A guide for describing, evaluating, and reporting environmental, social, and governance (ESG) data Social-related data reported to stakeholders rose 37% in 2021 compared to 2020 (McKinsey & Company). Interested in learning more about your ESG data and how to achieve your sustainability goals?

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Metrics—Planet Data and Metrics Page 86 Metrics—Planet Data and Metrics Page 86 Metrics—Planet Data and Metrics Page 86

A guide for describing, evaluating, and reporting environmental, social, and governance (ESG) data Social-related data reported to stakeholders rose 37% in 2021 compared to 2020 (McKinsey & Company). Interested in learning more about your ESG data and how to achieve your sustainability goals?

A guide for describing, evaluating, and reporting environmental, social, and governance (ESG) data Social-related data reported to stakeholders rose 37% in 2021 compared to 2020 (McKinsey & Company). Interested in learning more about your ESG data and how to achieve your sustainability goals?

Predictive simulation technology uses conventional (isotropic) and advanced (anisotropic) modeling data from material characterizations, mold filling analysis, and finite element analysis (FEA) to more accurately forecast performance and potential failure points. By factoring in static and dynamic data, the CAE simulations can identify where an injection molded plastic part may crack or break when exposed to real-world conditions such as physical loading force, sudden impact (crash simulation), or environmental factors like temperature and humidity.   For more technical details on the structural performance of reinforced polymers using CAE, automotive design engineers may access material data and models for Avient’s fiber-reinforced solutions using Hexagon’s Digimat-MX Tool.

Predictive simulation technology uses conventional (isotropic) and advanced (anisotropic) modeling data from material characterizations, mold filling analysis, and finite element analysis (FEA) to more accurately forecast performance and potential failure points. By factoring in static and dynamic data, the CAE simulations can identify where an injection molded plastic part may crack or break when exposed to real-world conditions such as physical loading force, sudden impact (crash simulation), or environmental factors like temperature and humidity.   For more technical details on the structural performance of reinforced polymers using CAE, automotive design engineers may access material data and models for Avient’s fiber-reinforced solutions using Hexagon’s Digimat-MX Tool.

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Overview of how Avient serves wire & cable customers, highlighting both power and data cables technologies Corrugated Sheet Extrusion Sheet & Strap