Opportunities for Industry 4.0/5.0: AI-Driven Data Analysis, Process Optimization and Automation

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

Deadline for manuscript submissions: 15 October 2025 | Viewed by 7371

Special Issue Editors


E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan
Interests: smart manufacturing; quality and reliability engineering; electronics packaging and PCB assembly; data mining

E-Mail Website
Guest Editor
Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan
Interests: smart manufacturing; optimization; modeling; linear programming; decision-making; fuzzy set theory; neutrosophic set theory; machine learning

Special Issue Information

Dear Colleagues,

The advent of Industry 4.0 and the emerging concepts of Industry 5.0 are revolutionizing the industrial landscape by integrating advanced technologies such as artificial intelligence (AI), big data analytics, and automation. Industry 4.0 focuses on the digitization and interconnectivity of manufacturing processes, enabling smart factories with enhanced operational efficiency and productivity. Meanwhile, Industry 5.0 aims to harmonize human–machine collaboration, emphasizing sustainable and personalized manufacturing. These advancements are transforming industries by optimizing production processes, reducing costs, and fostering innovation, thereby creating unprecedented opportunities for growth and development.

This Special Issue on “Opportunities for Industry 4.0/5.0: AI-Driven, Data Analysis, and Process Automation” seeks high-quality works focusing on the latest advancements and applications of AI, data analysis, and automation in the context of Industry 4.0 and 5.0. We invite researchers and practitioners to submit original research articles, reviews, and case studies that explore the theoretical foundations, methodologies, and practical implementations of these technologies. Topics include, but are not limited to, the following:

  • AI and machine learning for predictive maintenance and fault detection;
  • Big data analytics for process optimization and decision-making;
  • Cyber–physical systems and their role in smart manufacturing;
  • Internet of Things (IoT) applications in industrial automation;
  • Human–robot collaboration and co-working environments;
  • Advanced manufacturing technologies and smart factories;
  • Data-driven quality control and assurance in production;
  • Sustainable and energy-efficient industrial processes;
  • Decision-making models and optimization in industrial processes;
  • Fuzzy logic and its applications in Industry 4.0/5.0;
  • Case studies and practical implementations of Industry 4.0/5.0 technologies;
  • Challenges and future directions in AI-driven industry transformation.

This Special Issue will provide a comprehensive platform for disseminating cutting-edge research and practical insights into the transformative power of AI, data analysis, and automation in modern industrial practices.

Dr. Chien-Yi Huang
Dr. Amirhossein Nafei
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 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 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.

Keywords

  • Industry 4.0
  • Industry 5.0
  • artificial intelligence (AI)
  • data analysis
  • process automation
  • machine learning
  • predictive maintenance
  • cyber–physical systems
  • internet of things (IoT)
  • optimization
  • fuzzy logic
  • decision-making

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

27 pages, 1834 KiB  
Article
Multi-Objective Optimization in Industry 5.0: Human-Centric AI Integration for Sustainable and Intelligent Manufacturing
by Shu-Chuan Chen, Hsien-Ming Chen, Han-Kwang Chen and Chieh-Lan Li
Processes 2024, 12(12), 2723; https://doi.org/10.3390/pr12122723 - 2 Dec 2024
Cited by 1 | Viewed by 5326
Abstract
The shift from Industry 4.0 to Industry 5.0 represents a significant evolution toward sustainable, human-centric manufacturing. This paper explores how advanced multi-objective optimization techniques can integrate Artificial Intelligence (AI) with human insights to enhance both sustainability and customization in manufacturing. We investigate specific [...] Read more.
The shift from Industry 4.0 to Industry 5.0 represents a significant evolution toward sustainable, human-centric manufacturing. This paper explores how advanced multi-objective optimization techniques can integrate Artificial Intelligence (AI) with human insights to enhance both sustainability and customization in manufacturing. We investigate specific optimization methods, including genetic algorithms (GAs), Particle Swarm Optimization (PSO), and reinforcement learning (RL), which are tailored to balance efficiency, waste reduction, and carbon footprint. Our proposed framework enables human creativity to interact with AI-driven processes, embedding human input into a computational structure that adapts dynamically to operational goals. By linking optimization directly to environmental impacts, such as reducing waste, energy consumption, and carbon emissions, this study establishes a pathway toward environmentally sustainable production. This research fills existing gaps by offering a detailed, practical model that harmonizes theoretical insights with applications in personalized manufacturing environments. In this regard, it contributes to the ongoing development of Industry 5.0, emphasizing how AI and human collaboration can foster intelligent, adaptable, and sustainable manufacturing systems. Full article
Show Figures

Figure 1

14 pages, 5492 KiB  
Article
Design and Research of Intelligent Washing and Disinfection Integrated System for Pigsties
by Xi Wang and Yongyi Gu
Processes 2024, 12(12), 2705; https://doi.org/10.3390/pr12122705 - 30 Nov 2024
Viewed by 1220
Abstract
With the rapid expansion of the market and the increase in pig farming density, improving the automation and intelligence of pig farms has become key. Despite continuous progress in this field, there is still a lack of intelligent systems for cleaning and disinfecting [...] Read more.
With the rapid expansion of the market and the increase in pig farming density, improving the automation and intelligence of pig farms has become key. Despite continuous progress in this field, there is still a lack of intelligent systems for cleaning and disinfecting pigs. In this paper, we conduct research from the perspective of product functional requirements. By conducting research to obtain raw data on user needs, the Analytic Hierarchy Process (AHP) is used to conduct a hierarchical analysis of user needs. The demand indicator system for the intelligent washing and disinfection integrated system of pig farms is summarized at three levels: goals, criteria, and indicators. Combined with competitor analysis and literature research methods, we obtained the operative words for the design requirements. Using Quality Function Deployment (QFD) to convert user requirements into performance indicators of product design, a quality house model for the product is constructed. We next analyzed the requirements of the intelligent washing and disinfection integrated system for pig farms in terms of functionality, usage, safety, and appearance, and this completed the conceptual design. Finally, we improved the mechanical structure of the mobile nozzle, supplemented the automation control system relied upon for nozzle movement, and enhanced the scientific and rational design. This study provides new ideas for the research and development of intelligent equipment in pig farms, promoting the development of intelligent and precision farming. Full article
Show Figures

Figure 1

Back to TopTop