Mandated to aggressively reduce emissions, today’s refining and chemical companies must also find new ways to improve energy efficiency and—in turn—margins. The sooner owner/operators uncover opportunities for improvement, the faster they can advance operational excellence goals.

AspenTech is thrilled to be a Gold Sponsor for this year’s event April 6-10 in Dallas. Our experts are looking forward to meeting you at booth #715!

Mandated to aggressively reduce emissions, today’s refining and chemical companies must also find new ways to improve energy efficiency and—in turn—margins. The sooner owner/operators uncover opportunities for improvement, the faster they can advance operational excellence goals.

Advanced simulation tools are key to overcoming the challenges of the green hydrogen economy. Process engineers who leverage Aspen Plus® simulation software can optimize hydrogen production processes, boost efficiency and reduce costs.

Process safety remains a priority for companies, but balancing the design of safety systems to withstand risks against higher CAPEX costs is challenging. Accurate, efficient modeling of depressurization is key, especially in carbon-capture processes.

Discover AspenTech Inmation, a cutting-edge industrial data fabric designed to optimize data-driven operations.

Optimizing chemical processes requires input from multiple disciplines – engineering, costing, safety and environmental. Evaluating these factors early in the design lifecycle significantly improves the quality of the design and reduces time spent collaborating across teams.

AspenTech Industrial AI™는 공정 산업의 판도를 바꾸는 기술로서 AI 알고리즘의 속도와 성능에 실제 도메인 전문 지식의 효율성과 매개변수를 결합하였습니다. 특수 목적에 맞게 설계된 아스펜테크의 AI 솔루션은 데이터 인사이트, 엔지니어링 기반기술, 공정자산에 대한 지식 및 산업에 특화된 전문 지식을 결합하여 고객 기업이 끊임없이 변화하는 비즈니스 요구 사항에 더 빠르게 적응하고 대응할 수 있도록 지원합니다.

Process industries, especially refineries, must continually adapt to operational changes driven by variations in feedstock, product demands, and other factors. Moreover, many critical KPIs cannot be directly measured in real-time within an operating plant.

Frequent shifts in market dynamics and operational constraints make refinery decision-making increasingly complex. Traditional methods for refinery cost analysis and margin modeling struggle to keep pace, leading to inefficiencies and missed opportunities.