Wireless Industrial Automation Research Articles

Design and implementation of a wireless CAN module for marine engines using ZigBee protocol

AbstractThis paper describes the design and implementation of a wireless control area network (CAN bus) protocol for communication between the smart NOx (nitrogen oxide) sensor on diesel engines and the engine control unit (ECU). In this research, the approach taken is based on a case study of Wärtsilä's smart NOx sensor on a W4L20 diesel engine with the objective of replacing the wired CAN protocol with a wireless CAN communication node. In the current setup, the smart NOx sensor is connected to the engine control unit (ECU) with a wired CAN bus connection. The XBee module, which uses the ZigBee (IEEE 802.15.4) technology was used in the design and implementation of the wireless CAN prototype. With the emergence of 5G networks and the era of IoT, the topic of wireless industrial automation becomes essential in the modern industry. In addition to the great advantages and opportunities that the use of wireless nodes has in automation systems, there are many real challenges. The practical design challenges have been addressed in this paper.

Time-Critical IoT Applications Enabled by Wi-Fi 6 and Beyond

Wireless Industry 4.0 applications typically have stringent latency and reliability requirements. Even though state-of-the-art Wi-Fi networks can reliably achieve single digit milliseconds latency, new emerging time-critical applications have requirements that current Wi-Fi cannot meet. In this paper, we present next generation Wi-Fi technologies and describe how they can be leveraged to enable three time-critical Industry 4.0 use cases: wireless industrial automation control, remote rendering in extended reality applications and cooperative simultaneous localization and mapping using autonomous mobile robots in a factory plant.

ARM Microcontroller Based Wireless Industrial Automation System

In modern era most of the work being completed by the new and advanced various technology. Most of the industries are being run on the robotics technologies. But in INDIA most of the company are running in various technologies as like embedded system, plc, Arduino for sensing the alcohol detection and gas detection system and most important thing microcontroller. In this paper we discuss the ARM microcontroller based wireless industrial automation system. This automation consists the coordinator module and sensor module. In which one module is connected with the monitoring computer that is called the coordinator module and for connecting with the monitor of the computer it is also called the centralized unit. And the sensor module is an ARM microcontroller for a monitoring and controlling the whole plant. The coordinator unit main work is to collects the all type of data from the sensor module and provide that information to the IP network. For better communication between these two modules, we use the best technology is ZIGBEE technology. Its main work to preset the changing and control the plant various parameter. ARM microcontroller using the embedded c language coding. This paper we do the deeply study about the ARM microcontroller and about the wireless industrial automation system and the term of ZIGBEE technology.

ARM Microcontroller Based Wireless Industrial Automation System

In modern era most of the work being completed by the new and advanced various technology. Most of the industries are being run on the robotics technologies. But in INDIA most of the company are running in various technologies as like embedded system, plc, Arduino for sensing the alcohol detection and gas detection system and most important thing microcontroller. In this paper we discuss the ARM microcontroller based wireless industrial automation system. This automation consists the coordinator module and sensor module. In which one module is connected with the monitoring computer that is called the coordinator module and for connecting with the monitor of the computer it is also called the centralized unit. And the sensor module is an ARM microcontroller for a monitoring and controlling the whole plant. The coordinator unit main work is to collects the all type of data from the sensor module and provide that information to the IP network. For better communication between these two modules, we use the best technology is ZIGBEE technology. Its main work to preset the changing and control the plant various parameter. ARM microcontroller using the embedded c language coding. This paper we do the deeply study about the ARM microcontroller and about the wireless industrial automation system and the term of ZIGBEE technology.

Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems

Many industrial automation systems rely on time-synchronized (and timely) communication among sensing, computing, and actuating devices. Advances in Ethernet enabled by time-sensitive networking (TSN) standards, being developed by the IEEE 802.1 TSN Task Group, are significantly improving time synchronization as well as worst case latencies. Next-generation industrial systems are expected to leverage advances in distributed time coordinated computing and wireless communications to enable greater levels of automation, efficiency, and flexibility. Significant progress has been made in extending accurate time synchronization over the air (e.g., 802.1AS profile for IEEE 802.11/Wi-Fi). Given the inherently unreliable, varying capacity and latency prone characteristics associated with wireless communications, proving the feasibility of worst case latency performance over the wireless medium is a major research challenge. More specifically, understanding what levels of capacity, reliability, and latency could be guaranteed over wireless links with high reliability are important research questions to guide the development of new radios, protocols, and time coordinated applications. This paper provides an overview of the potential applications, requirements, and unique research challenges to extend TSN capabilities over wireless. The paper also describes advances in wireless technologies (e.g., next-generation 802.11 and 5G standards) toward achieving reliable and accurate time distribution and timeliness capabilities. It also provides a classification of wireless applications and a reference architecture for enabling the integration of wired and wireless TSN capabilities in future industrial automation systems.

Channel measurement campaigns for wireless industrial automation

Abstract The factories of the future will be highly digitalized in order to enable flexible and interconnected manufacturing processes. Especially wireless technologies will be beneficial for industrial automation. However, the high density of metallic objects is challenging for wireless systems due to multipath fading. In order to understand the signal propagation in industrial environments, this paper provides results from a number of channel measurement campaigns funded by the German research initiative “Reliable wireless communication in the industry”. We give an overview of different measurement scenarios covering visible light communication and radio communication below 6 GHz. We analyze large and small scale parameters as well as delay statistics of the wireless channels. Finally, we discuss the importance of the results for the definition of industrial channel models.

Energy Efficient Data Transmission Approaches for Wireless Industrial Automation

Background: The industrial wireless automation system enables the monitoring and control of processes. It may be difficult to recharge the battery of sensors installed in harmful environments. Hence optimization of the power is the major issue to be addressed while implementing the network. The proposed hybrid data transmission approaches optimize data accuracy and energy efficiency of a wireless sensor node deployed in any industry. Methods: In the time-driven method, the sensor nodes periodically sense the environment and transmit the data continuously over time. In the event-driven method, the sensor nodes transmit data only when there is a drastic change in the occurrence of a certain event. Results: Based on the nature of the process, applications are classified as, less critical, critical and most critical. The time-driven based hybrid transmission approach is suggested for the most critical applications because they need to be monitored continuously so as to attain data accuracy. In the case of critical applications, the data is not required to be sent continuously, but instead it can be sampled and transmitted once in two seconds. Though the above suggested methods intended to provide better outcomes in terms of power utilization, in the case of process control applications, most critical and critical applications need to be monitored continuously. Hence such applications could be done as a heterogeneous industrial automation network, which is the combination of wired and wireless connectivity. This can be implemented by replacing all the signal cables with wireless communication system, regular power supply must be provided for the radio module attached with final control elements and also to the transmitters involved in most critical applications. For the least critical applications, the data can be sampled and transmitted once in four seconds. Conclusion: Simulation has been performed for time-driven based and duty-cycling based hybrid transmission approaches. The results can guide process engineers in selecting the transmission approach for optimizing the power of IWAS based on the critical level of the process. In the case of a critical process, the time-driven based hybrid transmission approach may be used, and in the case of a less critical process, the duty-cycling based hybrid transmission approach could be selected. By selecting appropriate transmission approach the life time of IWAS could be improved. Keywords: Controllers, process control, transceivers, transmitters, temperature sensors, wireless sensor networks.

A D2D-Based Protocol for Ultra-Reliable Wireless Communications for Industrial Automation

As one indispensable use case for the 5G wireless systems on the roadmap, ultra-reliable and low latency communications (URLLC) is a crucial requirement for the coming era of wireless industrial automation. This paper aims to develop communication techniques for making such a paradigm shift from the conventional human-type broadband communications to the emerging machine-type URLLC. One fundamental task for URLLC is to deliver a short command from the controller to each actuator within the stringent delay requirement and also with high-reliability in the downlink. Motivated by the geographic feature in industrial automation that in the factories many tasks are assigned to different groups of devices who work in close proximity to each other and thus can form clusters of reliable device-to-device (D2D) networks, this paper proposes a novel two-phase transmission protocol for achieving the above goal. Specifically, in the first phase within the latency requirement, the multi-antenna base station (BS) combines the messages of each group together and multicasts them to the corresponding groups; while in the second phase, the devices that have decoded the messages successfully, who are defined as the leaders, help relay the messages to the other devices in their groups. Under this protocol, we further design an innovative leader selection based beamforming strategy at the BS by utilizing the sparse optimization technique, which leads to the desired sparsity pattern in user activity, i.e., at least one leader exists in each group, in the first phase, thus making full utilization of the reliable D2D networks in the second phase. Simulation results are provided to show that the proposed two-phase transmission protocol considerably improves the reliability of the whole system within the stringent latency requirement as compared to other existing schemes for URLLC such as Occupy CoW.

D-MSR: A Distributed Network Management Scheme for Real-Time Monitoring and Process Control Applications in Wireless Industrial Automation

Current wireless technologies for industrial applications, such as WirelessHART and ISA100.11a, use a centralized management approach where a central network manager handles the requirements of the static network. However, such a centralized approach has several drawbacks. For example, it cannot cope with dynamicity/disturbance in large-scale networks in a real-time manner and it incurs a high communication overhead and latency for exchanging management traffic. In this paper, we therefore propose a distributed network management scheme, D-MSR. It enables the network devices to join the network, schedule their communications, establish end-to-end connections by reserving the communication resources for addressing real-time requirements, and cope with network dynamicity (e.g., node/edge failures) in a distributed manner. According to our knowledge, this is the first distributed management scheme based on IEEE 802.15.4e standard, which guides the nodes in different phases from joining until publishing their sensor data in the network. We demonstrate via simulation that D-MSR can address real-time and reliable communication as well as the high throughput requirements of industrial automation wireless networks, while also achieving higher efficiency in network management than WirelessHART, in terms of delay and overhead.