Digital Technology in Sustainable Manufacturing Systems
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 October 2023) | Viewed by 4051
Special Issue Editors
Interests: digital twin; intelligent operation and maintenance; optimization design of complex equipment
Special Issues, Collections and Topics in MDPI journals
Interests: industrial sustainability; manufacturing systems; knowledge management; digital twin
Special Issue Information
Dear Colleagues,
We are pleased to invite you to contribute to “Digital Technology in Sustainable Manufacturing Systems” in Sustainability. This Special Issue investigates how digital technologies impact economic, environmental, and social aspects of sustainable manufacturing, including process optimization, energy, material efficiency, waste reduction and reuse, policy frameworks, and regulatory tools. Digital technology plays a crucial role in sustainable manufacturing practices. It involves the use of technologies such as robotics, artificial intelligence, big data, and the Internet of Things (IoT), and the development and integration of new digital technologies such as digital twins, advanced sensors, and predictive analytics to achieve specific goals in the circular economy, industrial symbiosis, human-centered manufacturing, and life cycle assessment for sustainability.
There are several challenges related to digital technologies for sustainability in manufacturing systems. The problems involved in digital technologies are extensive and complex, as the corresponding working conditions vary from manufacturing systems. In the meantime, sustainable manufacturing focuses on reducing the environmental impact by minimizing and reusing wastes, reducing energy consumption, and utilizing renewable energy sources. The integration of digital technologies into sustainable manufacturing processes further opens up research directions on evaluating, monitoring, and optimizing waste reduction, energy efficiency, and materials utilization.
We have organized this Special Issue to call for discussions on the latest research progress in digital technologies for sustainable manufacturing, including various problems faced in the improvement of sustainable manufacturing systems and the impacts of digital technologies on sustainability
Prof. Dr. Hao Li
Dr. Shuai Zhang
Dr. Haoqi Wang
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
- sustainable manufacturing
- wastes reduction
- energy consumption and efficiency
- process optimization
- artificial intelligence
- digital twin
- internet of thing (IoT)
- industrial symbiosis
- circular economy
- life cycle assessment