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Smart Manufacturing and Industry 4.0: 3rd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 192

Special Issue Editors


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Guest Editor
Department of Automotive, Mechanical and Manufacturing Engineering, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, ON L1H 7K4, Canada
Interests: precision manufacturing; advanced manufacturing technologies; digital manufacturing; measurement uncertainty; 3D coordinate metrology
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Mechatronics and Mechanical Systems Engineering, Universidade de São Paulo, São Paulo 2231, Brazil
Interests: CAD/CAM; computer graphics; Industry 4.0; cutting and packing and optimization problems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Smart manufacturing processes and systems have been receiving a great amount of attention through the latest innovations, ongoing efforts, and best practices in the Industry 4.0 era. The concept of the smart factory—along with its cyber-physical systems, intelligent support for manufacturing decision-making, and intelligent inspection to monitor production health—has become increasingly central to modern industrial transformation.

This includes in situ data collection and fusion of sensor information for manufacturing processes, collaborative robots, self-configuration and self-diagnosis, the Internet of Things for shop floors, intelligent prescriptive and preventive maintenance, simulation-assisted process control and digital twins, big data analytics for manufacturing systems and processes, on-demand and customized production through hybrid additive and subtractive manufacturing, autonomy and autonomous vehicles, smart quality assurance and intelligent inspection, data-driven and model-based prognostics, and zero-defect production.

This Special Issue of Applied Sciences aims to showcase new initiatives, applications, and research advances in smart manufacturing processes and systems that address the needs of the fourth industrial revolution.

Dr. Ahmad Barari
Dr. Marcos de Sales Guerra Tsuzuki
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. Applied Sciences 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

  • smart manufacturing
  • intelligent manufacturing
  • Industry 4.0
  • digital manufacturing
  • digital metrology
  • intelligent support systems
  • manufacturing process control
  • smart quality assurance
  • intelligent inspection
  • predictive and prescriptive maintenance
  • model-based prognostics
  • vision systems
  • collaborative robots
  • manufacturing health management
  • artificial intelligence for manufacturing processes
  • big data analytics
  • sensor information
  • digital twins
  • manufacturing virtualization and simulation
  • self-configuration and self-diagnosis
  • Internet of Things
  • self-optimization models
  • scheduling and sequencing
  • blockchain technology
  • resource efficiency
  • circular economy tracking
  • autonomy
  • autonomous vehicles
  • drones

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Published Papers (1 paper)

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Research

21 pages, 1055 KB  
Article
Barriers for Smart Manufacturing Implementation in SMEs: A Comprehensive Exploration and Practical Insights
by Vladimir Modrak and Zuzana Soltysova
Appl. Sci. 2025, 15(19), 10552; https://doi.org/10.3390/app151910552 - 29 Sep 2025
Abstract
The aim of this study was to identify and explore the most significant barriers in implementing smart manufacturing (SM) in terms of small and medium enterprises (SMEs). A two-round Delphi method was used to uncover them in this regard. To assess the reliability [...] Read more.
The aim of this study was to identify and explore the most significant barriers in implementing smart manufacturing (SM) in terms of small and medium enterprises (SMEs). A two-round Delphi method was used to uncover them in this regard. To assess the reliability of the obtained results, Cronbach’s alpha, Intraclass correlation coefficient, and a statistical F-test were performed for both rounds. Cronbach’s alpha for round 1 was 0.729, and 0.816 for round 2. On this basis, good inter-rater reliability was demonstrated in round 2. At the same time, the Intraclass correlation coefficient from round 1 was 0.54, and from round 2, it was 0.74, indicating a significant improvement in panel consensus. The comparison of the equality of variances within the two rounds using the F-test confirmed that a third round of the survey was not necessary. Moreover, the coefficient of variation and relative interquartile range were applied to assess internal consistency among the involved experts to come to a more comprehensive and cohesive understanding of the issue at hand. A total of 30 barriers/limitations or shortages were identified in the preparatory phase of the research, which, in some sense, do not allow or slow down the implementation of the SM. The Delphi survey found that financial problems, lack of government support, and technological constraints can be considered as the most serious barriers to the implementation of SM in an SME environment. Finally, the obstacles/constraints or shortcomings that proved to be the most critical were analyzed in terms of their impact on the ability of small and medium-sized enterprises to embrace the challenges of smart manufacturing. Full article
(This article belongs to the Special Issue Smart Manufacturing and Industry 4.0: 3rd Edition)
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