Video

Aspen DMC3 Demo: Constrained Model ID

Lucas Reis demos 3 scenarios where the Constrained Model ID feature can be used: zero gain constraints (set gains equal to zero), mass balances (ensure they make physical sense) and gain ratios (set gain ratios equal to one, or gains equal to each other).

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Six Keys to Operational Excellence in the Process Industries

How data visualization & analytics improves operating efficiency.

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How to Have Rigorous Fired Heater Models Within Your Refinery Process Simulation Flowsheet

See how you can incorporate rigorous models of fired heaters within your refinery process flowsheet so as to improve the fidelity of your process.

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Learn How to Accurately Predict Impact of Operational Changes on Refinery Profit

See how engineers can develop and use a refinery-wide process model in Aspen HYSYS to accurately predict the impact of operational improvements on the refinery’s profit.

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Visualization and Analytics for Ad Hoc Problem Solving

Visualization and analysis shorten the duration and severity of production disruptions. This video discusses some of the challenges engineers face in rapidly identifying and responding to disturbances.

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Part 1: Optimizing Heat Exchanger Design & Operation

Part 1: Improving the User Experience -  This interview with AspenTech developer Sam Neilsen, is a compelling piece to put the people behind the software with EDR.

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Part 4: Optimizing Heat Exchanger Design

Part 4: This interview with Hafez Bharami, a PhD chemical engineering in our heat exchanger R&D team.

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Part 3: Optimizing Heat Exchanger Design

Part 3; Interview with product manager Sujit Potdar communicates the value proposition to businesses and the product scope and vision of Aspen EDR.

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Part 2: Optimizing Heat Exchanger Design

Part 2: Technical direction and vision. This interview with key developer Gabe Aurieoles, puts the face to the technical expertise and vision behind the EDR product.

Data Management for Manufacturing Operations Management

Data must be prepared for analysis by removing bad values, dealing with missing values, aligning data from different systems and performing any required transformations. The skills for those tasks are anything but common. Automation can play a significant role in completing those tasks and others in the analysis workflows by supplementing the skills of users with best-practice based approaches to data conditioning. 

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