Predictive Analytics

AVEVA Predictive Analytics employs artificial intelligence to enhance asset reliability and prevent unplanned downtime through predictive maintenance. By providing forecasting on time-to-failure and suggesting remedial actions, it aids in minimizing repair durations and reducing downtime. The platform operates in a no-code environment, allowing anomalies to be detected weeks or months ahead of potential failures, which empowers users to manage these issues proactively.

Key benefits of this solution include the ability to identify asset anomalies long before failures occur, thereby eliminating unplanned downtime. Users can efficiently roll out and scale predictive maintenance programs to accelerate return on investment. The tool also delivers qualitative insights, transforming analytics into actionable measures that help mitigate failures and capture best practices.

Features

• Anomaly Detection: Provides advanced alerts and includes a case management system for knowledge capture, allowing users, even those without programming skills, to deploy, validate, and interpret predictive models. Predefined templates streamline the configuration and scaling processes.
• Fault Diagnostics: Utilizes custom data and diagnostic instruments to offer precise real-time insights, helping users perform consistent analyses to quickly diagnose and resolve issues. It matches current performance against fault conditions and identifies faulty sensors.
• Time to Failure Forecast: Offers forecasts on likely failure timing, empowering users to prioritize repairs and maintenance strategies that enhance safety and profitability without unnecessary operational pauses.
• Prescriptive Guidance: Leverages over 22,000 hours of experience from the AVEVA Asset Library, offering predefined guidance to operationalize asset maintenance and performance decisions, thus cutting down repair times.
• Security: Easily integratable with existing enterprise security systems, supporting single sign-on authentication and detailed user access management.
• Bring Your Own Algorithm: Allows the integration of specific algorithms into the maintenance loop using Python or similar languages, enhancing customization and complementing built-in model templates with advanced analytics.

Success stories such as PETRONAS, a major player in the oil and gas sector, underscore the platform's efficacy. By deploying AVEVA Predictive Analytics, PETRONAS achieved significant cost savings, specifically $US33 million since 2019, through early equipment anomaly notifications.

The application allows users to schedule downtimes strategically, lowering maintenance expenditures and reducing workforce disruptions. It aids in improving sustainability by predicting and preventing failures before they occur, thus conserving resources and decreasing energy usage. Continuous real-time asset performance monitoring ensures equipment issues do not escalate into severe productivity losses, providing alerts when deviations are detected.