For metals and mining, a prescriptive maintenance solution marries the inherent knowledge of operations with existing process data to automatically create an alert when a failure will occur - reducing the time spent searching for root causes.

To achieve operational excellence, process manufacturers must quickly and systematically address the root causes of asset reliability problems, which include inadequate operating procedures, poor design, and improper scheduling of production.

The era of the intelligent mine is here and the maintenance department of the future will use insight to improve its decision-making ability based on data.

Real-time condition-based monitoring of assets is an attractive solution for mining companies to minimize their unscheduled downtime and improve reliability of critical equipment. The success of an asset monitoring program depends on how well this data is analyzed, filtered and categorized to enable accurate predictions of impending failures. Focusing on the behavior of an asset only tells a small portion of the story. To fully predict failures, the trends of the entire process must be considered as a whole.

As all companies have been challenged by the current economic and health crisis, the successful recovery requires a new view toward future development and growth with metrics that consider broad and more long-term goals. Featured in Hydrocarbon Processing, AspenTech’s Paige Morse shares considerations for building future resiliency that center around digitalization.

The impact of COVID-19 has accelerated digitalisation for the process industry. In this exclusive interview with Pipeline Oil & Gas News, Antonio Pietri, President and CEO of AspenTech®, discusses how this acceleration of digitalisation will lead to the creation of a Self-Optimizing Plant.

In this article, Robert Golightly explains the limitations of traditional maintenance practices and how new advancements in predictive maintenance are pushing assets and equipment to the limits of performance. Learn how today's industry leaders are using low-touch machine learning to extract value from design and operations data to predict when and where failures will occur.

After an electrical storm stopped gas production at one of its plants, SABIC executives and reliability engineers turned to Aspen Fidelis Reliability to calculate the probability of it—or a similarly debilitating event—happening again. Read this article from Plant Services to learn more.

Predictive technologies are taking the mining world by storm, providing new insights to help companies avoid dangerous situations and costly mistakes.

In today’s market, thriving in the mining industry means exploring new strategies for growth in the digital transformation era. Mining executives are seeking leading experts to help mitigate risk and lower cost. The Northern Miner recently sat down with AspenTech to discuss best practices of how a true machine learning solution has the power to transform mining.