In today’s ever-evolving global economy, energy and chemical companies need to operate with newfound agility to meet market demand and maximize margins. Aspen DMC3 Adaptive Control now embeds powerful AI machine learning algorithms to build seed models by simply mining historical data. In addition, operators and engineers are now able to find answers 24x7 to common questions and get actionable guidance from Aspen Virtual Advisor's augmented intelligence. View this video and learn how you can coordinate multiple APCs in closed-loop and optimize broad envelopes in real-time to align planning, scheduling and operation, significantly reducing margin leakage and energy costs.

Achieve resilient operations by evaluating optimized downtime scheduling options to minimize impact on production and order commitments. Watch this video to learn how to leverage prescriptive maintenance and advanced scheduling optimization to make ideal downtime decisions.

Indepth on APM

Aspen Unified Reconciliation and Accounting (AURA) is the next generation production accounting solution that addresses key market needs: fast and efficient mass and volume balance, advanced analysis, reporting and visualization to enhance collaboration among key stakeholders and enable agile decision making. Use this interactive infographic to discover how AURA effectively manages the business process of measuring, validating, reconciling and publishing all the flows and inventories into, within and out of a plant.

A breakthrough innovation, Aspen Hybrid Models™ help energy companies quickly develop comprehensive, accurate models to address the most complex operational challenges.

Discover how to predict equipment breakdowns and perform prescriptive maintenance using a new approach to asset performance management. In this white paper, learn how nine early adopters of prescriptive analytics have reduced unplanned downtime and improved asset reliability. Download the paper to read real stories about the bottom-line results that have been achieved—in as little as 2 ½ weeks.

One of the key challenges in accelerating decision-making and reducing the development cycle of any operational E&P prospect is to seamlessly share the same updated data with all parties involved in the project. An Aspen Geolog-OSDU Connector was built by the AspenTech SSE team in close collaboration with TotalEnergies.

Linking vast amounts of plant data with either off line or online process models, engineers can improve operational decisions with deeper process insights. AspenONE Engineering will increase throughput and operating efficiency through data-driven decisions enabled by plant calibrated predictive models through an operator friendly interface.

The digital transformation journey can be personalized based on each company’s maintenance maturity, by augmenting or improving on technologies such as condition-based monitoring and product inspections rather than replacing them.

As the Oil & Gas industry attempts to address the threat that carbon release poses to the global climate, the issue of unplanned downtime comes into focus. To avoid greenhouse gas emissions and minimize safety incidents, companies can leverage AI systems such as prescriptive maintenance powered by machine learning to predict impending failures weeks or months in advance—and prescribe actions to avoid or mitigate the issue.