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Machines
Special Issues
Advances in Smart Manufacturing and Industry 4.0
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Advances in Smart Manufacturing and Industry 4.0

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Material Processing Technology".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 6427

Special Issue Editor

Dr. Shohin Aheleroff

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Guest Editor
SUEZ Smart Solutions Limited, Auckland 1010, New Zealand
Interests: Industry 4.0; digital twin; IoT; mass personalization production

Special Issue Information

Dear Colleagues,

Recognized as the successor to the three earlier Industrial Revolutions, Industry 4.0 represents the smart manufacturing paradigm for the Factories of the Future. Technologies such as additive manufacturing, artificial intelligence, big data, blockchain, cloud computing, cyber-physical systems, digital twins, and the Internet of Things have been widely utilized to transform traditional manufacturing systems into smart ones1. Building a safe human–machine interaction is highly encouraged in smart manufacturing. In this context, smart manufacturing is a means to satisfy increasing individualized requirements aiming at mass personalization for achieving global sustainability 2. While Industry 4.0 is technology-driven, it reminds people about human-centric and resilient manufacturing following social responsibilities and wealth creation.

The manufacturing landscape is changing rapidly, with several innovations, including 3D printing and collaborative robots in agile manufacturing, delivering high-value and affordable products at scale. Nevertheless, a significant gap exists in transforming traditional manufacturing systems into smart ones 3 The increased uncertainty and unpredictability combined with market competition urge the manufacturing industry to move towards a more smart, adaptive, flexible, and responsive manufacturing system. Since the pandemic, the manufacturing industry has been experiencing accelerated disruption and uncertainty, resulting in limited companies being able to make necessary changes with minimum effort and resources in a sufficient time. It is critical for smart manufacturing to utilize enabling technologies to be predictive, proactive, agile, and lean. As an emerging and promising research topic, this Special Issue aims to publish state-of-the-art and visionary research works on Advances in Smart Manufacturing and Industry 4.0, including theoretical methods, conceptual models, Industry 4.0 technologies, manufacturing case studies, and industrial applications 4. Topics to be covered include, but are not limited to the following:

  • Service-oriented approach under Industry 4.0
  • Mass personalisation design, development, and manufacturing
  • Sustainable industrialisation in the United Nations’ Sustainable Development Goal No.9
  • Advanced decision-making for on-demand manufacturing
  • Digital Manufacturing and the Smart Factory
  • Machine tools and machining processes in smart manufacturing
  • Cloud manufacturing for sustainability and resilience
  • Industry 4.0 enabling technologies for lean manufacturing
  • AR/VR/MR-based human–machine interactions in smart manufacturing
  • Machine learning applications for advanced manufacturing
  • Big data and IoT in smart manufacturing
  • Industry 4.0-enabled production planning and maintenance scheduling
  • Knowledge management for smart manufacturing
  • Smart manufacturing process modelling, simulation, and control, toward prediction
  • Case studies under Industry 4.0

Dr. Shohin Aheleroff
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. Machines is an international peer-reviewed open access monthly 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 manufacturing
  • mass personalisation manufacturing
  • IoT
  • additive manufacturing
  • 3D printing
  • big data
  • blockchain
  • sustainable manufacturing
  • resilient manufacturing
  • cyber-physical Systems.

Published Papers (3 papers)

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Research

20 pages, 3459 KiB  
Article
A Hybrid Fuzzy Multi-Criteria Decision-Making Model for Evaluating the Influence of Industry 4.0 Technologies on Manufacturing Strategies
by Fawaz M. Abdullah, Abdulrahman M. Al-Ahmari and Saqib Anwar
Machines 2023, 11(2), 310; https://doi.org/10.3390/machines11020310 - 20 Feb 2023
Cited by 3 | Viewed by 1930
Abstract
Manufacturing is transitioning from traditional and mass manufacturing to mass personalization, fast, and intelligent production. Through full automation in various fields and data sharing, Industry 4.0 (I4.0) contributes to the digitalization of manufacturing by enhancing industrial flexibility and product customization. I4.0 is being [...] Read more.
Manufacturing is transitioning from traditional and mass manufacturing to mass personalization, fast, and intelligent production. Through full automation in various fields and data sharing, Industry 4.0 (I4.0) contributes to the digitalization of manufacturing by enhancing industrial flexibility and product customization. I4.0 is being utilized as a strategy for advanced manufacturing to counter global competitiveness. A company’s manufacturing strategy outputs (MSOs) are critical to its ability to move forward and remain competitive. Despite their importance, I4.0 technologies have received less attention in the literature, and it is unclear how they influence MSOs. Thus, this study aims to build a powerful hybrid MCDM method for ranking the influence of I4.0 technologies on MSOs by adopting a combination of AHP and fuzzy TOPSIS. The application of fuzzy set theory has addressed the ambiguity in comparing various I4.0 technologies. The AHP was used to calculate the weights of criteria and sub-criteria, and the fuzzy-TOPSIS method was utilized to rank the I4.0 technologies. The results revealed that the cost criterion is the most critical factor when implementing I4.0 technologies. In contrast, additive manufacturing (AM) is the most suitable I4.0 technology for countering global competition. Full article
(This article belongs to the Special Issue Advances in Smart Manufacturing and Industry 4.0)
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25 pages, 7703 KiB  
Article
Hard Milling Process Based on Compressed Cold Air-Cooling Using Vortex Tube for Sustainable and Smart Manufacturing
by Luka Celent, Dražen Bajić, Sonja Jozić and Marko Mladineo
Machines 2023, 11(2), 264; https://doi.org/10.3390/machines11020264 - 10 Feb 2023
Cited by 3 | Viewed by 1569
Abstract
Improving machining performance and meeting the requirements of sustainable production at the same time represents a major challenge for the metalworking industry and scientific community. One approach to satisfying the above challenge is to apply different types of cutting fluids or to optimise [...] Read more.
Improving machining performance and meeting the requirements of sustainable production at the same time represents a major challenge for the metalworking industry and scientific community. One approach to satisfying the above challenge is to apply different types of cutting fluids or to optimise their usage during the machining process. The fact that cutting fluids are well known as significant environmental pollutants in the metalworking industry has encouraged researchers to discover new environmentally friendly ways of cooling and lubricating in the machining process. Therefore, the main goal is to investigate the influence of different machining conditions on the efficiency of hard machining and find a sustainable solution towards smart manufacturing. In the experimental part of the work, the influence of various machining parameters and conditions on the efficiency of the process was investigated and measured through the surface roughness, tool wear and cutting force components. Statistical data processing was carried out, and predictive mathematical models were developed. An important achievement is the knowledge of the efficiency of compressed cold air cooling for hard milling with the resulting lowest average flank wear of 0.05 mm, average surface roughness of 0.28 µm, which corresponds to grinding procedure roughness classes of N4 and N5, and average tool durability increase of 26% compared to dry cutting and conventional use of cutting fluids. Becoming a smart machining system was assured via technological improvement achieved through the reliable prediction of tool wear obtained by radial basis neural networks modelling, with a relative prediction error of 3.97%. Full article
(This article belongs to the Special Issue Advances in Smart Manufacturing and Industry 4.0)
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10 pages, 1846 KiB  
Article
Digitising a Machine Tool for Smart Factories
by Anton Averyanov, Shohin Aheleroff, Jan Polzer and Xun Xu
Machines 2022, 10(11), 1093; https://doi.org/10.3390/machines10111093 - 18 Nov 2022
Cited by 3 | Viewed by 2123
Abstract
Smart factory development renders an incredible opportunity for the manufacturing industry to join the Fourth Industrial Revolution (Industry 4.0). However, an incredible number of conventional CNC machine tools are populating the world’s factories. Replacing these machines is an expensive process. This task might [...] Read more.
Smart factory development renders an incredible opportunity for the manufacturing industry to join the Fourth Industrial Revolution (Industry 4.0). However, an incredible number of conventional CNC machine tools are populating the world’s factories. Replacing these machines is an expensive process. This task might be considered unliftable by most small businesses. An inexpensive digitalisation of Machine Tool 3.0 to an Industry 4.0-compatible tool might be one way for small businesses to keep up with the progress and stay competitive. The developed framework uses recent advances in the open-source community to transform a conventional CNC machine into Machine Tool 4.0. The suggested approach opens up a way to bypass the proprietary computer numerical control and enable connectivity and efficient data communication with the machine tool. At almost no cost, the provided strategy converts an average CNC machine into a machine tool with the full spectrum of accessibility and interoperability of Machine Tool 4.0. The proposed solution can enable small- and medium-sized enterprises to step up and propel them into the Industry 4.0 era. Full article
(This article belongs to the Special Issue Advances in Smart Manufacturing and Industry 4.0)
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