Efficient Calibration Process and Big Data

View latest talks on Big Data and Calibration Process Efficiency.

 

 

 

 

Harnessing Big Data – AiChE 2020

Big Data implies a systematic approach to extracting information from multiple, byte-dense data sources. Effective extraction of this information leads to improvements in decision making at all levels of industry. Here, we combine traditional approaches in statistics, database organization, pattern recognition, and chemometrics with some newer concepts tied to data mining, neurocomputing, and machine learning. The cost is low and the benefits are high.

The Multivariate Process Paradigm – SciX 2020

This is a summary of a chemical processing consortium, established eight years ago to re-evaluate how the calibration process for sensors and analyzers could be managed more efficiently. The focus is on optical spectrometers to enable a shift from current practices to approaches that take advantage of the computational power at our fingertips. It was critical to prioritize solutions that are non-disruptive, utilize legacy systems, and lessen the workload rather than layer on additional requirements. The result is a choice of tools available to consume the data and generate actionable, process-specific information.