CBI4.0: A Cross-Layer Approach for Big Data Gathering for Active Monitoring and Maintenance in the Manufacturing Industry 4.0

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Date

2021, 2021

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Volume Title

Publisher

Elsevier

Open Access Color

Green Open Access

No

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No
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Top 10%
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Top 10%
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Top 10%

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Abstract

Industry 4.0 (I4.0) defines a new paradigm to produce high-quality products at the low cost by reacting quickly and effectively to changing demands in the highly volatile global markets. In Industry 4.0, the adoption of Internet of Things (IoT)-enabled Wireless Sensors (WSs) in the manufacturing processes, such as equipment, machining, assembly, material handling, inspection, etc., generates a huge volume of data known as Industrial Big Data (IBD). However, the reliable and efficient gathering and transmission of this big data from the source sensors to the floor inspection system for the real-time monitoring of unexpected changes in the production and quality control processes is the biggest challenge for Industrial Wireless Sensor Networks (IWSNs). This is because of the harsh nature of the indoor industrial environment that causes high noise, signal fading, multipath effects, heat and electromagnetic interference, which reduces the transmission quality and trigger errors in the IWSNs. Therefore, this paper proposes a novel cross-layer data gathering approach called CBI4.0 for active monitoring and control of manufacturing processes in the Industry 4.0. The key aim of the proposed CBI4.0 scheme is to exploit the multi-channel and multi-radio architecture of the sensor network to guarantee quality of service (QoS) requirements, such as higher data rates, throughput, and low packet loss, corrupted packets, and latency by dynamically switching between different frequency bands in the Multichannel Wireless Sensor Networks (MWSNs). By performing several simulation experiments through EstiNet 9.0 simulator, the performance of the proposed CBI4.0 scheme is compared against existing studies in the automobile Industry 4.0. The experimental outcomes show that the proposed scheme outperforms existing schemes and is suitable for effective control and monitoring of various events in the automobile Industry 4.0.

Description

Phd, Muhammad Faheem,/0000-0003-4628-4486; Raza, Basit/0000-0001-6711-2363; Butt, Rizwan Aslam/0000-0002-4784-0918

Keywords

Internet of Things, Industry 4.0, Big Data, Multi-Channel Communication, Wireless Sensor Network, 670, QA75 Electronic computers. Computer science

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Citation

WoS Q

Q1

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Q1
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OpenCitations Citation Count
34

Source

Journal of Industrial Information Integration

Volume

24

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CrossRef : 33

Scopus : 48

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Mendeley Readers : 95

SCOPUS™ Citations

52

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Web of Science™ Citations

43

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Page Views

382

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10

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Sustainable Development Goals

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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