacturing, use and maintenance, which lays a data foundation for the whole process of quality traceability and continuous improvement of product research and development. Meanwhile, the deep combination of emerging technologies (such as artificial intelligence, big data, Internet of Things, etc.) and DT further promotes the real-time interaction and integration of information space and physical space, playing an increasingly important role in product manufacturing, and has become the cornerstone of smart manufacturing. Thus, it is expected that primary and emerging research topics about bringing

More specifically, this Special Issue “Digital Twin Applications in Smart Manufacturing” will cover intelligent perception and information fusion, intelligent modeling and analysis, intelligent collaborative optimization control, intelligent analysis and optimization decision-making, and precise execution and service for DT in smart manufacturing. This Special Issue will focus on (but not be limited to) the following topics:

• Reference architecture of DT in smart manufacturing
• High-performance intelligent perception and comprehensive cognition of manufacturing data for DT
• Dynamic intelligent modeling with deep integration of mechanism model and data model in DT
• Implementation, operation, and optimization of DT in smart manufacturing
• Multi-layer decision and optimal control method of end-edge-cloud based on DT
• New smart manufacturing scheduling using DT
• DT and big data-driven preventive maintenance in smart manufacturing
• DT-based dynamic adjustment and control service
• Distributed DT system and its applications in smart manufacturing

Prof. Dr. Jiafu Wan
Dr. Yuqian Lu
Prof. Dr. Sang Do Noh
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.