Improve Operational Readiness with Machine Learning Based Prescriptive Maintenance

Leverage Disparate Data Sources to Develop Prescriptive Intelligence on Equipment Operation and Failure

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About the Solution Sheet

With the growth of smart sensor technologies, there is an expanding universe of Internet-of-Things generating a rich stream of data on equipment operations and their interaction with people. It is projected that there will be over 17 Billion connected smart sensors by 2025. At the same time, many asset intensive organizations continue to rely on reactive, preventative, or legacy maintenance strategies that lead to less than optimal operational efficiencies. This solution brief focuses on the opportunities to improve asset management strategies through the use of Machine Learning (ML) technology to build prescriptive maintenance solutions that can leverage the growing availability of Big Data.

About Skytree

Skytree – The Machine Learning Company® is disrupting the Advanced Analytics market with our enterprise-grade machine-learning platform that gives organizations the power to discover deep analytic insights, predict future trends, make recommendations and reveal untapped markets and customers. Skytree’s mission is to bring the power of state-of-the-art machine learning to everyone: including data scientists, developers and non-experts alike.

The Skytree machine-learning platform is built for speed and scalability, allowing users to build the most accurate machine-learning models, faster. Skytree machine-learning software delivers an end-to-end model building experience, from data preparation to model creation and deployment. Skytree automates the machine learning model-building process, saving you time. Machine-learning models using Skytree can be built using all of your data, both structured and unstructured, with no down sampling required.

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