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.

工业 4.0 (I4.0) 定义了一种新范式，通过快速有效地应对高度动荡的全球市场不断变化的需求，以低成本生产高质量产品。在工业 4.0 中，在设备、加工、装配、材料处理、检查等制造过程中采用支持物联网 (IoT) 的无线传感器 (WS)，会产生大量数据，称为工业数据。大数据 (IBD)。然而，将这些大数据从源传感器可靠、高效地收集和传输到地板检测系统，以实时监控生产和质量控制过程中的意外变化，这是工业无线传感器网络 (IWSN) 面临的最大挑战. 这是因为室内工业环境的恶劣性质会导致高噪音，信号衰落、多径效应、热量和电磁干扰，这会降低 IWSN 中的传输质量和触发错误。因此，本文提出了一种称为 CBI4.0 的新型跨层数据收集方法，用于对工业 4.0 中的制造过程进行主动监控。提议的 CBI4.0 方案的主要目标是利用传感器网络的多通道和多无线电架构来保证服务质量 (QoS) 要求，例如更高的数据速率、吞吐量和低丢包率、损坏通过在多通道无线传感器网络 (MWSN) 中的不同频段之间动态切换来减少数据包和延迟。通过通过 EstiNet 9.0 模拟器进行多次模拟实验，所提出的 CBI4.0 的性能。0 方案与汽车工业 4.0 中的现有研究进行了比较。实验结果表明，所提出的方案优于现有方案，适用于汽车工业4.0中各种事件的有效控制和监测。