Controlling polymer quality during manufacturing is a significant challenge due to the cost, maintenance and reliability of online measurements of final product quality.
Controlling polymer quality during manufacturing is a significant challenge due to the cost, maintenance and reliability of online measurements of final product quality. Polymerization is highly nonlinear in nature, which poses great challenges for manufacturers to produce consistent quality product. In most cases, the quality measurement is done manually through sample lab analysis in post-production.
These challenges call for a real-time solution. Most manufacturing companies are adopting advanced digital technologies to optimize operations. Several open-source programming tools are available, along with machine learning (ML) and artificial intelligence (AI) algorithms and high-performanc
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