Machine learning technology can now predict equipment failures weeks in advance. But how do you decide when and how to perform the repair to maximize productivity and minimize risk? Learn how Aspen Mtell and Aspen Fidelis enable you to quickly evaluate hundreds of possible future scenarios, and understand the financial consequences and risk involved in different operational decisions.

Aspen Mtell introduces exciting new features, including Alert Manager, industry-specific asset templates, custom models (BYOM) and intuitive dashboards and KPIs for improved visibility, health insights and recommended actions. This infographic provides a comprehensive overview of the capabilities now available in Aspen Mtell.

Aspen Mtell® combines the power of data and technology to enable reliability and maintenance engineers to monitor the performance of assets, providing real-time visibility into asset health and actionable insights for faster decision-making. Discover why companies like LG Chem, Evolution Mining, OCP Ecuador and others have opted for AspenTech´s prescriptive maintenance solution to improve their operational efficiency and achieve carbon mitigation and sustainability goals.

A recent study conducted by ARC Advisory Group analyzed how leading manufacturing companies are leveraging artificial intelligence (AI) and machine learning tools to improve asset performance. While condition-based maintenance is most prevalent, the study found that leaders have successfully built AI capabilities to enhance asset performance practices through in-house platforms, commercial solutions and a combination of both.

Bangkok Industrial Gas (BIG) wanted to transition from its on-premises database to Amazon Web Services (AWS) to aggregate data from different sources and unlock insights to predict equipment downtime early and accurately at BIG’s production plants.

With assets installed in remote locations, OCP Ecuador needed a maintenance solution that would enable them to predict and prevent equipment failures before they occurred. Using prescriptive maintenance, the company can now continuously monitor its critical assets for impending failure. In video, learn how OCP Ecuador reduced maintenance costs by 25% per year and increased engine overhaul from 16000 to 19200 hours, a 20% improvement in uptime.

Unexpected disturbances and shutdowns can severely impact any manufacturing facility. The AspenTech APM 4.0 portfolio uses agents that can be replicated quickly and easily across all plant assets to assure production and avoid unnecessary maintenance. Learn how APM 4.0 delivers an all-inclusive approach to efficiency, productivity and safety to support operational excellence in plant operations and the bottom line for manufacturers.

In this case study, discover how Sardeolica used prescriptive maintenance to achieve maximum value and expects to reduce maintenance costs up to 10 percent per year.

In today's industrial landscape, the ability to leverage data for safety and reliable plant maintenance is critical. But with so much industrial data from disparate sources, it’s difficult to gain the insights you need to achieve your operational goals.

Register today for the premier global event (April 29–May 3 in Houston, TX) for AspenTech customers, including users, operational leaders and executives within asset-intensive industries who are looking to elevate their business performance, improve their resiliency and meet their sustainability targets.