As all companies have been challenged by the current economic and health crisis, the successful recovery requires a new view toward future development and growth with metrics that consider broad and more long-term goals. Featured in Hydrocarbon Processing, AspenTech’s Paige Morse shares considerations for building future resiliency that center around digitalization.

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。

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.

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.

産業用AIでより高いレベルの収益性と持続可能性を実現します。私たちは、最も広く採用されている業界をリードする製品やソリューションにAIを組み込み、データサイエンティストがドメインエキスパートと協力してモデルを充実させています。

Delivering higher levels of profitability and sustainability with Industrial AI. We embed AI into our most widely adopted, industry-leading products and solutions, and empower data scientists to collaborate with domain experts to enrich models.

Delivering higher levels of profitability and sustainability with Industrial AI. We embed AI into our most widely adopted, industry-leading products and solutions, and empower data scientists to collaborate with domain experts to enrich models.

EPC（設計・調達・建設）

This paper discusses digital transformation in the oil patch. It explores how upstream industry leaders are capitalizing on the explosion of data and how, in particular, merging rigorous process models with both analytics and data visualization can help achieve a competitive advantage. It also reveals how innovations from AspenTech are helping to lead the way toward asset reliability and profitability.

Traditional preventive maintenance alone cannot solve the problems of unexpected breakdowns. With asset performance management powered by low-touch machine learning, it’s now possible to extract value from decades of process, asset and maintenance data to optimize asset performance. In this white paper, learn how this disruptive technology deploys precise failure pattern recognition with very high accuracy to predict equipment breakdowns months in advance and advise on prescriptive maintenance. The paper also outlines five best practices for driving state-of-the-art reliability management to increase production and profitability.