Advanced Manufacturing Systems and Technologies in Industry 4.0

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: closed (15 July 2024) | Viewed by 2110

Special Issue Editor


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Guest Editor
School of Mechano-Electronic Engineering, Xidian University, Xi’an 710071, China
Interests: additive manufacturing of conformal electronics; intelligent manufacturing technologies and systems
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Special Issue Information

Dear Colleagues,

In the last decade, the world has witnessed a remarkable shift towards digitalization and the rapid development of Industry 4.0. This paradigm shift has brought about significant advancements in advanced manufacturing systems and technologies. Augmented reality (AR), virtual reality (VR), the Internet of Things (IoT), and digital twin paradigms have expanded our view of the world, allowing us to interact with the physical world through digital simulations and enhancements. These advancements have led to the creation of new environments that simplify operations, enhance productivity, and improve the reliability of manufacturing systems. The integration of these technologies has paved the way for advanced manufacturing systems, enabling greater efficiency, precision, and safety in production processes.

This Special Issue will focus on the novel methodologies, tools, and techniques that can facilitate the successful transition to advanced manufacturing systems and technologies in Industry 4.0 and provide a platform for researchers to share their innovative ideas and findings.

This Special Issue will present the latest developments, challenges, and opportunities in advanced manufacturing systems and technologies in Industry 4.0 and provide a platform for researchers to share their innovative ideas and findings. For this Special Issue, original research articles and reviews are welcome. Potential research topics include (but are not limited to) the following:

  • The integration of cyber–physical systems and intelligent manufacturing;
  • The Internet of Things for smart factories;
  • Digital twin and virtual reality in manufacturing;
  • Cloud computing for real-time data analysis;
  • Cognitive computing in manufacturing optimization;
  • Human–machine interaction and collaborative robotics;
  • Data analytics and optimization in smart factories;
  • Additive manufacturing of flexible and conformal electronics.

Prof. Dr. Jin Huang
Guest Editor

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Keywords

  • Industry 4.0
  • smart manufacturing
  • manufacturing system
  • digital technologies
  • real-time data analysis
  • IoT

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Published Papers (1 paper)

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Research

19 pages, 8960 KiB  
Article
An Intelligent Manufacturing Management System for Enhancing Production in Small-Scale Industries
by Yuexia Wang, Zexiong Cai, Tonghui Huang, Jiajia Shi, Feifan Lu and Zhihuo Xu
Electronics 2024, 13(13), 2633; https://doi.org/10.3390/electronics13132633 - 4 Jul 2024
Cited by 1 | Viewed by 1688
Abstract
Industry 4.0 integrates the intelligent networking of machines and processes through advanced information and communication technologies (ICTs). Despite advancements, small mechanical manufacturing enterprises face significant challenges transitioning to ICT-supported Industry 4.0 models due to a lack of technical expertise and infrastructure. These enterprises [...] Read more.
Industry 4.0 integrates the intelligent networking of machines and processes through advanced information and communication technologies (ICTs). Despite advancements, small mechanical manufacturing enterprises face significant challenges transitioning to ICT-supported Industry 4.0 models due to a lack of technical expertise and infrastructure. These enterprises commonly encounter variable production volumes, differing priorities in customer orders, and diverse production capacities across low-, medium-, and high-level outputs. Frequent issues with machine health, glitches, and major breakdowns further complicate optimizing production scheduling. This paper presents a novel production management approach that harnesses bio-inspired methods alongside Internet of Things (IoT) technology to address these challenges. This comprehensive approach integrates the real-time monitoring and intelligent production order distribution, leveraging advanced LoRa wireless communication technology. The system ensures efficient and concurrent data acquisition from multiple sensors, facilitating accurate and prompt capture, transmission, and storage of machine status data. The experimental results demonstrate significant improvements in data collection time and system responsiveness, enabling the timely detection and resolution of machine failures. Additionally, an enhanced genetic algorithm dynamically allocates tasks based on machine status, effectively reducing production completion time and machine idle time. Case studies in a screw manufacturing facility validate the practical applicability and effectiveness of the proposed system. The seamless integration of the scheduling algorithm with the real-time monitoring subsystem ensures a coordinated and efficient production process, ultimately enhancing productivity and resource utilization. The proposed system’s robustness and efficiency highlight its potential to revolutionize production management in small-scale manufacturing settings. Full article
(This article belongs to the Special Issue Advanced Manufacturing Systems and Technologies in Industry 4.0)
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