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Artificial Intelligence in Sustainable Industry
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Artificial Intelligence in Sustainable Industry

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (31 January 2025) | Viewed by 6750

Special Issue Editors

Prof. Dr. Jinhai Liu

E-Mail Website
Guest Editor
College of Information Science and Engineering, Northeastern University, Shenyang, China
Interests: industrial intelligence; intelligent robots; electrical system monitoring and control; data-driven fault diagnosis theory and technology
Dr. Fuming Qu

E-Mail Website
Guest Editor
School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing, China
Interests: systems optimization; systems engineering; artificial intelligence in industry; unmanned production

Special Issue Information

Dear Colleagues,

With the development and promotion of the global Sustainable Development Goals (SDGs), there is a growing need for industry to adopt sustainable production methods. Artificial Intelligence (AI), as a key technological innovation, provides new opportunities and solutions for achieving sustainable industry. With the rapid development of AI technology, industrial production and manufacturing, process monitoring, quality control, and other fields can be automated by AI technology, thus improving efficiency, reducing costs, and promoting industrial upgrading and transformation. Through the in-depth study of the latest developments in AI technology in sustainable industry, not only can production efficiency and quality be improved, but the transformation of industry with intelligence and digitalization and the innovation and upgrading of industrial production methods can also be achieved. Therefore, an in-depth discussion on the applications of AI in industry is of great theoretical and practical significance and contributes positively to the promotion of sustainable industrial development.

This Special Issue aims to explore the applications of AI in sustainable industry; publish the latest reviews, research articles, and technical notes on AI in sustainable industry within a broader theme; and promote the integration of sustainable industry and AI technologies. The papers selected for this Special Issue will undergo a rigorous peer review process with the aim of quickly and widely disseminating research findings, developments, and applications.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following topics:

  • Automation and intelligent applications of artificial intelligence in manufacturing industry.
  • Application of artificial intelligence in industrial fault diagnosis.
  • Quality control and predictive maintenance.
  • Renewable energy prediction and optimization.
  • Artificial intelligence for energy management and energy saving optimization in industrial production processes.
  • Robotic automation and collaborative robots.
  • Application of artificial intelligence technology in supply chain management.
  • Grid optimization and stability.
  • Other related research areas.

We look forward to receiving your contributions.

Prof. Dr. Jinhai Liu
Dr. Fuming Qu
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. Sustainability is an international peer-reviewed open access semimonthly 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

  • artificial intelligence (AI)
  • sustainable industry
  • process monitoring
  • fault diagnosis
  • preventive maintenance

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

Published Papers (2 papers)

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Research

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25 pages, 1011 KiB  
Article
Artificial Intelligence Adoption in Sustainable Banking Services: The Critical Role of Technological Literacy
by Hengjun Mei, Simona-Aurelia Bodog and Daniel Badulescu
Sustainability 2024, 16(20), 8934; https://doi.org/10.3390/su16208934 - 15 Oct 2024
Cited by 4 | Viewed by 5137
Abstract
This study explores how customers recognize and accept artificial intelligence devices (AIDs) in the realm of sustainable banking services, applying the Artificially Intelligent Device Use Acceptance (AIDUA) model. This research not only seeks to corroborate the AIDUA model in the banking sector, but [...] Read more.
This study explores how customers recognize and accept artificial intelligence devices (AIDs) in the realm of sustainable banking services, applying the Artificially Intelligent Device Use Acceptance (AIDUA) model. This research not only seeks to corroborate the AIDUA model in the banking sector, but also aims to enrich it by introducing technological literacy as a moderating factor, particularly in the perspective of sustainable banking. Data were collected through 435 valid, self-administered face-to-face surveys from bank customers in China, determined through convenience sampling. The hypotheses, covering both direct and moderating effects, were examined using structural equation modeling. This study verifies the applicability and reliability of the AIDUA model, in assessing customer acceptance of AIDs within sustainable banking services. The findings indicate that customer acceptance of AIDs unfolds in three distinct phases. Initially, the consumers’ perceptions of social influence (SI), hedonic motivation (HM), and perceived anthropomorphism (PA) positively influence their green performance expectancy (GPE) and green effort expectancy (GEE) concerning AIDs. As a result, greater GPE and GEE among bank customers lead to stronger positive emotions, which greatly contribute to increased AIDs usage and a reduction in resistance to their implementation. Additionally, the findings determine that technological literacy plays a substantial moderating role in the association connecting green performance expectancy and customer emotions in relation to adopting AIDs, thereby highlighting its importance in advancing sustainable banking initiatives. Full article
(This article belongs to the Special Issue Artificial Intelligence in Sustainable Industry)
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Review

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17 pages, 10837 KiB  
Review
A Review of the Application of Computer Vision Techniques in Sustainable Engineering of Open Pit Mines
by Di Shan, Fuming Qu, Zheng Wang, Yaming Ji and Jianwei Xu
Sustainability 2025, 17(7), 3051; https://doi.org/10.3390/su17073051 - 29 Mar 2025
Viewed by 856
Abstract
Mineral resources are important industrial raw materials and the cornerstone of ensuring industrial production, especially metal ores. With the continuous development and progress of artificial intelligence technology, it is of great significance to apply artificial intelligence technology to mining. Computer vision technology, as [...] Read more.
Mineral resources are important industrial raw materials and the cornerstone of ensuring industrial production, especially metal ores. With the continuous development and progress of artificial intelligence technology, it is of great significance to apply artificial intelligence technology to mining. Computer vision technology, as a sensor that collects information like a human “eye”, is becoming increasingly important in ensuring mining safety, improving mining continuity, and reducing environmental interference through computer vision methods. In this context, this paper focuses on general problems of metal mineral resources, the sustainability of exploration, drilling and blasting, transport, personnel safety, and security. It describes the latest progress of computer vision technology in each link and summarizes and looks forward to the key technical methods. It also summarizes and looks ahead to the key technical methods in each area. The research results show that the application of computer-vision-related technologies in related links not only greatly improves production efficiency but also reduces environmental interference and the probability of production safety accidents, effectively ensuring sustainable mining. In the future, to achieve unmanned mining throughout the entire process, it will be necessary to combine computer vision technology with other specialties such as intelligent control and intelligent perception to achieve a technological breakthrough throughout the entire process. Full article
(This article belongs to the Special Issue Artificial Intelligence in Sustainable Industry)
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