Special Issue "Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Automation Control Systems".

Deadline for manuscript submissions: 15 June 2023 | Viewed by 330

Special Issue Editor

Dr. Sergey Y. Yurish
E-Mail Website
Guest Editor
International Frequency Sensor Association, Steve Tarradas 1, Castelldefels, 08860 Barcelona, Spain
Interests: photonic sensors; photodetectors; photonic integrated circuits
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Industry 4.0 has much potential and is expected to grow substantially in the near future. According to a modern market study, the global Industry 4.0 market size is projected to reach USD 377.30 billion by 2029 at a CAGR of 16.3 % during the forecast period 2022–2029.

Industry 4.0/5.0 is an integrated system consisting of automation tools, robotic control, communications and big data analytics. The increased adoption of industrial robots is one of the main driving factors of this market, while the main restraining factors include data risks associated with the integration of advanced technologies.

This Special Issue contains extended papers selected from the 3rd IFSA Winter Conference on Automation, Robotics & Communications for Industry 4.0/5.0 (ARCI 2023), 22–24 February 2023, Chamonix-Mont-Blanc, France.

Topics include (but are not limited to):

  • Process Automation;
  • Process control and monitoring;
  • Design principles in Industry 4.0/5.0;
  • Smart manufacturing and technologies;
  • Smart factories;
  • Machine learning and artificial intelligence in manufacturing;
  • Chemical process control;
  • Industrial big data and analytics;
  • Digital production and virtual engineering.

Dr. Sergey Y. Yurish
Guest Editor

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Processes 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 2000 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.

Published Papers (1 paper)

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Research

Article
Research on Assembly Sequence Optimization Classification Method of Remanufacturing Parts Based on Different Precision Levels
Processes 2023, 11(2), 383; https://doi.org/10.3390/pr11020383 - 26 Jan 2023
Viewed by 194
Abstract
Aiming at resolving the problem of low assembly accuracy and the difficulty of guaranteeing assembly quality of remanufactured parts, an optimization classification method for the assembly sequence of remanufactured parts based on different accuracy levels is proposed. By studying the characteristics of recycled [...] Read more.
Aiming at resolving the problem of low assembly accuracy and the difficulty of guaranteeing assembly quality of remanufactured parts, an optimization classification method for the assembly sequence of remanufactured parts based on different accuracy levels is proposed. By studying the characteristics of recycled parts, based on the requirement that the quality of remanufactured products not be lower than that of the assembly quality of new products, the classification selection matching constraints of remanufactured parts are determined, and the classification selection matching optimization models of remanufactured parts with different precision levels is established. An algorithm combining particle swarm optimization and a genetic algorithm is proposed to solve the model and obtain the optimal assembly sequence. Taking the remanufacturing assembling of a 1.4 TGDI engine crank and a connecting rod mechanism as an example, the comparison of quality data shows that this method can effectively improve the qualified rate of assembly, reduce the cost of after-sale claims, provide new theories and methods for remanufacturing enterprises that need hierarchical assembly, and provide effective guidance for the development of the remanufacturing industry. Full article
(This article belongs to the Special Issue Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0)
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