With mounting pressure to reduce carbon emissions—and still meet critical production targets—today’s energy and chemical companies are challenged to stay on top of changing operating conditions and respond in a timely, efficient and coordinated manner.

For decades, first principle models have been used for process design and optimization in the chemical industry. Recent innovations employ machine learning techniques—enriched with first principle constraints—to create a hybrid model that closely represents real plant behavior. Fast, easy access to industrial AI is helping organizations make accurate decisions to select an optimum design quickly and improve operations, maximizing productivity and minimizing energy usage.

Industrial data from a variety of sources and locations has the potential to help organizations meet energy efficiency goals, avoid raw materials/feedstock shortages, decrease downtime, increase profitability and improve ESG reporting. But the chemical industry, like other asset-intensive industries, generates large amounts of data that never gets collected, contextualized and used to its full potential.

The successful execution of engineering projects requires intense collaboration among multi-discipline teams, but manual data handoffs often lead to errors, inconsistencies and delays that can derail a project.

To chemical and polymer manufacturers, achieving site optimization and resiliency to disruptions is key to meeting the world's ever-changing demand. Take a deep dive look into the flywheel effect of how Advanced Process Control (APC) and Scheduling synergies takes manufacturing sites to another level of performance and resilience. Leverage both of these crucial layers together to multiply the benefits of each other.

Watch this webinar on Aspen InfoPlus.21® (IP.21) from AspenTech, exploring the potential of contextualizing historical data to transform your business.

Reducing energy use and GHG emissions remains a priority for the process industries. However, when designing more energy efficient plants or revamping existing sites, a high level of expertise is required to perform Pinch analysis. Engineers have limited time available for design, and the use of separate tools by multiple disciplines also brings the risk of errors due to manual data transfer.

We're excited to present the AspenTech DataWorks Community—a dynamic platform designed to connect, educate and empower industrial professionals like never before.

Uncontrolled flare emissions are a costly economic and environmental risk for energy and chemicals companies. During this webinar, learn how Braskem Process Engineers investigated losses in a downstream column and used Aspen ProMV to quickly resolve the problem — saving >$1M a year in losses to flare.

For chemical manufacturers, responding with agility to inevitable daily supply and demand disruptions is vital to reach planning and scheduling goals.