With current shortages in on-site staffing, many companies struggle to prevent unexpected breakdowns. AI and machine learning technology leverage precise pattern recognition from manufacturing assets to provide weeks, or even months, of advanced warning on imminent degradation and failures.

The upstream oil and gas sector has faced a variety of challenges such as unpredictable oil prices, changing patterns of demand and ensuring safe working conditions at remote sites. Accelerated digitalization programs, particularly those that include digital twin technology, can provide agility and resilience to better handle future market uncertainty and lay the foundation for longer term competitive advantage.

Refineries are tasked with finding better ways to navigate today’s extremely disruptive environment. Many companies are operating under a “new normal”, characterized by extremely volatile markets, a depressed demand for products and a non-essential staff working remotely. In this on-demand webinar AspenTech experts share best practices to help you:

YPFB es la petrolera nacional de Bolivia y es un productor clave en la producción de gas en Sudamérica. Su producción empezó a disminuir drásticamente en dos de sus principales campos de gas en Bolivia por lo tanto YPFB necesitaba superar este problema para cumplir con sus obligaciones contractuales. En este webinar aprenda cómo utilizaron un gemelo digital de Aspen HYSYS para solucionar los cuellos de botella de su planta, ductos y estaciones de compresión lo que les permitió:

Economic, workforce and production transitions for chemical industry

在全球范围内，各领先组织正在接纳并实施先进的数字化技术。数字化转型之旅将改变资产密集型行业（尤其是能源和化工企业）的性质。在这种情况下，数字孪生（实物资产及其操作行为的虚拟副本）将发挥关键作用。对于今天我们创建的数字孪生，一个关键概念是人工智能在提供虚拟数据相关见解和建议方面的作用。

Real-time condition-based monitoring of assets is an attractive solution for mining companies to minimize their unscheduled downtime and improve reliability of critical equipment. The success of an asset monitoring program depends on how well this data is analyzed, filtered and categorized to enable accurate predictions of impending failures. Focusing on the behavior of an asset only tells a small portion of the story. To fully predict failures, the trends of the entire process must be considered as a whole.

En el panorama volátil actual, los refinadores deben cambiar sus operaciones para adaptarse a las demandas de los productos que están en constante cambio, y hacerlo con una fuerza laboral que trabaja remotamente. La tecnología de digital twin ofrece información clave para que los ingenieros puedan predecir posibles disrupciones del proceso desde cualquier lugar.

CDU(Crude Distillation Units)는 정유사에서 수익성을 추구하는 가장 중요한 공정입니다. 현재의 VUCA, 즉 변동성이 크고(Volatile), 불확실하며(Uncertain), 복잡하고(Complex), 모호한(Ambiguous) 비즈니스 환경에서 정유사들이 디지털 트윈 기술을 활용하여 현재의 불확실성을 보다 효과적으로 타개하여 민첩하고 신속하게 대응할 수 있도록 돕는 두 가지 기술 영역에 대하여 알아보겠습니다.

In today’s volatile environment, refiners must shift operations to adapt to ever-changing product demands – and do it with an increasingly remote workforce. Plant digital twin technology provides operational insights so engineers can predict potential disruptions from anywhere.