In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...

Multivariate testing, with its many combinations, creative needs, and more demanding implementation, is a great place for larger organizations to implement more rigorous processes. Testing helps build ...

Five case studies show how diagnostic data used with multivariable process data increases process efficiency and uptime. Instrumentation selection for plant applications is a multistep process, ...

Monitoring the manufacturing process becomes a challenging task with a huge number of variables in traditional multivariate statistical process control (MSPC) methods. However, the rich information is ...

Multivariate data analysis (MVDA) is being used to effectively handle complex datasets generated by process analytical technology (PAT) in biopharmaceutical process development and manufacturing.

Validating drug production processes need not be a headache, according to AI researchers who say machine learning (ML) could be a single answer to biopharma’s multivariate problem. The FDA defines ...

Validating drug production processes need not be a headache, according to AI researchers, who say machine learning could be a single answer to biopharma’s multivariate problem. The FDA defines process ...