Special Issue "Data-Driven Intelligent Manufacturing for Circular Economy and Sustainability"

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

Deadline for manuscript submissions: 15 May 2022.

Special Issue Editors

Dr. Miying Yang
E-Mail Website
Guest Editor
Group of Sustainability, School of Management, Cranfield University, Cranfield MK43 0AL, UK
Interests: digital sustainability; sustainable supply chains; Industry 4.0; sustainable manufacturing
Prof. Dr. Steve Evans
E-Mail Website
Guest Editor
Centre for Industrial Sustainability, Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK
Interests: industrial sustainability; life cycle engineering; circular economy; industrial symbiosis; sustainable design; sustainable manufacturing
Prof. Dr. Saeema Ahmed-Kristensen
E-Mail Website
Guest Editor
Initiative for Digital Economy INDEX, Business School, University of Exeter, Exeter EX4 4PU, UK
Interests: data-driven product development; design engineering; design innovation; knowledge management; creativity and cognition

Special Issue Information

Dear Colleagues,

In the current Industry 4.0 era, many firms have been exploring the adoption of the emerging digital technologies for sustainable intelligent manufacturing, e.g., Internet of Things (IoT), digital twin, artificial intelligence (AI), big data analytics, 3D printing, robotics, virtual reality, and cloud computing. The IoT has been extensively applied in factories and supply chains to monitor the production process and track and trace the logistics and warehouse operations. Big data analytics are used to analyse the large volume of data generated from IoT devices and other sources. AI is used to provide predictive and preventive functions of data analysis through learning algorithms. These digital technologies are recognised widely as a means to improve labour productivity, but with much less recognition that they are also a promising means to improve the sustainability performance of manufacturing and supply chains.

Despite their promising functions, recent research and practice have shown that manufacturing firms often fail in adopting these emerging digital technologies towards sustainability goals. Technology innovation alone is not sufficient to achieve sustainable intelligent manufacturing. It also requires the design of new, data-driven business models (e.g., digital product-service systems), and the reconfiguration of digital supply chains and business ecosystems to facilitate this transition. The current academic understanding of this topic and the applications in companies are still limited.

This Special Issue calls for academic papers on data-driven intelligent manufacturing for circular economy and sustainability from both technical aspects that show the potential of digital technologies to deliver better sustainability performance, as well as management aspects that relate to why and how these technologies could be implemented effectively. Relevant topics include but are not limited to:

  • Digitalisation and sustainability;
  • Digitalisation and circular economy;
  • Data-driven business model innovation for sustainability or circular economy;
  • The impact of digitalisation on supply chain sustainability;
  • The adoption of digital technologies for sustainability or circular economy;
  • The design, modelling, and simulation of business ecosystem towards sustainability;
  • Enablers and barriers of transition towards data-driven sustainable manufacturing;
  • Methods and tools for intelligent sustainable design and manufacturing;
  • Digital product-service system for sustainability or circular economy;
  • Supply chain implications of different sustainable business models;
  • Life cycle data for sustainability.

Contributions of any types are welcome, including literature reviews, conceptual studies, empirical studies, case studies, modelling, and simulation.

Dr. Miying Yang
Prof. Dr. Steve Evans
Prof. Dr. Saeema Ahmed-Kristensen
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 papers will be 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 1900 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

  • intelligent manufacturing
  • circular economy
  • data-driven design
  • data-driven manufacturing
  • data-driven business model innovation
  • data-driven ecosystem
  • data-driven supply chains
  • Industry 4.0 for sustainability
  • digital supply chain
  • digital product-service systems
  • digital twin
  • Industry 4.0 technologies (e.g., IoT, big data, AI, additive manufacturing, robotics)
  • sustainable value innovation
  • Life cycle data for sustainability

Published Papers

This special issue is now open for submission.
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