Industrial Analytics to Discover Knowledge from Instrumented Networked Machines

Computer technologies, sensor technologies, fiber optics, high-performance network technologies, mobile devices, wireless sensor networks, and powerful data repositories have permeated all layers of industry and opened the door for unprecedented data analytic capabilities used to improve equipment operation, equipment design, process quality, and product quality. Powerful and inexpensive sensors can continuously collect data about industrial equipment operations and industrial processes. Human operators and maintenance workers also utilize mobile devices to carry out their work collecting and transmitting enormous amounts of data related to the industrial activity. This paper presents the concept of Industrial Analytics which provides a framework for analyzing industrial data to discover valuable knowledge of the industrial activity that can help make decisions related to equipment design, predictive maintenance, process optimization, remote services, and product quality. The paper also presents an Industrial Analytics example applied to instrumented and networked electro-mechanical devices conducting their work in industrial environments. Keywords-industrial analytics; sensors; machine learning; data repositories; networked electro-mechanical devices; knowledge discovery.