화학 산업은 제조 운전 과정에서 엄청난 양의 공정 데이터가 실시간으로 생성됩니다. 이 데이터는 많은 정보를 담고 있으며, 공정 모델링을 함께 적용하는 경우, 보다 나은 운전 의사 결정을 내릴 수 있는 통찰력을 제공할 수 있습니다. 본 웨비나는 증류탑 성능 향상 방안을 모색하고 있는 프로세스 엔지니어와 운전 담당자들을 대상으로 합니다.

Today, it’s more important than ever to perform rigorous optioneering to find the best solutions for improving process efficiency and asset flexibility. In this webinar, AspenTech’s experts will show how the new Aspen Multi-Case™ dramatically accelerates the evaluation of design and operating scenarios, provides visual tools for selecting the best alternatives and improves overall agility and collaboration across the engineering team.

Las columnas de destilación son unidades problemáticas, que representan uno de los mayores desafíos operativos en la industria de procesos, principalmente porque las condiciones internas son dinámicas y hay una visión operativa limitada de su comportamiento. Los gemelos digitales online y offline ofrecen a los ingenieros y operadores poderosas capacidades para el análisis de columnas y así puedan responder a cambios operacionales de una forma más rápida.

Crude Distillation Units (CDU) are one of the most critical units impacting a refinery’s profit margin. Refiners have found it challenging to optimize their CDU operations as the complexity of the unit has kept them from simulating the entire unit in one piece. However, with new ‘equation-oriented’ technology in Aspen HYSYS, refineries can build a robust integrated model of their crude distillation column and pre-heat train network. View this webinar and learn how you can improve your CDU operations today!

Distillation columns are troublesome units, representing one of the biggest operational challenges in the processing industry — primarily because internal conditions are dynamic and there is limited operational insight into their behavior. Offline and online advanced process simulation offers engineers and operators powerful process engineering capabilities for column analysis. With operations-oriented columns troubleshooting, you can gain insights into key processes and enable faster problem-solving.

화학 산업은 제조 운전 과정에서 엄청난 양의 공정 데이터가 실시간으로 생성됩니다. 이 데이터는 많은 정보를 담고 있으며, 공정 모델링을 함께 적용하는 경우, 보다 나은 운전 의사 결정을 내릴 수 있는 통찰력을 제공할 수 있습니다. 이 웨비나를 통해 증류탑 성능 향상 방안을 비롯하여 첨단 기술을 통해 업스트림 비즈니스 발전을 지원하는 아스펜테크의 비전에 대해 알아보십시오.

Chemical manufacturing operations provide a huge amount of process data generated in real time. This data is a wealth of information and can provide insight into better operational decision-making when tied to process modeling. Our webinar is designed for both process engineers and operators seeking to improve their distillation column performance.

Frustrated designing your column or understanding how process changes will affect your distillation unit operations? Many non-ideal distillation systems cannot be modeled accurately with equilibrium-based modeling. Rate-based modeling provides a more rigorous modeling approach for complex systems. Once tuned, rate-based models can yield better predictions at extrapolated operation conditions.

Refineries and olefin plants are constantly challenged by the gap between their plan and actual plant performance, leaving millions of dollars per year in lost margins on the table. ARC’s Contributing Analyst Peter Reynolds discusses this challenge and why it presents a big opportunity for refineries and chemical companies. In addition, AspenTech’s Henrik Terndrup, Sr. Director of Product Management, will explain how dynamic optimization technology - Aspen GDOT – is helping more than 15 companies meet or even exceed planned targets. View this on-demand webinar to discover how your refinery or olefins facility can improve margins by vertically integrating planning, scheduling and advanced process control in a closed loop.

Operations in the process industries are challenging due to the inherent complexities and lack of insights. Plant digital twin technology helps solve these challenges. Learn how Burns & McDonnell developed and deployed a plant digital twin of a refinery’s FCC unit using rigorous process simulation to: