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Machines
Special Issues
Smart Manufacturing, Digital Supply Chains and Industry 4.0
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Smart Manufacturing, Digital Supply Chains and Industry 4.0

A special issue of Machines (ISSN 2075-1702).

Deadline for manuscript submissions: closed (30 September 2018) | Viewed by 84185

Special Issue Information

Dear Colleagues,

Smart manufacturing, Digital Supply Chains and Industry 4.0 shape the transformation of industrial engineering, production and supply chain management. Smart operations and digital supply chains can be considered from different points of view which imply an integration of industrial engineering, business informatics, management, and operations research competencies.

The aim of this Special Issue is to bring together researchers and practitioners in industrial engineering, manufacturing systems, operations research, supply chain management, and business informatics to present and discuss emerging topics in modern manufacturing modeling, management, and control. The Special Issue will cover all topics related to design, implementation and operation of modern manufacturing and supply chain systems in digitalization era, including (but not limited to) the following:

  • Design and reconfiguration of smart manufacturing systems
  • Intelligent facility planning and materials handling
  • Industry 4.0
  • Smart logistics
  • Adaptive manufacturing systems
  • Additive manufacturing
  • Augmented reality
  • Virtual reality
  • Digital manufacturing networks and smart operations
  • Big Data and business analytics for manufacturing and supply chain systems
  • Enterprise modelling, integration and networking
  • Intelligent modeling, simulation, control and monitoring of manufacturing processes
  • Robotics in manufacturing
  • Intelligent manufacturing systems
  • Intelligent transportation
  • Service oriented architecture for production management and control
  • Complex adaptive systems and emergent synthesis in manufacturing
  • Web-enabled manufacturing control and wireless automation
  • Design for reusability
  • Maintainability, reliability, safety and dependability of production systems
  • Quality management
  • Virtual reality
  • Sensor networks, ubiquitous computing, active identifiers, wireless communication in manufacturing
  • Distributed systems and multi-agents technologies
  • Simulation technologies

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
  • Digital Supply Chain
  • Simulation
  • Smart Logistics
  • Adaptive Manufacturing Systems
  • Big Data and Business Analytics
  • Smart Manufacturing Systems
  • Robotics
  • Additive Manufacturing
  • Sensors
  • Augmented Reality

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

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Research

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12 pages, 1220 KiB  
Article
Applications of Big Data analytics and Related Technologies in Maintenance—Literature-Based Research
by Jens Baum, Christoph Laroque, Benjamin Oeser, Anders Skoogh and Mukund Subramaniyan
Machines 2018, 6(4), 54; https://doi.org/10.3390/machines6040054 - 1 Nov 2018
Cited by 20 | Viewed by 7772
Abstract
Digitalisation is argued to increase the efficiency of maintenance activities in a production system. One consequence of digitalisation is data deluge; this allows data analytics methods and technologies to be used. However, the actual data analytical methods and technologies used may differ, thus [...] Read more.
Digitalisation is argued to increase the efficiency of maintenance activities in a production system. One consequence of digitalisation is data deluge; this allows data analytics methods and technologies to be used. However, the actual data analytical methods and technologies used may differ, thus leading to many scientific papers on this topic. The purpose of our contribution is to find and cluster scientific papers regarding the implemented approaches relevant for use in production maintenance. Our research is based on a broad, systematic literature review consisting of a two-step search approach combined with additional filtering and classification. Based on the search results, we evaluate and visualise the potential impact of data analytics on the subject of maintenance. The results of this study broadly summarise the research activities in production maintenance, whilst indicating that the impact of data analytics will grow further. Specific methodological approaches are clearly favored. Full article
(This article belongs to the Special Issue Smart Manufacturing, Digital Supply Chains and Industry 4.0)
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22 pages, 1799 KiB  
Article
Using Sensor-Based Quality Data in Automotive Supply Chains
by Michael Teucke, Eike Broda, Axel Börold and Michael Freitag
Machines 2018, 6(4), 53; https://doi.org/10.3390/machines6040053 - 1 Nov 2018
Cited by 20 | Viewed by 6827
Abstract
In many current supply chains, transport processes are not yet being monitored concerning how they influence product quality. Sensor technologies combined with telematics and digital services allow for collecting environmental data to supervise these processes in near real-time. This article outlines an approach [...] Read more.
In many current supply chains, transport processes are not yet being monitored concerning how they influence product quality. Sensor technologies combined with telematics and digital services allow for collecting environmental data to supervise these processes in near real-time. This article outlines an approach for integrating sensor-based quality data into supply chain event management (SCEM). The article describes relationships between environmental conditions and quality defects of automotive products and their mutual relations to sensor data. A discrete-event simulation shows that the use of sensor data in an event-driven control of material flows can keep inventory levels more stable. In conclusion, sensor data can improve quality monitoring in transport processes within automotive supply chains. Full article
(This article belongs to the Special Issue Smart Manufacturing, Digital Supply Chains and Industry 4.0)
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16 pages, 242 KiB  
Article
On the Regulatory Framework for Last-Mile Delivery Robots
by Thomas Hoffmann and Gunnar Prause
Machines 2018, 6(3), 33; https://doi.org/10.3390/machines6030033 - 1 Aug 2018
Cited by 107 | Viewed by 17125
Abstract
Autonomously driving delivery robots are developed all around the world, and the first prototypes are tested already in last-mile deliveries of packages. Estonia plays a leading role in this field with its, start-up Starship Technologies, which operates not only in Estonia but also [...] Read more.
Autonomously driving delivery robots are developed all around the world, and the first prototypes are tested already in last-mile deliveries of packages. Estonia plays a leading role in this field with its, start-up Starship Technologies, which operates not only in Estonia but also in foreign countries like Germany, Great Britain, and the United States of America (USA), where it seems to provide a promising solution of the last-mile problem. But the more and more frequent appearance of delivery robots in public traffic reveals shortcomings in the regulatory framework of the usage of these autonomous vehicles—despite the maturity of the underlying technology. The related regulatory questions are reaching from data protection over liability for torts performance to such mundane fields as traffic law, which a logistic service provider has to take into account. This paper analyses and further develops the regulatory framework of autonomous delivery robots for packages by highlighting legal implications. Since delivery robots can be understood as cyber-physical systems in the context of Industry 4.0, the research contributes to the related regulatory framework of Industry 4.0 in international terms. Finally, the paper discusses future perspectives and proposes specific modes of compliance. Full article
(This article belongs to the Special Issue Smart Manufacturing, Digital Supply Chains and Industry 4.0)
15 pages, 48956 KiB  
Article
UML-Based Cyber-Physical Production Systems on Low-Cost Devices under IEC-61499
by Carlos A. García, Exteban X. Castellanos and Marcelo V. García
Machines 2018, 6(2), 22; https://doi.org/10.3390/machines6020022 - 27 May 2018
Cited by 14 | Viewed by 6857
Abstract
Current industry must improve the day-to-day control and industrial communications of its processes in order to bring itself closer to the Industry 4.0 paradigm. To attain these improvements, which aim towards obtaining agile and intelligent manufacturing systems, the IEC-61499 standard is considered to [...] Read more.
Current industry must improve the day-to-day control and industrial communications of its processes in order to bring itself closer to the Industry 4.0 paradigm. To attain these improvements, which aim towards obtaining agile and intelligent manufacturing systems, the IEC-61499 standard is considered to be the main option by many researchers. Despite its benefits, its biggest drawback is the lack of software tools required for an effective design process for distributed control systems. The following work details the implementation of the IEC-61499 standard in low-cost devices using 4DIAC-FORTE for distributed control of a FESTO MPS 200 educational system, by using Unified Modeling Language (UML) diagrams as a software tool for modeling the function blocks (FBs) of the IEC-61499 standard. This work demonstrates a simple and easy way to create distributed systems. Full article
(This article belongs to the Special Issue Smart Manufacturing, Digital Supply Chains and Industry 4.0)
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Review

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17 pages, 2310 KiB  
Review
Interoperability in Smart Manufacturing: Research Challenges
by Abe Zeid, Sarvesh Sundaram, Mohsen Moghaddam, Sagar Kamarthi and Tucker Marion
Machines 2019, 7(2), 21; https://doi.org/10.3390/machines7020021 - 2 Apr 2019
Cited by 120 | Viewed by 14646
Abstract
Recent advances in manufacturing technology, such as cyber–physical systems, industrial Internet, AI (Artificial Intelligence), and machine learning have driven the evolution of manufacturing architectures into integrated networks of automation devices, services, and enterprises. One of the resulting challenges of this evolution is the [...] Read more.
Recent advances in manufacturing technology, such as cyber–physical systems, industrial Internet, AI (Artificial Intelligence), and machine learning have driven the evolution of manufacturing architectures into integrated networks of automation devices, services, and enterprises. One of the resulting challenges of this evolution is the increased need for interoperability at different levels of the manufacturing ecosystem. The scope ranges from shop–floor software, devices, and control systems to Internet-based cloud-platforms, providing various services on-demand. Successful implementation of interoperability in smart manufacturing would, thus, result in effective communication and error-prone data-exchange between machines, sensors, actuators, users, systems, and platforms. A significant challenge to this is the architecture and the platforms that are used by machines and software packages. A better understanding of the subject can be achieved by studying industry-specific communication protocols and their respective logical semantics. A review of research conducted in this area is provided in this article to gain perspective on the various dimensions and types of interoperability. This article provides a multi-faceted approach to the research area of interoperability by reviewing key concepts and existing research efforts in the domain, as well as by discussing challenges and solutions. Full article
(This article belongs to the Special Issue Smart Manufacturing, Digital Supply Chains and Industry 4.0)
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13 pages, 1834 KiB  
Review
A Bibliometric and Topic Analysis on Future Competences at Smart Factories
by Andrej Jerman, Mirjana Pejić Bach and Andrej Bertoncelj
Machines 2018, 6(3), 41; https://doi.org/10.3390/machines6030041 - 16 Sep 2018
Cited by 37 | Viewed by 5737
Abstract
The aim of the study is to review the topic of competences that will be present at smart factories. The study used bibliometric and topic analysis to achieve insight into new trends in Industry 4.0. Bibliometric analysis and topic mining was done on [...] Read more.
The aim of the study is to review the topic of competences that will be present at smart factories. The study used bibliometric and topic analysis to achieve insight into new trends in Industry 4.0. Bibliometric analysis and topic mining was done on 43 peer-reviewed journal articles and conference papers, published before July 2018 in the Thomson Reuters’ Web of Science and Scopus databases, using the software tool Statistica Data Miner. Results are segmented into four sections: (1) personnel development in learning organizations, (2) training techniques for personnel, (3) future engineering profiles and engineering education, and (4) relational capabilities. Each section is thoroughly discussed in this paper. The study contributes to the pool of knowledge on Industry 4.0 phenomena by compiling competences needed at smart factories in the future. Full article
(This article belongs to the Special Issue Smart Manufacturing, Digital Supply Chains and Industry 4.0)
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22 pages, 2519 KiB  
Review
Requirements of the Smart Factory System: A Survey and Perspective
by Mohammed M. Mabkhot, Abdulrahman M. Al-Ahmari, Bashir Salah and Hisham Alkhalefah
Machines 2018, 6(2), 23; https://doi.org/10.3390/machines6020023 - 1 Jun 2018
Cited by 220 | Viewed by 24120
Abstract
With the development of Industry 4.0 and the emergence of the smart factory concept, the traditional philosophy of manufacturing systems will change. The smart factory introduces changes to the factors and elements of traditional manufacturing systems and incorporates the current requirements of smart [...] Read more.
With the development of Industry 4.0 and the emergence of the smart factory concept, the traditional philosophy of manufacturing systems will change. The smart factory introduces changes to the factors and elements of traditional manufacturing systems and incorporates the current requirements of smart systems so that it can compete in the future. An increasing amount of research in both academia and industry is dedicated to transitioning the concept of the smart factory from theory to practice. The purpose of the current research is to highlight the perspectives that shape the smart factory and to suggest approaches and technical support to enable the realization of those perspectives. This paper fills this gap by identifying and analyzing research on smart factories. We suggest a framework to analyze existing research and investigate the elements and features of smart factory systems. Full article
(This article belongs to the Special Issue Smart Manufacturing, Digital Supply Chains and Industry 4.0)
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