Open-Access AI Platform for IoT Condition Monitoring

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Industrial bearing and power transmission component distributors are the direct contact of industrial clients in need of components and services related to industrial machine maintenance and retrofit, or in emergencies when machine breakdowns occur. Their experience provides invaluable insight that ensures machine uptime and maximum profit for their industrial clients. However, the traditional service model that these distributors have relied on is quickly being upended by new technologies. Intelligent machine condition monitoring technology is on the cusp of revolutionizing the way maintenance engineers ensure the uptime of their equipment. Unfortunately, this technology currently resides in the hands of premium service providers and is currently only viable for the largest of companies.General Bearing Service (GBS), in partnership with the Advanced Dynamics Design Lab (ADDL) at the University of Ottawa, intends to bring the latest advances in machine condition monitoring to Canadian small and mid-size enterprises (SMEs) that rely on GBS to help them ensure a consistent and predictable production cash flow. To do so, GBS intends to offer AI-based machine condition monitoring systems to clients and provide maintenance contracts that guarantee uptime and improved process efficiency. To achieve this, GBS will work closely with the ADDL to create a cloud database populated with IoT multi-sensor data from industry containing machine fault data captured using a data fusion schema, as well as develop and improve computationally efficient deep machine learning algorithms for machine health prognostics.This partnership will provide GBS the required technological resources and expertise to modernize their industry and provide the much-needed value-added services required by their clients to remain competitive. This partnership will also provide the ADDL with in-depth insight into the industry required to advance research in this field of study, test innovative solutions, and train highly qualified personnel.