On Demand Webinar

Using Digital Twins to Build More Accurate Inferentials for Improved Process Control

Advanced process control (APC) applications require accurate inputs for stream qualities, including product compositions and distillation curve points. While online analyzers are effective in supporting model predictive controllers, they are expensive and often unavailable for important process streams. There is a more cost-effective approach for building virtual analyzers or inferentials to accurately estimate stream qualities and it starts with digital twins.

Video

Executive Dialogue: Meeting the Dual Challenge in the Context of Net Zero - 2050

European refiners face a “dual challenge" – meeting the growing demand for resources and higher standards of living from a growing population while also addressing sustainability goals, reductions in carbon emissions and plastic waste in the environment. View this insightful conversation featuring industry leaders from Eni and MOL Group as they discuss both the challenges and opportunities in the transition to net zero by 2050.

Case Study

SABIC Continuously Optimizes its Utility System to Reduce Emissions and Increase Plant Energy Efficiencies

SABIC is a leading multinational manufacturing company, specializing in the manufacture of petrochemicals, chemicals, industrial polymers, fertilizers and metals. Energy efficiency is a key focus area for SABIC. To close the gap towards achieving 2025 goals, SABIC identified the need to quantify energy losses and execute actions to optimize operations while addressing daily plant challenges.

News Article

To make industrial data actionable, evolve your data historian with an AIoT strategy

CIO - To make industrial data actionable evolve your data historian with an AIoT strategy

News Article

3 Ways CDOs Drive Successful Industrial Digital Transformation

InformationWeek - 3 Ways CDOs Drive Successful Industrial Digital Transformation

On Demand Webinar

Use of Surrogate Models to Enhance Rigorous Simulation Performance

Surrogate models (or Reduced-Order Models) allow simulation users to explore and identify optimal process performance conditions faster than full, rigorous simulations. But there are times when users may find they are extrapolating beyond the data used to develop the surrogate model or when there is a desire to confirm the accuracy of the surrogate model. In these cases, the surrogate model can be used to enhance model performance, from both a robustness and performance perspective.

On Demand Webinar

On-Demand Data Reconciliation for a Fleet of Hydrogen Production Plant

The growing interest in hydrogen as the fuel of the future requires manufacturing plants to be operating efficiently using data-driven methods. With online data servers, engineers have a seemingly infinite amount of data at their fingertips. Reconciling this data for use in more advanced tools or calculations can be a tedious and labor-intensive process.

Article

Artificial Intelligence can Elevate Pharma Manufacturing

Unnecessary downtime can be expensive for pharmaceutical manufacturing operations; unplanned stoppages can delay the delivery of much needed product, potentially causing damage to a company's reputation.

Aspen DMC3 Builder

Aspen DMC3 Builder helps you manage the entire lifecycle of APC controllers with a single, powerful, integrated platform.

Aspen PIMS-AO

AspenTech's Aspen PIMS-AO proprietary optimization engine gives your plant production planning team the ability to improve quality, robustness and speed.

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