Linde Engineering North America monitors construction costs and progress using ACCE linked to 3D models driving down the cost of the estimate.

Learn how YPFB Andina was able to increase their gas production using an integrated model solution that was able to provide a $280M increase in revenue in 1 year.

Phillips66 improves estimating productivity by 85% and reduces estimating variability to +/-15% with a five year before and after analysis of estimates vs. completed projects. Download the case study to learn more.

Shell Oil Company is a global energy and petrochemicals company that produces natural gas, gasoline, oil, and many bulk and specialty chemical products for customers worldwide. Read this case study to learn how Shell’s Manufacturing Margin Optimization team uses AspenTech solutions and AWS Cloud to optimize its energy and petrochemicals business, including planning and scheduling applications.

In this case study learn how a global oil and gas company was able to detect and predict a variety of pending equipment failures. Download today to uncover how Aspen Mtell enabled the company to correctly identify all reported events – as well as unknown problems.

GlaxoSmithKline (GSK) wanted to review the structure of its batch production record and associated workflows as part of a continuous improvement process. Reducing batch review time usually results in faster batch cycle time, meaning higher throughput at the production facility and faster cash-to-cash cycle time. AspenTech was selected for this process due to integration with other solutions, such as Aspen InfoPlus.21® and GSK’s existing plant automation software (DCS). The pilot project was a resounding success, reducing order preparation time by 95% and record review time by over 50%.

When developing its highly successful digital transformation program, a leading European energy company turned to Aspen Mtell® for predictive maintenance. After deploying Aspen Mtell on more than 50 large assets in a refinery, the company began testing the technology at a wind farm and had five early successes in predicting gear box failures.

This article, featured in The Chemical Engineer, discusses why operators often struggle to know where to begin to digitally transform. AspenTech's Paige Morse outlines how many operations, particularly in specialties, have become increasingly complex as customers demand higher levels of performance and quality and a greater range of options from producers. Operators realize they need to diversify product lines to meet these increasingly sophisticated needs. Download this article to learn more.

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.

Industrial organizations are sitting on a decades-old, massive double-edged sword: their data. Until now.