Downstream refining and manufacturing facilities always seek to improve equipment reliability, performance, and maintenance costs to maximize profitability and business value. However, aging operational equipment and resource-intensive maintenance activities pose a risk both to field personnel and to downstream enterprises as a whole. Equipment Health and Maintenance solutions on AWS provide predictive analytics that gather and analyze equipment process data in near real time and generate data-driven insights for downstream-refining enterprises. With these solutions, downstream refining and manufacturing facilities can better predict potential equipment failures and develop preventative maintenance strategies, improving their efficiency and minimizing unplanned downtimes.

Partner Solutions

Software, SaaS, or managed services from AWS Partners

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  • Aspen Mtell

    Provides early and accurate warning of when an asset failure will occur, how the failure will occur and what to do about it.
  • A fully managed sustainable industrial asset performance…

    Shoreline created the industry-first, off-the-shelf, fully automated solution for remote machine health monitoring and predictive maintenance, methane emissions detection and energy monitoring. This easy to use and deploy fully managed asset performance management platform remotely monitors industrial assets 24x7 to deliver real-time, actionable knowledge. It's offered as an affordable single SaaS subscription, including sensors, with zero Capex.
  • Seeq

    Seeq's extensive support for time series data and its inherent challenges enables process engineers, managers, teams and data scientists to derive more value from data already collected by accelerating analytics, publishing, and decision making.
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Guidance

Prescriptive architectural diagrams, sample code, and technical content

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