IMPROVING AGV DEPENDABILITY: A CLOUD-BASED SYSTEM FOR FAULT DIAGNOSIS DATA COLLECTION - Richter, Anna (Ayden International Journal of Basic and Applied Sciences, 2024)
In recent years, fault diagnosis technology has witnessed substantial growth in its application within factories, significantly enhancing production efficiency and safety by reducing the incidence of accidents. As the manufacturing industry in China experiences continuous advancements, the adoption of Automated Guided Vehicles (AGVs) has become increasingly widespread. AGV logistics transportation systems serve as vital components in the production processes of various enterprises. The failure of AGV vehicles can result in a severe reduction in production efficiency and pose potential risks to personnel safety. Hence, the integration of remote fault diagnosis technology into AGV vehicles is an imperative trend [1]. Given the dynamic nature of AGV car movements, the method of remote data transmission is limited to wireless transmission. Compared to traditional wired data storage for fault diagnosis, a wireless data transmission-based system demands higher data transmission rates and storage requirements. This paper introduces a novel cloud platform-based design for an AGV fault diagnosis data acquisition system. This system aims to enhance AGV fault diagnosis by leveraging the capabilities of cloud technology, ensuring efficient data transmission and storage to maintain the reliability and performance of AGV logistics transportation systems.