See how you can use Aspen Technology solutions to develop a refinery wide process model that would enable refinery process engineers to evaluate the economic impact of operational changes and help planners achieve a more accurate assessment of profit margins.

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.

See how refineries can keep their profit margins high by maintaining their planning models up to date, in the face of changing operating conditions, using capabilities built in Aspen HYSYS.

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.

As operators seek ongoing investment and replacement of assets for the stability of hydrocarbon markets, what is next in LNG and beyond? How do firms rise to the top of the class in terms of returns on exploration investment, instead of bottom of the barrel? This article talks about how Industry leaders bring all aspects of an asset development into concurrency—from exploration to reservoir studies to engineering design to construction and operation—and the use of digitalization, technology and big data.

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.

In the Pharma Times article “Working in Silos” AspenTech’s Justin Eames discusses the pitfalls of working in silos in the pharmaceutical industry and explains how AspenTech’s solutions can make an impact at speed using predictive analytics. Discover how to predict asset degradation and failure well in advance of an impending breakdown or disruption and gain the ability to make decisions that can not only minimize cost and disruption, but that can also protect public health by ensuring continuity and resulting quality of drug supply.

“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.

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.