Machine Learning Applications for Sustainable and Smart Manufacturing Development
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: 2 November 2026 | Viewed by 280
Editors
Interests: sustainable manufacturing; life cycle assessment (LCA); metrics and methodologies for environmental impact assessment; circular economy and industrial symbiosis; machine learning (ML) and artificial intelligence (AI); Industry 4.0 and twin transition
Interests: smart and sustainable production and logistics; analytics; optimization and intelligent algorithms; expert systems; digital manufacturing & logistic platforms; engineering and performance management systems
Special Issue Information
Dear Colleagues,
Sustainable and smart manufacturing increasingly relies on data-driven decision-making to address global challenges. Machine Learning (ML) provides powerful tools to model complex systems, optimize natural resources consumption, and minimize environmental impact generation. Its applications include manufacturing operations, Life Cycle Assessment (LCA), and logistics, offering transformative opportunities to enhance sustainability and competitiveness across industries. This Special Issue aims to gather cutting-edge research on how ML can accelerate sustainable manufacturing development. Specific emphasis will be given to the following: (i) optimizing sustainability at the operations level, including energy, water, chemical and material consumption optimization; (ii) advancing the state of the art in LCA through data-driven methods, such as surrogate modeling and uncertainty reduction; and (iii) optimizing logistics and supply chains for improved resilience and reduced environmental footprint. This topic directly aligns with Sustainability’s scope, fostering interdisciplinary dialogue between engineering, environmental science, and data analytics.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- ML for energy, water, and resource optimization in manufacturing;
- Data-driven and ML-based approaches for LCA improvement;
- Digital twins, predictive maintenance, and real-time process control for Sustainale Manufacturing;
- Sustainable logistics and supply chain optimization;
- Integration of ML with Circular Economy (CE) and Industrial Symbiosis (IS) strategies;
- Explainable ML and sustainability metrics.
I look forward to receiving your contributions.
Dr. Roberto Rocca
Dr. Francisco Fraile Gil
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized 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
- machine learning
- sustainable manufacturing
- resource consumption optimization
- sustainability innovation
- advances in LCA methodology development
- environmental impact assessment optimization
- sustainable development
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.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
