Abstract:
In recent years, Industry 4.0 and Industrial Internet of Things have provided a strong enabling toolset to the reliability efforts of various industries. An important asp...Show MoreMetadata
Abstract:
In recent years, Industry 4.0 and Industrial Internet of Things have provided a strong enabling toolset to the reliability efforts of various industries. An important aspect in these efforts is the acquisition of relevant data from various parts of a plant facility, transmitting it to a remotely-located central server in real time, contextually analyzing this data, and making it ubiquitous and readily available to authorized users for decentralized and efficient decision making for corrective action. While there are numerous ways to achieve data transmission via wired sensors and devices, the implementation is challenging in mobile assets, such as overhead cranes. Measurement and transmission devices are often installed in locations difficult to approach, and the sensor wiring is susceptible to moving members and exposure to hot and corrosive environment. This makes it difficult to ensure overall Reliability. For the same reasons, transmission of acquired data to the remote server is also impractical using wired communication in mobile assets. In this paper, we present two wireless configurations for data telemetry in mobile assets, such as overhead cranes, for the purpose of Remote Monitoring and Intelligent Predictive Diagnostics of critical systems. In the presented implementations, we acquire data from wireless sensors, meant to be installed on such mobile assets, and transmit this data wirelessly to a remotely-located cloud server for analysis, and for making the analyzed data readily and universally available to authorized users. The first configuration uses an existing wireless internet network for data transmission to the server, and the second uses a 4G LTE cellular network. Using a workshop simulation and test setup, we demonstrate the successful implementation of these configurations.
Published in: 2020 IEEE Midwest Industry Conference (MIC)
Date of Conference: 07-08 August 2020
Date Added to IEEE Xplore: 30 September 2020
ISBN Information: