{"571221":{"#nid":"571221","#data":{"type":"news","title":"Data Driven","body":[{"value":"\u003Cp\u003EFrom \u003Cem\u003EResearch Horizon\u0027s\u003C\/em\u003E \u0022Data Driven\u0022 article:\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWith unprecedented amounts of data suddenly on tap, the challenge many researchers face is how to consume it.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFor example, inexpensive sensor technology has made it easy for power companies to collect data on critical high-value assets such as generators and turbines. Yet analytical technology has lagged behind, inhibiting their ability to make sense out of it, said \u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/nagi-gebraeel\u0022\u003ENagi Gebraeel\u003C\/a\u003E\u003C\/strong\u003E, Georgia Power associate professor in Georgia Tech\u2019s School of \u003Cstrong\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/\u0022\u003EIndustrial and Systems Engineering\u003C\/a\u003E\u003C\/strong\u003E (ISyE) and associate director of the Strategic Energy Institute.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn response, Gebraeel\u2019s research group is developing a new computational platform to provide detection and predictive analytics for the energy industry. This platform remotely assesses the health and performance of equipment in real time and monitors trends to determine such things as:\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EThe best time to perform maintenance.\u003C\/li\u003E\r\n\t\u003Cli\u003EWhen to order new parts so they don\u2019t linger in inventory, costing money and possibly becoming obsolete.\u003C\/li\u003E\r\n\t\u003Cli\u003EHow shutting down one piece of equipment will affect the entire network.\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n\r\n\u003Cp\u003E\u201cThe latter is especially important because any slack caused by shutting down one generator has to be picked up by the rest of the generators,\u201d Gebraeel said. \u201cNow their lifetime has to be re-evaluated because they are working in overload. That\u2019s where optimization and analytics intersect.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EBy integrating detection, prediction, and optimization capabilities, the new platform could help power companies achieve significant savings. Indeed, a preliminary study shows a 40 to 45 percent reduction in maintenance costs alone.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EIn the past, there\u2019s been a lot of unnecessary preventative maintenance, Gebraeel pointed out. \u201cCompanies do it because of safety, which is rational, but they are being too conservative because they don\u2019t have enough visibility into their assets.\u201d\u003C\/p\u003E\r\n\r\n\u003Cp\u003EKey to creating the computational platform is re-engineering older statistical algorithms that were developed in the context of limited data, Gebraeel said. Today\u2019s algorithms must be executed on processing platforms that can handle terabytes and petabytes of data, deployed across a large number of computer nodes.\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETo read the rest of the article, click here: \u003Ca href=\u0022http:\/\/www.rh.gatech.edu\/features\/data-driven\u0022\u003Ehttp:\/\/www.rh.gatech.edu\/features\/data-driven\u003C\/a\u003E.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EA highly interdisciplinary field that blends statistics, computing, algorithms, applied mathematics, and visualization, data science uses automated methods to gather and extract knowledge from very large or complex sets of data.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"A highly interdisciplinary field that blends statistics, computing, algorithms, applied mathematics, and visualization, data science uses automated methods to gather and extract knowledge from very large or complex sets of data."}],"uid":"28766","created_gmt":"2016-08-31 12:02:44","changed_gmt":"2016-10-08 03:22:30","author":"Shelley Wunder-Smith","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2016-08-31T00:00:00-04:00","iso_date":"2016-08-31T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"571211":{"id":"571211","type":"image","title":"Nagi Gebraeel is analyzing large volumes of sensor data from electric power generation equipment to find information that could improve reliability and reduce maintenance costs.","body":null,"created":"1472659026","gmt_created":"2016-08-31 15:57:06","changed":"1475895379","gmt_changed":"2016-10-08 02:56:19","alt":"Nagi Gebraeel is analyzing large volumes of sensor data from electric power generation equipment to find information that could improve reliability and reduce maintenance costs.","file":{"fid":"207091","name":"data_portrait_003.jpg","image_path":"\/sites\/default\/files\/images\/data_portrait_003.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/data_portrait_003.jpg","mime":"image\/jpeg","size":389514,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/data_portrait_003.jpg?itok=8oMqJaCa"}}},"media_ids":["571211"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[{"id":"145","name":"Engineering"}],"keywords":[{"id":"15092","name":"big data"},{"id":"213","name":"energy"},{"id":"426","name":"isye"},{"id":"7930","name":"Nagi Gabraeel"}],"core_research_areas":[{"id":"39431","name":"Data Engineering and Science"},{"id":"39541","name":"Systems"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}