There is a challenge for many refinery and chemical companies to impove the analysis proess and raise performance. The inside story of operational intelligence lies in rich thin visualization and analytics capabilities that improve production execution, enabling process manufacturers to quickly identify and resolve operational issues.

Virtually all multinational, diversified chemical companies are expanding their emphasis on specialty chemicals. Competition is intensifying, resulting in both margin degradation and faster product commoditization while customers are further exacerbating the situation by demanding “faster, better and cheaper” products. Learn how to leverage production scheduling to improve customer satisfaction and further take advantage of flexibility inside the plant.

Terrain-induced slugging can cause damage to processing equipment, but predicting slug volumes for sizing slugcatchers is challenging. Learn how Aspen HYSYS can be used to predict slug volumes due to terrain-induced slugging.  

See how the results of BLOWDOWN Technology in Aspen HYSYS compare with published results.

The goal of APC implementation in the chemicals industry is simple: to maximize margins while meeting customer expectations. Aspen DMC3 delivers faster time-to-benefits resulting in a much higher return on investment. Learn how APC is key to achieving operational excellence.

Learn about the underlying technology and validation results for the Acid Gas - Chemical Solvents Property Package in Aspen HYSYS used for amine solvents in Gas-Liquid Systems, such as MDEA, MEA, DEA, PZ and PZ+MDEA.

在白皮书里，我们探讨先进过程控制(APC)如何提高生产处理量，降低能耗，改善石油化工厂和聚合物工厂的产品质量。

Learn about the underlying technology and validation results for the Acid Gas - Physical Solvents Property Package in Aspen HYSYS used for physical solvents in gas-liquid systems, specifically DEPG.

Traditional preventive maintenance alone cannot solve the problems of unexpected breakdowns. With asset performance management powered by low-touch machine learning, it’s now possible to extract value from decades of process, asset and maintenance data to optimize asset performance. This white paper describes five best practices for driving state-of-the-art reliability management to predict breakdowns months in advance—increasing production and profitability.

Traditional preventive maintenance alone cannot solve the problems of unexpected breakdowns. With asset performance management powered by low-touch machine learning, it’s now possible to extract value from decades of process, asset and maintenance data to optimize asset performance. In this white paper, learn how this disruptive technology deploys precise failure pattern recognition with very high accuracy to predict equipment breakdowns months in advance and advise on prescriptive maintenance. The paper also outlines five best practices for driving state-of-the-art reliability management to increase production and profitability.