AI and analytics drive superior asset performance
Asset reliability is critical to operational resilience and profitability. AI-enhanced analytics transform data and operations management, while generative AI ushers in a new era of collaboration and decision-making in the industrial world.
Many organizations have deployed point solutions for asset monitoring and performance optimization. They then find it difficult to build an end-to-end solution that can automatically discover new assets, monitor performance, assess the need for intervention and initiate the appropriate maintenance tasks.
Asset reliability management seeks to achieve optimal asset performance, minimize maintenance costs, enhance safety, report against sustainability KPIs, and ensure compliance. With a robust end-to-end reliability strategy powered by innovative AI technology, you can achieve operational resilience, meet your sustainability goals and maximize profitability.
Asset reliability use cases
Enable a connected workforce to drive safe and reliable operations by increasing overall equipment effectiveness, reducing unplanned downtime, and building the confidence to shape a sustainable future.
Reduce maintenance costs
Rethink traditional time-based or scheduled maintenance. Condition-based maintenance uses real-time performance data to track asset health and trigger maintenance only when needed. It allows you to lower maintenance expenses, reduce spare parts inventory, and minimize travel time.
Reduce unplanned downtime
Improve asset reliability and availability by building models that predict potential failures before they occur. Use advanced analytics, AI and ML to increase predictive accuracy and take action to avoid outages. Monitor working conditions to spot safety issues and protect your workforce.
Optimize efficiency and production
Adopt a proactive, data-driven approach to maximize reliability, efficiency, product quality and safety. Enforce consistency and manage compliance risks. Minimize waste and loss with real-time monitoring and advanced analytics.
Customer stories
Suncor
Suncor achieved predictive maintenance by improving its risk analysis and turbine performance degration measurement with AVEVA™ PI Vision™ and AVEVA™ Predictive Analytics.
Quebec Iron Ore
Quebec Iron Ore digitally transformed its mining operations to improve asset reliability and achieve complete pit-to-port visualization with AVEVA solutions.
SCG Chemicals
When the leadership of SCG Chemicals, one of Thailand’s largest integrated petrochemical complexes, wished to improve efficiency across its value chain the team selected AVEVA™ Asset Performance Management software to help deliver the resilience, agility and maintenance savings they needed to accelerate the transformation of their operations.
