Reduce batch cycle time, production errors, and operating costs

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As operators seek ongoing investment and replacement of assets for the stability of hydrocarbon markets, what is next in LNG and beyond? How do firms rise to the top of the class in terms of returns on exploration investment, instead of bottom of the barrel? This article talks about how Industry leaders bring all aspects of an asset development into concurrency—from exploration to reservoir studies to engineering design to construction and operation—and the use of digitalization, technology and big data.

In the Pharma Times article “Working in Silos” AspenTech’s Justin Eames discusses the pitfalls of working in silos in the pharmaceutical industry and explains how AspenTech’s solutions can make an impact at speed using predictive analytics. Discover how to predict asset degradation and failure well in advance of an impending breakdown or disruption and gain the ability to make decisions that can not only minimize cost and disruption, but that can also protect public health by ensuring continuity and resulting quality of drug supply.

To achieve operational excellence, process manufacturers must quickly and systematically address the root causes of asset reliability problems, which include inadequate operating procedures, poor design, and improper scheduling of production.

For metals and mining, a prescriptive maintenance solution marries the inherent knowledge of operations with existing process data to automatically create an alert when a failure will occur - reducing the time spent searching for root causes.

See how you can use Aspen Technology solutions to develop a refinery wide process model that would enable refinery process engineers to evaluate the economic impact of operational changes and help planners achieve a more accurate assessment of profit margins.

To achieve operational excellence, process manufacturers must quickly and systematically address the root causes of asset reliability problems, which include inadequate operating procedures, poor design, and improper scheduling of production.

Leaders often wonder, where do we apply digital technologies to the challenges in our business? How can we chart our success? This uncertainty is understandable considering the technology’s complexity and rapid evolution, but understanding and integrating artificial intelligence (AI) is increasingly critical to competitiveness in the chemical industry.

2015年《巴黎协定》和其他国际气候变化协定有助于提高全球对各国需要采取紧急行动应对气候变化的认识。随着企业继续关注可持续性，围绕数字化作为关键推动因素的作用，一个共同的主题正在形成。事实上，ARC咨询集团最近的一项调查显示，75%的受访者认为数字化转型对于实现可持续发展目标非常重要。