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Industry 4.0 and Application of Artificial Intelligence System in Operation Management

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

Deadline for manuscript submissions: 31 December 2025 | Viewed by 922

Special Issue Editor


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Guest Editor
Facultad de Ciencias Físico Matemáticas, Universidad Autónoma de Nuevo León, San Nicolás de los Garza, Nuevo León, Mexico
Interests: large-scale optimization; high-performance computing; digital twins; integer programming; global optimization; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue of the journal Sustainability, which focuses on the critical intersection and the application of artificial intelligence in operation management, life cycle analysis, lean manufacturing, and green optimization in the pursuit of sustainable manufacturing practices. As industries face increasing pressure to reduce their environmental footprints while maintaining economic viability, the integration of these methodologies has become essential. Life cycle analysis (LCA) provides a comprehensive framework for assessing the environmental impacts of products throughout their entire life cycle, from raw material extraction to disposal. Lean manufacturing principles emphasize waste reduction and efficiency, which align perfectly with sustainability goals. Meanwhile, green optimization techniques aim to enhance resource utilization and minimize negative environmental impacts. This research area is of paramount importance as it not only addresses the urgent need for sustainable development but also fosters innovation and competitive advantage in manufacturing considering Industry 4.0.

This Special Issue aims to gather a diverse array of research contributions that advance the understanding and implementation of sustainable practices in manufacturing through the lenses of life cycle analysis, lean manufacturing, and green optimization. By focusing on these interconnected themes, we seek to provide insights that are directly relevant to the scope of the journal Sustainability, which aims to promote multidisciplinary discussions on environmental, social, and economic sustainability. We aspire to compile research that explore both theoretical frameworks and practical applications, and if the number of submissions allows, the Special Issue may be published in book form. Contributions that offer novel methodologies, case studies, or empirical research will be particularly valuable in enriching this discourse.

In this Special Issue, original research articles and comprehensive reviews are welcome. We encourage submissions that explore, but are not limited to, the following research areas:

  • Digital Twins Development
  • Life Cycle Analysis Applications in Manufacturing
  • Industry 4.0 and Sustainable Manufacturing
  • Application of Artificial Intelligence in Operation Management
  • Lean Manufacturing Techniques for Sustainable Production
  • Green Optimization Strategies
  • Circular Economy Models in Manufacturing
  • Case Studies of Sustainable Manufacturing Practices
  • Quantitative and Qualitative Metrics for Sustainability Assessment
  • Barriers and Drivers of Sustainable Manufacturing Adoption
  • Technological Innovations Supporting Sustainable Practices

I look forward to receiving your contributions and fostering a rich dialogue on sustainable practices in manufacturing. Together, we can advance knowledge and foster actionable insights that contribute to a more sustainable future. Join us in this important endeavor to promote sustainability within the manufacturing sector.

Prof. Dr. Jose Antonio Marmolejo-Saucedo
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. 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

  • digital twins
  • Industry 4.0
  • life cycle analysis
  • lean manufacturing
  • green optimization
  • sustainable practices
  • circular economy

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Published Papers (2 papers)

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Research

35 pages, 1049 KiB  
Article
Strategic Human Resource Development for Industry 4.0 Readiness: A Sustainable Transformation Framework for Emerging Economies
by Kwanchanok Chumnumporn Vong, Kalaya Udomvitid, Yasushi Ueki, Nuchjarin Intalar, Akkaranan Pongsathornwiwat, Warut Pannakkong, Somrote Komolavanij and Chawalit Jeenanunta
Sustainability 2025, 17(15), 6988; https://doi.org/10.3390/su17156988 - 1 Aug 2025
Viewed by 322
Abstract
Industry 4.0 represents a significant transformation in industrial systems through digital integration, presenting both opportunities and challenges for aligning the workforce, especially in emerging economies like Thailand. This study adopts a sequential exploratory mixed-method approach to investigate how strategic human resource development (HRD) [...] Read more.
Industry 4.0 represents a significant transformation in industrial systems through digital integration, presenting both opportunities and challenges for aligning the workforce, especially in emerging economies like Thailand. This study adopts a sequential exploratory mixed-method approach to investigate how strategic human resource development (HRD) contributes to sustainable transformation, defined as the enduring alignment between workforce capabilities and technological advancement. The qualitative phase involved case studies of five Thai manufacturing firms at varying levels of Industry 4.0 adoption, utilizing semi-structured interviews with executives and HR leaders. Thematic findings informed the development of a structured survey, distributed to 144 firms. Partial Least Squares Structural Equation Modeling (PLS SEM) was used to test the hypothesized relationships among business pressures, leadership support, HRD preparedness, and technological readiness. The analysis reveals that business pressures significantly influence leadership and HRD, which in turn facilitate technological readiness. However, business pressures alone do not directly enhance readiness without the support of intermediaries. These results underscore the critical role of integrated HRD and leadership frameworks in enabling sustainable digital transformation. This study contributes to theoretical perspectives by integrating HRD, leadership, and technological readiness, offering practical guidance for firms aiming to navigate the complexities of Industry 4.0. Full article
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21 pages, 950 KiB  
Article
A Fuzzy Unit Commitment Model for Enhancing Stability and Sustainability in Renewable Energy-Integrated Power Systems
by Sukita Kaewpasuk, Boonyarit Intiyot and Chawalit Jeenanunta
Sustainability 2025, 17(15), 6800; https://doi.org/10.3390/su17156800 - 26 Jul 2025
Viewed by 282
Abstract
The increasing penetration of renewable energy sources (RESs), particularly solar photovoltaic (PV) sources, has introduced significant uncertainty into power system operations, challenging traditional scheduling models and threatening system reliability. This study proposes a Fuzzy Unit Commitment Model (FUCM) designed to address uncertainty in [...] Read more.
The increasing penetration of renewable energy sources (RESs), particularly solar photovoltaic (PV) sources, has introduced significant uncertainty into power system operations, challenging traditional scheduling models and threatening system reliability. This study proposes a Fuzzy Unit Commitment Model (FUCM) designed to address uncertainty in load demand, solar PV generation, and spinning reserve requirements by applying fuzzy linear programming techniques. The FUCM reformulates uncertain constraints using triangular membership functions and integrates them into a mixed-integer linear programming (MILP) framework. The model’s effectiveness is demonstrated through two case studies: a 30-generator test system and a national-scale power system in Thailand comprising 171 generators across five service zones. Simulation results indicate that the FUCM consistently produces stable scheduling solutions that fall within deterministic upper and lower bounds. The model improves reliability metrics, including reduced loss-of-load probability and minimized load deficiency, while maintaining acceptable computational performance. These results suggest that the proposed approach offers a practical and scalable method for unit commitment planning under uncertainty. By enhancing both operational stability and economic efficiency, the FUCM contributes to the sustainable management of RES-integrated power systems. Full article
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