Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0
With the deployment of data-driven assembly and production factories, challenges arise in sensor data acquisition and gathering. Different wireless technologies are currently used for transferring data, each with different advantages and constraints. In this paper, we present a hybrid network archit...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-11-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/23/11248 |
| _version_ | 1827675122988744704 |
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| author | Brecht De Beelde David Plets Wout Joseph |
| author_facet | Brecht De Beelde David Plets Wout Joseph |
| author_sort | Brecht De Beelde |
| collection | DOAJ |
| description | With the deployment of data-driven assembly and production factories, challenges arise in sensor data acquisition and gathering. Different wireless technologies are currently used for transferring data, each with different advantages and constraints. In this paper, we present a hybrid network architecture for providing Quality of Service (QoS) in an industrial environment where guaranteed minimal data rates and maximal latency are of utmost importance for controlling devices and processes. The location of the access points (APs) is determined during the initial network-planning action, together with physical parameters such as frequency, transmit power, and modulation and coding schemes. Instead of performing network-planning just once before the network rollout, the network is monitored continuously by adding telemetry data to the frame header of all data streams, and the network is automatically reconfigured in real-time if the requirements are not met. By not using maximum transmit powers during the initial roll-out, more APs are needed, but coverage is guaranteed when new obstructions such as metallic racks or machinery are added. It is found that decreasing the transmit power by 6 dB gives the best trade-off between the number of required APs and network robustness. The proposed architecture is validated via simulations and via a proof-of-concept setup. |
| first_indexed | 2024-03-10T04:57:43Z |
| format | Article |
| id | doaj.art-ecc3b1e2f4f44349bc70866414a6dc69 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T04:57:43Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-ecc3b1e2f4f44349bc70866414a6dc692023-11-23T02:04:59ZengMDPI AGApplied Sciences2076-34172021-11-0111231124810.3390/app112311248Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0Brecht De Beelde0David Plets1Wout Joseph2Department of Information Technology, Ghent University/IMEC, 9052 Ghent, BelgiumDepartment of Information Technology, Ghent University/IMEC, 9052 Ghent, BelgiumDepartment of Information Technology, Ghent University/IMEC, 9052 Ghent, BelgiumWith the deployment of data-driven assembly and production factories, challenges arise in sensor data acquisition and gathering. Different wireless technologies are currently used for transferring data, each with different advantages and constraints. In this paper, we present a hybrid network architecture for providing Quality of Service (QoS) in an industrial environment where guaranteed minimal data rates and maximal latency are of utmost importance for controlling devices and processes. The location of the access points (APs) is determined during the initial network-planning action, together with physical parameters such as frequency, transmit power, and modulation and coding schemes. Instead of performing network-planning just once before the network rollout, the network is monitored continuously by adding telemetry data to the frame header of all data streams, and the network is automatically reconfigured in real-time if the requirements are not met. By not using maximum transmit powers during the initial roll-out, more APs are needed, but coverage is guaranteed when new obstructions such as metallic racks or machinery are added. It is found that decreasing the transmit power by 6 dB gives the best trade-off between the number of required APs and network robustness. The proposed architecture is validated via simulations and via a proof-of-concept setup.https://www.mdpi.com/2076-3417/11/23/11248network-planningsensor networkswireless communicationIIoTPHY layerMAC layer |
| spellingShingle | Brecht De Beelde David Plets Wout Joseph Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0 Applied Sciences network-planning sensor networks wireless communication IIoT PHY layer MAC layer |
| title | Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0 |
| title_full | Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0 |
| title_fullStr | Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0 |
| title_full_unstemmed | Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0 |
| title_short | Wireless Sensor Networks for Enabling Smart Production Lines in Industry 4.0 |
| title_sort | wireless sensor networks for enabling smart production lines in industry 4 0 |
| topic | network-planning sensor networks wireless communication IIoT PHY layer MAC layer |
| url | https://www.mdpi.com/2076-3417/11/23/11248 |
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