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Case Study

Top Diesel and Naphtha Producer Uses Product and Process Quality Analytics to Reduce Flaring, Emissions

ORYX GTL Limited is a gas-to-liquids (GTL) diesel and naphtha producer located in Doha, Qatar. The company is committed to reducing its carbon production through the minimization of flaring. By implementing AspenTech´s product and process quality analytics solution, Aspen ProMV®, ORYX was able to increase its diesel and naphtha yield.

Case Study

Specialty Chemicals Producer Reduces Off-Spec Product With Aspen ProMV®

A leading global producer of catalyst solutions and specialty chemicals faced a significant challenge as a result of light impurities causing product quality issues in its downstream production units. By implementing Aspen ProMV, the company witnessed a rapid time to value, with analysis and modeling completed in a fraction of the time required by competing solutions.

Case Study

Petrochemical Company Reduces Energy Consumption at its Pyrolysis Furnaces

A global petrochemical producer wanted to improve monitoring and efficiency, specifically starting with energy consumption, of its pyrolysis furnaces by integrating a predictive vision. With the current process, it was challenging to maintain unit efficiency and stay at a consistent operating level. The company was able to solve these challenges by implementing Aspen ProMV™.

Case Study

Polymers Producer Uses Digital Process Analysis to Reduce Costs and Advance Sustainable Operations

A polymer producer that specializes in the production of raw materials for the plastics industry, including polypropylene, polyethylene and masterbatch, needed a solution that would allow them to achieve the right balance between producing high-quality products and keeping the production costs in line. The company selected Aspen ProMV®, which allowed them to automate process analysis and monitoring.

Case Study

Como a Braskem Idesa Aumentou o Tempo Operativo do Reator em mais de 20% Usando Datos e Recursos Existentes

Neste estudo de caso, saiba como a Braskem Idesa usou o Aspen ProMV™ para identificar e corregir em forma proativa condições que históricamente levaram ao entumpimento dos reatores altos.

Case Study

Cómo Braskem Idesa incrementó su tiempo útil en más de 20% utilizando datos y recursos existentes

En este caso de estudio, conozca cómo Braskem Idesa utilizó Aspen ProMV ™ para identificar y corregir de manera proactiva y de acuerdo a las condiciones históricas que llevaron a una mayor velocidad de ensuciamiento.

Case Study

How Braskem Idesa Increased Reactor Uptime by Over 20% Using Existing Data and Resources

In this case study, learn how Braskem Idesa used Aspen ProMV™ to proactively identify and correct for conditions that historically led to high reactor fouling.

Case Study

Aspen ProMV™ Saves Petrochemical Company Over $1 Million USD in Losses to Flare

A large petrochemical company was seeing incremental loss to flare of more than $1M USD annually. Read how Aspen ProMV was able resolve their issue within 2 days, save $1M per year and prevent future losses.

Case Study

Análisis estadístico multivariable encuentra la causa de un problema de alta viscosidad en el aceite de enfriamiento

Una de las empresas más grandes a nivel mundial para productos químicos, plásticos y de refinación utilizó Aspen ProMV para entender y resolver sus problemas de producción causado por un problema de alta viscosidad en el aceite de enfriamiento. En este caso de estudio conozca cómo Aspen ProMV permitió a la empresa a destacar las principales variables de proceso que están altamente correlacionadas con problemas de viscosidad y que guio rápidamente a los ingenieros de proceso al problema subyacente para limitar las pérdidas.

Case Study

Multivariate Statistical Analysis Finds Cause of Quench Oil High-Viscosity Issue

One of the world's largest chemical, plastic and refining companies used Aspen ProMV to understand and resolve production problems caused by an ongoing quench oil high-viscosity issue. In this case study, learn how Aspen ProMV enabled the company to highlight the top process variables highly correlated with viscosity issues, and quickly guided process engineers to the underlying issue to limit losses.

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