Celebrating International Day of Women and Girls in Science at AspenTech

At AspenTech, we are fortunate to have a prominent contingent of women in STEM. In recognition of this day, we highlight women scientists and engineers who make up the AspenTech family.


Digitalization and Sustainability Perspectives from 2023 ARC Forum

Operational excellence, digitalization and sustainability were all key topics of discussion at the 27th Annual ARC Forum. AspenTech CMO, Lawrence Schwartz details his experience.

Case Study

Novozymes Uses Process Modeling to Optimize and Develop Biodiesel Processes

Novozymes A/S, a global biotechnology company based in Denmark, was looking to support the development and optimization of biodiesel processes due to increasing biodiesel market demand, rising materials costs and more stringent industry regulations. Novozymes saw potential in combining AspenTech technology with its own unique design and processing expertise to more quickly identify new opportunities to increase profitability of biodiesel production processes.


Insights from ARC Forum 2023: Navigating the Path to a Sustainable Future

At the annual ARC Forum meeting in Orlando, we highlight the dual challenge of meeting the growing demand for resources while addressing sustainability goals.


Taming the Downtime Scheduling Beast

Achieve supply chain resilience with downtime scheduling that leverages prescriptive maintenance and advanced scheduling optimization to minimize impact on production.

Press Release

Aspen Technology Combines inmation Software and AIoT Hub to Advance Customers’ Digital Transformation Strategies

A global leader in industrial data management from the shopfloor to the boardroom, we accelerate data-driven value creation in asset-intensive industries through robust data software offerings. 


Exploring the African Heritage in our Daily Cuisine

To celebrate Black History Month, Byron Gautier, a member of the AspenTech Black Leadership Forum, explores how African culture has shaped our food, drink and American popular culture.


Introducing the AspenTech DataWorks Business Unit

AspenTech DataWorks is purpose-built to be the global leader in industrial data management.

Technical Paper

Unsupervised Machine Learning for Seismic Facies Classification Applied in Presalt Carbonate Reservoirs of the Búzios Field, Brazil

Seismic data can provide useful information for prospect identification and reservoir characterization. Combining seismic attributes helps identify different patterns, for improved geological characterization. Machine learning applied to seismic interpretation is very useful in assisting with data classification limitations.

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