[vc_row][vc_column][rev_slider_vc alias=”data-science-methodology”][/vc_column][/vc_row][vc_row css=”.vc_custom_1557437085104{margin-top: 6.3% !important;margin-right: 8.5% !important;margin-bottom: 1% !important;margin-left: 8.5% !important;}”][vc_column width=”1/6″][/vc_column][vc_column width=”2/3″][vc_column_text]
Getting Data Science to Deliver Results for You using ei3’s Proven Methodology
[/vc_column_text][vc_column_text]
- We analyze available data to create a mathematical model of the machine or process we wish to make predictions over. Using our tools, this model – commonly often called “digital twin”, can be created in a semi-automatic fashion based on historic data from the machine itself, or engineering insight into its operations.
- Deviations from that model are analyzed and enriched using semantic information; this process is often called “tagging”. Based on this exercise which combines analytics with the engineering insights into your machine, deviations can be interpreted in terms of machine anomalies, impending failures, or wear-and-tear events.
- Finally, model and tags are translated into a predictive algorithm that is run continuously on real-time data, creating alerts to the right users, or events in a back-end system, as appropriate to any detected data anomaly.
Interested in hearing outcomes from the application of AI algorithms in real production environments?
[/vc_column_text][ult_buttons btn_title=”Schedule a demo” btn_link=”url:https%3A%2F%2Fei3.com%2Fschedule-a-demo%2F||target:%20_blank|” btn_align=”ubtn-center” btn_size=”ubtn-custom” btn_width=”250″ btn_height=”45″ btn_title_color=”#ffffff” btn_bg_color=”#0651a0″ btn_bg_color_hover=”#0651a0″ btn_title_color_hover=”#ffffff” icon=”Defaults-arrow-right” icon_size=”18″ icon_color=”#ffffff” btn_icon_pos=”ubtn-sep-icon-at-right” btn_font_style=”font-weight:bold;” btn_font_size=”desktop:18px;”][/vc_column][vc_column width=”1/6″][/vc_column][/vc_row]