Authors may use MDPI'sĮnglish editing service prior to publication or during author revisions. Submitted papers should be well formatted and use good English. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Please visit the Instructions for Authors page before submitting a manuscript. Machines is an international peer-reviewed open access monthly journal published by MDPI. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. All manuscripts are thoroughly refereed through a single-blind peer-review process. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Research articles, review articles as well as short communications are invited. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. All submissions that pass pre-check are peer-reviewed. Manuscripts can be submitted until the deadline. Once you are registered, click here to go to the submission form. Manuscripts should be submitted online at by registering and logging in to this website. Distributed DT system and its applications in smart manufacturing.DT-based dynamic adjustment and control service.DT and big data-driven preventive maintenance in smart manufacturing.New smart manufacturing scheduling using DT.Multi-layer decision and optimal control method of end-edge-cloud based on DT.Implementation, operation, and optimization of DT in smart manufacturing.Dynamic intelligent modeling with deep integration of mechanism model and data model in DT.High-performance intelligent perception and comprehensive cognition of manufacturing data for DT.Reference architecture of DT in smart manufacturing.This Special Issue will focus on (but not be limited to) the following topics: 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. Thus, it is expected that primary and emerging research topics about bringing 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. 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. Smart manufacturing is a typical complex system which is very suitable for observation and research using DT theory. 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. 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. 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. Digital twin (DT) has recently attracted much attention worldwide as a newly emerging and fast-growing technology.
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