Special Issue "Design and Manufacturing: An Industry 4.0 Perspective"

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

Deadline for manuscript submissions: 31 October 2022 | Viewed by 801

Special Issue Editors

Dr. Panagiotis Kyratsis
E-Mail Website
Guest Editor
Dept. of Product and Systems Design Engineering, University of Western Macedonia, GR50100 Kila Kozani, Greece
Interests: CAD/CAM/CAE; manufacturing and machining; product and packaging design; reverse engineering and prototyping
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Angelos P. Markopoulos
E-Mail Website
Guest Editor
Prof. Dr. Henrique de Amorim Almeida
E-Mail Website
Guest Editor
Escola Superior de Tecnologia e Gestão de Leiria, Leiria, Portugal
Interests: CAD/CAM/CAE; additive manufacturing; direct digital fabrication; manufacturing and machining; product design; reverse engineering
Dr. Tatjana Spahiu
E-Mail Website
Guest Editor
Faculty of Mechanical Engineering, Textile and Fashion Department, Polytechnic University of Tirana, Tirana, Albania
Interests: CAD-based manufacturing; CAD/CAM/CAE; manufacturing and machining in the fashion industry; reverse engineering and prototyping of garments and footwear

Special Issue Information

Dear Colleagues,

Industrial investments include the use of advanced technologies, which refine, accelerate, improve the quality of, and raise the profitability of the stakeholders. As part of Industry 4.0, 3D printing technology, the Internet of Things (IoT), virtual and augmented reality, artificial intelligence, computer-based simulations, etc., offer considerable opportunities for transforming the traditional approach of product design and manufacturing towards a computer-based innovative way of work. Not only have design and manufacturing changed, but also researchers, engineers and the academic works towards incorporating high-end applications to all stages of a product’s life cycle, each of them shaping the future of the industry by creating both new opportunities within specific sectors and new challenging demands.

This Special Issue aims to assemble recent advances in design and manufacturing from an Industry 4.0 point of view, topics of great interest including frameworks and applications offering advantages towards achieving the goals of Industry 4.0. 

Dr. Panagiotis Kyratsis
Dr. Angelos P. Markopoulos
Prof. Dr. Henrique de Amorim Almeida
Dr. Tatjana Spahiu
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 1800 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 applications
  • 3D printing and additive manufacturing
  • Internet of Things (IoT)
  • 3D virtual and augmented reality
  • 3D prototyping
  • artificial intelligence and machine learning
  • CAD/CAM/CAE systems
  • simulations and reverse engineering
  • modern machining and manufacturing
  • applications and simulations in robotics
  • sustainability and design based on circular economy principles
  • product lifecycle management systems (PLM)
  • sustainable product design and manufacturing
  • computational design, parametric design
  • design for X
  • interoperability, modularity and decentralization
  • remote monitoring and control
  • real-time supply chain optimization
  • digital quality management

Published Papers (1 paper)

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Research

Article
Multi-Objective Design Optimization of Flexible Manufacturing Systems Using Design of Simulation Experiments: A Comparative Study
Machines 2022, 10(4), 247; https://doi.org/10.3390/machines10040247 - 30 Mar 2022
Viewed by 555
Abstract
One of the basic components of Industry 4.0 is the design of a flexible manufacturing system (FMS), which involves the choice of parameters to optimize its performance. Discrete event simulation (DES) models allow the user to understand the operation of dynamic and stochastic [...] Read more.
One of the basic components of Industry 4.0 is the design of a flexible manufacturing system (FMS), which involves the choice of parameters to optimize its performance. Discrete event simulation (DES) models allow the user to understand the operation of dynamic and stochastic system performance and to support FMS diagnostics and design. In combination with DES models, optimization methods are often used to search for the optimal designs, which, above all, involve more than one objective function to be optimized simultaneously. These methods are called the multi-objective simulation–optimization (MOSO) method. Numerous MOSO methods have been developed in the literature, which spawned many proposed MOSO methods classifications. However, the performance of these methods is not guaranteed because there is an absence of comparative studies. Moreover, previous classifications have been focused on general MOSO methods and rarely related to the specific area of manufacturing design. For this reason, a new conceptual classification of MOSO used in FMS design is proposed. After that, four MOSO methods are selected, according to this classification, and compared through a detailed case study related to the FMS design problem. All of these methods studied are based on Design of Experiments (DoE). Two of them are metamodel-based approaches that integrate Goal Programming (GP) and Desirability Function (DF), respectively. The other two methods are not metamodel-based approaches, which integrate Gray Relational Analysis (GRA) and the VIKOR method, respectively. The comparative results show that the GP and VIKOR methods can result in better optimization than DF and GRA methods. Thus, the use of the simulation metamodel cannot prove its superiority in all situations. Full article
(This article belongs to the Special Issue Design and Manufacturing: An Industry 4.0 Perspective)
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