Technology Integration for Smart Manufacturing/Re-manufacturing Systems Development

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 4471

Special Issue Editors


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Guest Editor
Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy
Interests: remanufacturing; industrial system design and optimization; ergonomics
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Guest Editor
Department of Industrial Engineering, University of Salerno, I-84084 Fisciano, Italy
Interests: maintenance; industrial system design and optimization

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Guest Editor
Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy
Interests: remanufacturing; digital twin; industrial symbiosis; CMMS; lean management; industrial system design and management
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy
Interests: human–robot interaction; human reliability analysis in production and services; industrial system design and management; operations and maintenance management
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Dipartimento di Ingegneria—Università della Campania “Luigi Vanvitelli”, Via Roma, 29, 81031 Aversa, CE, Italy
Interests: industrial manufacturing system design and optimization; industrial production management and optimization
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Engineering, University of Campania “Luigi Vanvitelli”, via Roma 29, 81031 Aversa, Italy
Interests: human–robot interaction; industrial system design and optimization; supply chain modelling and simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The growth of advanced technologies and their extensive applications in industry are changing the current approach to manufacturing.

The introduction of modern I5.0 technologies and concepts in factory environments could lead to the smart transformation of production and manufacturing systems, while also favoring a circular economy approach, which is mainly expressed in remanufacturing. Technologies such as Digital Twin (DT), Virtual Reality (VR), Artificial Intelligence (AI), the Internet of Things (IoT) and Cloud Computing could improve shop floor performance and facilitate the development of new, profitable businesses. The integration of these technologies contributes to digital transformation and reveals new perspectives for companies, which have led to the achievement human-oriented factory environments and the growth of overall equipment effectiveness in manufacturing systems.

This Special Issue focuses on the scientific and industrial aspects of the integration of new technologies in manufacturing, and their effects on industrial system performance. We welcome original research exploring recent developments in the digital transformation of factories; case studies demonstrating the effectiveness of these transformations; and review articles.

Potential topics include, but are not limited to:

  • The integration of technology for smart manufacturing/remanufacturing system realization;
  • Digital Twins for enhancing manufacturing/remanufacturing systems;
  • Human–robot cooperation in manufacturing/remanufacturing contexts;
  • Cloud Manufacturing;
  • Cloud Remanufacturing;
  • Artificial Intelligence for Prognostics;
  • Artificial Intelligence for improving production processes;
  • The Internet of Things in manufacturing/remanufacturing contexts;
  • Additive manufacturing;
  • Virtual reality, cross reality or mixed reality in manufacturing/remanufacturing contexts;
  • The use of technologies for improving manufacturing/remanufacturing system performance;
  • New performance measurement methods;
  • Decision support systems for industrial system management and improvement;
  • Key performance indicators for the sustainable control and management of industrial systems;
  • The use of technologies for reverse logistics in remanufacturing;
  • Industrial symbiosis for sustainable manufacturing.

Dr. Mario Caterino
Dr. Salvatore Miranda
Dr. Raffaele Iannone
Dr. Valentina Di Pasquale
Dr. Marcello Fera
Dr. Marta Rinaldi
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. 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.

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Published Papers (2 papers)

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Research

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22 pages, 4139 KiB  
Article
An Internet of Things-Based Production Scheduling for Distributed Two-Stage Assembly Manufacturing with Mold Sharing
by Yin Liu, Cunxian Ma and Yun Huang
Machines 2024, 12(5), 310; https://doi.org/10.3390/machines12050310 - 2 May 2024
Viewed by 1191
Abstract
In digital product and ion scheduling centers, order–factory allocation, factory–mold allocation, and mold routing can be performed centrally and efficiently to maximize the utilization of manufacturing resources (molds). Therefore, in this paper, a manufacturing resource (molds)-sharing mechanism based on the Internet of Things [...] Read more.
In digital product and ion scheduling centers, order–factory allocation, factory–mold allocation, and mold routing can be performed centrally and efficiently to maximize the utilization of manufacturing resources (molds). Therefore, in this paper, a manufacturing resource (molds)-sharing mechanism based on the Internet of Things (IoT) and a cyber-physical production system (CPPS) is designed to realize the coordinated allocation of molds and production scheduling. A mixed-integer mathematical model is developed to optimize the cost structure and obtain a reasonable profit solution. A heuristic algorithm based on evolutionary reversal is used to solve the problem. The numerical results show that based on the digital coordinated production scheduling method, distributed two-stage assembly manufacturing with shared molds can effectively reduce the order delay time and increase potential benefits for distributed production enterprises. Full article
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20 pages, 1209 KiB  
Review
Virtual Reality for Training in Assembly and Disassembly Tasks: A Systematic Literature Review
by Valentina Di Pasquale, Paolo Cutolo, Carmen Esposito, Benedetta Franco, Raffaele Iannone and Salvatore Miranda
Machines 2024, 12(8), 528; https://doi.org/10.3390/machines12080528 - 2 Aug 2024
Cited by 2 | Viewed by 1999
Abstract
The evolving landscape of industrial manufacturing is increasingly embracing automation within smart factories. However, the critical role of human operators, particularly in manual assembly and disassembly tasks, remains undiminished. This paper explores the complexities arising from mass customization and remanufacturing, which significantly enhance [...] Read more.
The evolving landscape of industrial manufacturing is increasingly embracing automation within smart factories. However, the critical role of human operators, particularly in manual assembly and disassembly tasks, remains undiminished. This paper explores the complexities arising from mass customization and remanufacturing, which significantly enhance the intricacy of these manual tasks. Human involvement is essential in these tasks due to their complexity, necessitating a structured learning process to enhance efficiency and mitigate the learning–forgetting cycle. This study focuses on the utilization of virtual reality (VR) as an innovative training tool to address these challenges. By conducting a systematic literature review (SLR) on the impact of VR on training operators for assembly and disassembly tasks, this paper evaluates the current level of VR application, the used technologies, the operator performance, and the VR benefits and limitations. The analysis reveals a limited but promising application of VR in training, highlighting its potential to improve learning outcomes, productivity, and safety while reducing costs. However, the research also identifies gaps in the practical application of VR for training purposes suggesting a future research agenda to explore its full potential. Full article
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