Interoperability in Smart Manufacturing: Research Challenges
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 th...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-04-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/7/2/21 |
| _version_ | 1818836577985495040 |
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| author | Abe Zeid Sarvesh Sundaram Mohsen Moghaddam Sagar Kamarthi Tucker Marion |
| author_facet | Abe Zeid Sarvesh Sundaram Mohsen Moghaddam Sagar Kamarthi Tucker Marion |
| author_sort | Abe Zeid |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-19T03:08:50Z |
| format | Article |
| id | doaj.art-c8570ba2b3fe4dc0829ca0492aaf54ab |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-12-19T03:08:50Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-c8570ba2b3fe4dc0829ca0492aaf54ab2022-12-21T20:38:04ZengMDPI AGMachines2075-17022019-04-01722110.3390/machines7020021machines7020021Interoperability in Smart Manufacturing: Research ChallengesAbe Zeid0Sarvesh Sundaram1Mohsen Moghaddam2Sagar Kamarthi3Tucker Marion4Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USADepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USADepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USADepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USADepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USARecent 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.https://www.mdpi.com/2075-1702/7/2/21Industry 4.0smart manufacturingcyber–physical systemsInternet of thingsinteroperability |
| spellingShingle | Abe Zeid Sarvesh Sundaram Mohsen Moghaddam Sagar Kamarthi Tucker Marion Interoperability in Smart Manufacturing: Research Challenges Machines Industry 4.0 smart manufacturing cyber–physical systems Internet of things interoperability |
| title | Interoperability in Smart Manufacturing: Research Challenges |
| title_full | Interoperability in Smart Manufacturing: Research Challenges |
| title_fullStr | Interoperability in Smart Manufacturing: Research Challenges |
| title_full_unstemmed | Interoperability in Smart Manufacturing: Research Challenges |
| title_short | Interoperability in Smart Manufacturing: Research Challenges |
| title_sort | interoperability in smart manufacturing research challenges |
| topic | Industry 4.0 smart manufacturing cyber–physical systems Internet of things interoperability |
| url | https://www.mdpi.com/2075-1702/7/2/21 |
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