“Automation also can help identify issues before something critical fails. Finding problems as early as possible helps improve asset management,” says CSX Executive Vice President and Chief Operating Officer, Cindy Sanborn. Read this article to learn more about CSX’s exciting project with Mtell, which uses patented machine learning technologies with industrial assets to perform predictive maintenance which no longer runs parts to failure.

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.

LOTTE Advanced Materials was looking for a tool that would convert data into value to drive operational excellence. In this ARC Advisory Group article, read how LOTTE chose AspenTech’s aspenONE Manufacturing Execution Systems (MES) software to transform digitally, and build a robust data analytics platform. Now, LOTTE is able to lock in a visionary software implementation roadmap to optimize business processes and operations.

This article appeared in the 2018 American Fuel & Petrochemical Manufacturers (AFPM) Conference Daily (Oct 2018) that highlighted the Operational Planning, Control and Automation Technologies session during which Chevron talked about the closed-loop, real-time coordination of a refinery middle distillate system, the benefits and key takeaways.

This article describes how engineering, procurement and construction (EPC) firms are now forging ahead as the industry recovers from years of cutting costs to scale resources back up as the volume and size of projects increase.

In this article, Transform and Grow – Manufacturing Excellence in Specialty Chemicals, Aspen experts discuss what is required to drive transformation in specialty chemicals through technology-enabled best practices.

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.

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

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.

The 2015 Paris Agreement and other international climate change accords have helped raise global awareness of the need for countries to take urgent action to combat climate change. As companies continue to focus on sustainability, a common theme is taking shape around the role of digitalization as a key enabler. In fact, a recent ARC Advisory Group survey revealed that 75% of respondents rated digital transformation as highly important for achieving sustainability goals.