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Applied Sciences
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Smart Manufacturing and Industry 4.0, 2nd Edition
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Smart Manufacturing and Industry 4.0, 2nd Edition

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

Deadline for manuscript submissions: 20 May 2025 | Viewed by 8458

Special Issue Editors

Dr. Marcos de Sales Guerra Tsuzuki

E-Mail Website
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
Dr. Ahmad Barari

E-Mail Website
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; precision manufacturing; measurement uncertainty; 3D coordinate metrology
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 idea of the smart factory and its cyber physical systems, intelligent support systems for manufacturing decision making, intelligent inspection to monitor production health, in situ data collection and fusion of sensor information for manufacturing processes, collaborative robots, self-configuration and self-diagnosis, Internet of Things for manufacturing 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 processes utilizing the hybrid model of additive and subtractive manufacturing, autonomy and autonomous vehicles, smart quality assurance and intelligent inspection, data-driven and model-based prognostics, and zero defect production are among the most important topics that need further research attention. This call aims to develop a Special Issue of the journal of Applied Sciences dedicated to publishing new initiatives, applications, and research advances on smart manufacturing processes and systems addressing the needs of the fourth industrial revolution.

Dr. Marcos de Sales Guerra Tsuzuki
Dr. Ahmad Barari
Guest Editors

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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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Related Special Issue

Published Papers (5 papers)

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Research

23 pages, 16504 KiB  
Article
Skin Imaging: A Digital Twin for Geometric Deviations on Manufactured Surfaces
by Elnaz Ghanbary Kalajahi, Mehran Mahboubkhah and Ahmad Barari
Appl. Sci. 2023, 13(23), 12971; https://doi.org/10.3390/app132312971 - 4 Dec 2023
Viewed by 1377
Abstract
Closed-loop manufacturing is crucial in Industry 4.0, since it provides an online detection–correction cycle to optimize the production line by using the live data provided from the product being manufactured. By integrating the inspection system and manufacturing processes, the production line achieves a [...] Read more.
Closed-loop manufacturing is crucial in Industry 4.0, since it provides an online detection–correction cycle to optimize the production line by using the live data provided from the product being manufactured. By integrating the inspection system and manufacturing processes, the production line achieves a new level of accuracy and savings on costs. This is far more crucial than only inspecting the finished product as an accepted or rejected part. Modeling the actual surface of the workpiece in production, including the manufacturing errors, enables the potential to process the provided live data and give feedback to production planning. Recently introduced “skin imaging” methodology can generate 2D images as a comprehensive digital twin for geometric deviations on any scanned 3D surface including analytical geometries and sculptured surfaces. Skin-Image has been addressed as a novel methodology for continuous representation of unorganized discrete 3D points, by which the geometric deviation on the surface is shown using image intensity. Skin-Image can be readily used in online surface inspection for automatic and precise 3D defect segmentation and characterization. It also facilitates search-guided sampling strategies. This paper presents the implementation of skin imaging for primary engineering surfaces. The results, supported by several industrial case studies, show high efficiency of skin imaging in providing models of the real manufactured surfaces. Full article
(This article belongs to the Special Issue Smart Manufacturing and Industry 4.0, 2nd Edition)
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34 pages, 14174 KiB  
Article
Cloud-Based Architecture for Production Information Exchange in European Micro-Factory Context
by Fábio M-Oliveira, André Dionísio Rocha, Duarte Alemão, Nelson Freitas, Rayko Toshev, Jani Södergård, Nikolaos Tsoniotis, Charalampos Argyriou, Alexios Papacharalampopoulos, Panagiotis Stavropoulos, Pietro Perlo and José Barata
Appl. Sci. 2023, 13(18), 10223; https://doi.org/10.3390/app131810223 - 12 Sep 2023
Cited by 1 | Viewed by 1624
Abstract
In a constantly changing world, information stands as one of the most valuable assets for a manufacturing site. However, exchanging information is not a straightforward process among factories, and concerns regarding the trustability and validation of transactions between various stakeholders have emerged within [...] Read more.
In a constantly changing world, information stands as one of the most valuable assets for a manufacturing site. However, exchanging information is not a straightforward process among factories, and concerns regarding the trustability and validation of transactions between various stakeholders have emerged within the context of micro-factories. This work presents an architecture designed to enable information exchange among heterogeneous stakeholders, taking advantage of the cloud infrastructure. It was designed to enable the use of several tools, connected through a middleware system deployed on the cloud. To demonstrate the potential of this architecture, a platform was instantiated, and two use cases—designed to accurately represent real manufacturing sites—were implemented. Full article
(This article belongs to the Special Issue Smart Manufacturing and Industry 4.0, 2nd Edition)
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19 pages, 667 KiB  
Article
Dimensional Tolerances in Mechanical Assemblies: A Cost-Based Optimization Approach
by Eduardo Umaras, Ahmad Barari, Oswaldo Horikawa and Marcos Sales Guerra Tsuzuki
Appl. Sci. 2023, 13(16), 9202; https://doi.org/10.3390/app13169202 - 13 Aug 2023
Cited by 1 | Viewed by 2329
Abstract
There is a widely accepted consensus that component manufacturing precision is directly correlated with improved functional performance. However, this increase in precision comes at the expense of higher manufacturing costs, resulting in a trade-off between quality and affordability. In light of this opposing [...] Read more.
There is a widely accepted consensus that component manufacturing precision is directly correlated with improved functional performance. However, this increase in precision comes at the expense of higher manufacturing costs, resulting in a trade-off between quality and affordability. In light of this opposing behavior, low-cost products typically exhibit lower quality, whereas high-quality products tend to be more expensive. This study introduces a novel approach for optimizing the dimensional tolerances of mechanical assembly components, taking into account both their manufacturing requirements and the associated costs of non-quality. Furthermore, the method considers the functional constraints imposed by interrelated tolerance chains within the product. Instead of relying on an exact mathematical solution, the proposed solution employs a heuristic approach through a simple and flexible algorithm. This enables practical implementation, as different cost-tolerance functions can be selected based on specific requirements. To provide a comprehensive evaluation of the proposed method, a concise review of the relevant literature in the field was conducted, allowing a comparison with other state-of-the-art approaches. Full article
(This article belongs to the Special Issue Smart Manufacturing and Industry 4.0, 2nd Edition)
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19 pages, 2989 KiB  
Article
Project Portfolio Planning Taking into Account the Effect of Loss of Competences of Project Team Members
by Grzegorz Bocewicz, Eryk Szwarc, Amila Thibbotuwawa and Zbigniew Banaszak
Appl. Sci. 2023, 13(12), 7165; https://doi.org/10.3390/app13127165 - 15 Jun 2023
Viewed by 939
Abstract
This paper deals with a declarative model of the performance of employees conducting variably repetitive tasks based on the assumption of aging competences. An analytical model is used to consider refreshing the competences of the team’s multi-skilled members and shaping the structure of [...] Read more.
This paper deals with a declarative model of the performance of employees conducting variably repetitive tasks based on the assumption of aging competences. An analytical model is used to consider refreshing the competences of the team’s multi-skilled members and shaping the structure of staff’s competences to maximize their mutual substitutability in processes typical for a multi-item lot-size production. Its impact on maintaining the skill level of employees is important in cases of an unplanned event, e.g., caused by employee absenteeism and/or a change in the priorities of orders carried out, disrupting the task of software companies. The developed model implemented in the constraint programming environment enables the formulation of decision-making versions of both the problem of analysis (seeking an answer to the question to discover whether there is a solution that meets the given expectations) and synthesis (seeking an answer to the question, assuming there is a solution that meets the given expectations). The potential of the proposed reference model-based approach is illustrated with examples. Full article
(This article belongs to the Special Issue Smart Manufacturing and Industry 4.0, 2nd Edition)
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19 pages, 8374 KiB  
Article
Retrieval of Injection Molding Industrial Knowledge Graph Based on Transformer and BERT
by Zhe-Wei Zhou, Wen-Ren Jong, Yu-Hung Ting, Shia-Chung Chen and Ming-Chien Chiu
Appl. Sci. 2023, 13(11), 6687; https://doi.org/10.3390/app13116687 - 31 May 2023
Cited by 1 | Viewed by 1373
Abstract
Knowledge graphs play an important role in the field of knowledge management by providing a simple and clear way of expressing complex data relationships. Injection molding is a highly knowledge-intensive technology, and in our previous research, we have used knowledge graphs to manage [...] Read more.
Knowledge graphs play an important role in the field of knowledge management by providing a simple and clear way of expressing complex data relationships. Injection molding is a highly knowledge-intensive technology, and in our previous research, we have used knowledge graphs to manage and express relevant knowledge, gradually establishing an injection molding industrial knowledge graph. However, the current way of retrieving knowledge graphs is still mainly through programming, which results in many difficulties for users without programming backgrounds when it comes to searching a graph. This study will utilize the previously established injection molding industrial knowledge graph and employ a BERT (Bidirectional Encoder Representations from Transformers) fine-tuning model to analyze the semantics of user questions. A knowledge graph will be retrieved through a search engine built on the Transformer Encoder, which can reason based on the structure of the graph to find relevant knowledge that satisfies a user’s questions. The experimental results show that both the BERT fine-tuned model and the search engine achieve an excellent performance. This approach can help engineers who do not have a knowledge graph background to retrieve information from the graph by inputting natural language queries, thereby improving the usability of the graph. Full article
(This article belongs to the Special Issue Smart Manufacturing and Industry 4.0, 2nd Edition)
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