sustainability-logo

Journal Browser

Journal Browser

Industry 4.0 for Manufacturing Sustainability-Industrial Facilities and Project Management Innovation

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 7714

Special Issue Editors


E-Mail Website
Guest Editor
Department of Engineering, Università degli Studi di Messina, Contrada di Dio, 98166 Messina, Italy
Interests: industrial systems engineering; project management; analysis and design of industrial plants; green supply chain management
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Engineering, University of Palermo, 90128 Palermo, Italy
Interests: numerical simulations; optimization techniques; topology optimization CAD modeling
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Engineering, Università degli Studi di Palermo, Viale delle Scienze, Building 8, 90128 Palermo, Italy
Interests: plant layout; occupational health and safety (OHS); industrial risk; maintenance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Industry 4.0 is the term used in the manufacturing world to denote the fourth industrial revolution, characterized by the use of cyber–physical systems. Smart factories and smart manufacturing are part of the technological transformation introduced by the fourth industrial revolution. A smart factory works by integrating machines, people, and Big Data into a single, digitally connected ecosystem. A smart factory not only curates and analyzes data, it actually learns from experience. It interprets from data sets to forecast trends and events and to implement smart manufacturing workflows and automated processes. A smart factory undergoes continuous procedural improvement to self-optimize to be more resilient, safe, and productive, and to respect environmental sustainability. Despite the important contribution made by researchers around the world, further efforts are still needed to find innovative and economically sustainable technological solutions. Although most studies are focused on technological aspects, the way Industry 4.0 is revolutionizing traditional project management methods has not been sufficiently analyzed. Industry 4.0 is revolutionizing the traditional methods of project management. More and more virtual representations of the real world are created and computer systems are developed. In short, we are reaching levels where such systems are able to act autonomously and make their own decisions. Managing an innovation environment such as Industry 4.0, therefore, requires a creative and entirely new way of thinking. Traditional project management  styles have to be changed in order to adapt to the fourth industrial revolution. This requires further efforts by the research community, and not only from a technological perspective.

This Special Issue is focused on the development of new technologies centered on the Industry 4.0 paradigm and environmental sustainability. Project management studies in the Industry 4.0 era are also welcome. Contributions may include empirical research, case studies, or comparative or theoretical studies. Possible topics of interest include, but are not limited to:

  • Industry 4.0 and sustainable production;
  • Advanced manufacturing techniques in the Industry 4.0 era;
  • Artificial Intelligence and Machine learning techniques to improve process control and part quality;
  • Case studies in the design and deployment of digital manufacturing paradigms;
  • Industry 4.0 and project management;
  • Digitization and project management platforms.

Prof. Dr. Antonio Giallanza
Prof. Dr. Giuseppe Marannano
Prof. Dr. Concetta Manuela La Fata
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

  • Industry 4.0
  • smart factory
  • smart manufacturing
  • smart design
  • smart production
  • project management innovation
  • sustainable technological solutions

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

21 pages, 2538 KiB  
Article
China’s Industrial TFPs at the Prefectural Level and the Law of Their Spatial–Temporal Evolution
by Wei Wei, Qiao Fan and Aijun Guo
Sustainability 2023, 15(1), 322; https://doi.org/10.3390/su15010322 - 25 Dec 2022
Cited by 1 | Viewed by 1728
Abstract
Calculating China’s industrial total factor productivity (TFP) at the prefectural level comprehensively and accurately is not only an inevitable requirement for China’s industrialization to enter the new development stage of “improving quality and efficiency”, but also a practical need for TFP improvement at [...] Read more.
Calculating China’s industrial total factor productivity (TFP) at the prefectural level comprehensively and accurately is not only an inevitable requirement for China’s industrialization to enter the new development stage of “improving quality and efficiency”, but also a practical need for TFP improvement at the industrial level. Based on the improved Solow residual method with the general nesting spatial model embedded, this paper comprehensively calculated the industrial TFPs of 280 prefectural cities in China from 2003 to 2019, and undertook a detailed analysis of the spatiotemporal evolution law of the calculation results through Dagum’s Gini coefficient and kernel density estimation. Three main conclusions have been drawn in this paper. First, there is an apparent spatial difference among the industrial TFPs of the prefectural cities in China. It is the poorest and has an evident declining trend in northeast China, and best in eastern China, while the development of central and western China is between east and northeast China. Second, the spatial difference level of industrial TFPs of the prefectural cities in China shows a general development trend of firstly falling and then rising. Comparatively speaking, the contribution of intra-group differences is low, while the contribution of inter-group and the intensity of trans-variation are high. Third, the spatiotemporal evolution of China’s industrial TFPs at the prefectural level has the following characteristics: the overall distribution curve moves firstly towards the right and then left, the kernel density at the peak point continuously declines, the distribution ranges are firstly widening and then narrowing, and the tails of the distribution curve are constantly extending. Meanwhile, the distribution figures of the kernel density estimation in different regions show apparent heterogeneity. Full article
Show Figures

Figure 1

18 pages, 2820 KiB  
Article
Examining the Location Characteristics of Knowledge Industrial Space for Smart Planning and Industry 4.0: A Case Study of Hangzhou, China
by Qianhu Chen, Jing Chen and Yufan Ye
Sustainability 2022, 14(21), 14594; https://doi.org/10.3390/su142114594 - 06 Nov 2022
Cited by 1 | Viewed by 4881
Abstract
In the era of Industry 4.0, the knowledge economy is reshaping the global economic structure, which makes the research on the layout of knowledge industries particularly important. This study, using Hangzhou in China as a case, constructs an index system from two dimensions [...] Read more.
In the era of Industry 4.0, the knowledge economy is reshaping the global economic structure, which makes the research on the layout of knowledge industries particularly important. This study, using Hangzhou in China as a case, constructs an index system from two dimensions (i.e., business and living amenities), and compares three typical representative knowledge industries. The nearest neighbor index, kernel density, and stepwise regression model were adopted. Results revealed that: (1) The spatial agglomeration intensity of knowledge industries is varied in different classes, with the financial industry being the most agglomerated, scientific research technology service industry the second, and smart manufacturing industry the least agglomerated. (2) The spatial distribution of knowledge industries is agglomerated in the shape of “#”, which is in line with the urban skeleton. (3) For the distribution of the financial industry, parking lots and cafés are strong influencing factors. The scientific research technology service industry locates closer to sports and fitness amenities, colleges and universities, and parks, while the smart manufacturing industry has a strong connection with snacking spots, fast food, and scientific research institutions. The results can provide a decision-making basis for the micro-location selection of urban knowledge industries and the adjustment of future industrial planning in the intelligent era. Full article
Show Figures

Figure 1

Back to TopTop