Batch processes are common in many industries. Typically, raw materials are combined in a suitable batch vessel before chemical, physical or biological transformation takes place. In many cases the batch process control is recipe-driven and operations are not adjusted to accommodate raw material variation, changes in uncontrollable factors and other changing circumstances. The optimal end product quality can be achieved by adapting batch operations to any detectable changes during processing, thus providing a control mechanism to drive the product towards its desired state.
Dr. Frank Westad, Chief Scientific Officer at CAMO Software, says, “Our approach to batch modeling overcomes fundamental challenges in formatting batch data prior to analysis. The methodology handles uneven batch lengths and different starting points by modeling the data in relative time. This provides users with a better and more accurate tool when working with batch data, especially when monitoring new batches in real time to detect out-of-spec situations.”
CAMO has developed an improved batch modeling approach using Principal Component Analysis, accommodating uneven batch lengths and different chemical or biological starting points. The method models the data in relative time and is also independent of the actual sampling rate between the batches.
Key benefits that can be achieved from using Unscrambler® X Batch Modeling include:
Model batch progression in relative time
Ability to model independent of sampling time
No need to force batches to a common length
Identify similarities of batches
Batch Modeling is a plugin module for The Unscrambler® X and is also ready to use with CAMO’s process monitoring solution, Unscrambler® X Process Pulse II.
