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Oracle announced this week that it will expand the scope of automated learning algorithms and related artificial intelligence applications in manufacturing.
“Oracle Application Intelligent Applications for Manufacturing will use automated learning and AI to handle massive amounts of data to identify problems before they happen, while also improving overall operational efficiency,”
Oracle has already developed 150 key performance indicators for manufacturing companies that will serve as a baseline that will analyze manufacturing processes using automated learning algorithms and artificial intelligence Oracle Consulting Services Training Development Developer Official Support Partner Services Company Solution in Doha Al Rayyan Qatar models. Over time, customers will be able to add their own KPIs, machine learning algorithms, and artificial intelligence models.
Oracle Adaptive Intelligent Analytics
Specifically, Oracle Adaptive Intelligent Analytics for Manufacturing identifies patterns and links across variables. Users align these ideas with manufacturing business metrics such as productivity, quality, cycle time, cost, scrap, rework, and revenue to identify the root causes of problems. Then learning automatic learning models and AI predictive analytical Microsoft Power BI Consulting Services Training Development Developer Official Support Partner Services Company Solution in Doha Al Rayyan Qatar above all data collected to determine yield, Defects, scrap, rework, cycle time, and costs associated with certain operations. Instead of relying on the person to prepare a search query to discover that information, the models of artificial intelligence will be presented automatically. There is also a smart memory analysis tool to provide product tracking forward and backward to identify products, services, and customers that may be affected by a particular problem.
Oracle’s intelligent adaptation applications for manufacturing will be consumed primarily as SaaS software. But will also provide versions that can be deployed locally.
key Advantages
The key advantage of this approach is that industrial companies can start using automated learning algorithms and artificial intelligence SAP Consulting Services Training Development Developer Official Support Partner Services Company Solution in Doha Al Rayyan Qatar models immediately against spending three to four years in an effort to build an equivalent capacity on their own.
Because manufacturing depends heavily on a specified number of variables, it makes an ideal application of AI to structured, semi-structured and unstructured data. The problem in analyzing this data is to find a way to focus it in a repository, which results in the creation of a large set of data sufficient to implement automated learning algorithms.
It remains to be seen what exactly will have an impact on the quality of manufacturing and the number of people required to build anything. Most of the analyzes provided by AI models today are not presented because there is not enough data in a central place to analyze, let alone find data from scientists who can understand them. But as AI continues to expand, it is already clear that manufacturing at any level will not be repeated soon.
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