Across the globe, leading organizations are embracing and implementing advanced digital technologies. The digital transformation journey will change the nature of asset intensive industries, particularly the energy and chemicals businesses. In that context, digital twins — virtualized copies of physical assets and their operating behaviors — will play key roles. For the digital twins we create today, a key concept is the power of AI in providing insight and advice against the virtual data. Download this white paper to learn about these essential keys to your digital twin strategy:

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。

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。

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.

Industry is adopting AI/ML tools to find new ways to execute, become more efficient and increase value from assets in response to market changes.

Ambitious new carbon-reduction proposals by the EU will compel major increases in efficiency and sustainability for asset and energy-intensive industries.

Industrial organizations require historical and real-time data for AI and analytics on the cloud to keep the business running efficiently.

Is all condition monitoring created equally? Our technology enables new, easy to use and implement solutions that are scalable and provide more accurate and earlier detection.

With Aspen Hybrid Models, process engineers can use AI to easily tune simulations and make quick and accurate decisions. Learn how.