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==Introduction== | ==Introduction== | ||
Batch Statistical Process Control (BSPC) is the analysis of process data where the process inherently loops of "batches" | Batch Statistical Process Control (BSPC) is the analysis of process data where the process inherently loops of "batches". | ||
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==Experiment Designer Window== | ==Experiment Designer Window== | ||
The goal of the Batch Processor interface is to make it easier to assemble “batch” data for multivariate analysis. Because different analyses and conditions require different data manipulation, assembling data for batch analysis can be very difficult and [[media:Bspc_diagram_roadmap.png | complicated]]. | |||
Revision as of 10:24, 24 August 2012
Introduction
Batch Statistical Process Control (BSPC) is the analysis of process data where the process inherently loops of "batches".
Model Types
| Model | Modes (Dimensions) | Equal Length Batches | Steps Aligned | Comments |
|---|---|---|---|---|
| Summary PCA | 2 | No | No | Orientation = batches x (step/summary) |
| Batch Maturity | 2 | No | No | Can have Y-Block to indicate maturity |
| MPCA | 3 | Yes | Yes | |
| PARAFAC | 3 | Yes | Yes | |
| Summary PARAFAC | 3 | No | No | Orientation = batches x step x summary |
| PARAFAC2 | 3 | No | No |
Experiment Designer Window
The goal of the Batch Processor interface is to make it easier to assemble “batch” data for multivariate analysis. Because different analyses and conditions require different data manipulation, assembling data for batch analysis can be very difficult and complicated.
