MSPC: A Window With Endless Views
Summary
MSPC applies multivariate statistics to process data where variables may be correlated. With real-time automatic data collection, it can generate a multivariate control chart that presents complex information in a single view.
It can support continuous manufacturing monitoring and help speed real-time release (RTR) when used with PAT. Instead of reviewing hundreds of univariate charts, MSPC considers correlation to detect out-of-control situations and support QbD work toward Industry 4.0.
Key takeaways
- MSPC combines multivariate methods with real-time data collection to build a multivariate control chart.
- It replaces “many charts” review with a single view that accounts for variable correlation and is more sensitive to out-of-control conditions.
- It supports continuous manufacturing monitoring, RTR, and multidimensional visualization when used with PAT, and it connects to QbD design-space work toward Industry 4.0.
Who is this for
- PAT Scientist / PAT Engineer
- Continuous Manufacturing Process Engineer
- MSAT (Manufacturing Science & Technology) Lead
- Process Control / Automation Engineer (manufacturing analytics and monitoring)
- Quality Release Lead or QA professional involved in RTR decisions
- Manufacturing Data Scientist / Statistician working with correlated process variables
- Process Development Engineer using QbD/design-space approaches
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MSPC: a Window with Endless Views
As time goes on, the Multivariate Statistical Process Control (MSPC) is becoming increasingly valued. This happens due to its importance and advantages towards statistical process control and continuous improvement.
The classical univariate control charts such as the Shewhart type or the Cumulative Sum allow a trend analysis of a particular attribute during batch production. In fact, with these types of graphical tools, it is possible to determine critical deviations on a variable level.
However, if you have a panel with 300 Shewhart control charts, it can become challenging to analyze them all.
This analysis would be possible nonetheless, since there are tools that can guide us through the process that can present the critical plots and present a higher number of deviations. However, it would be very difficult to analyze all those plots and collect relevant information from them simultaneously.
In this situation, for example, the MSPC comes to the rescue. It provides a single view for all attributes, considering variable correlation, rendering MSPC more sensitive to an out-of-control situation and simplifying the identification of major impact events.
MSPC can support a continuous manufacturing process monitoring and real-time release events (RTR)
Diving into the definition of MSPC reveals a methodology that enables the application of multivariate statistical techniques to analyze complex process data with potentially correlated variables. This, in combination with real-time automatic data collection, can be used to generate a multivariate control chart, enabling a simple view of the complex information set behind.
MSPC can support continuous manufacturing process monitoring, as well as expedite real-time release events (RTR), providing means to quickly analyze and follow an increased number of variables. When properly aligned with Process Analytical Technology (PAT), MSPC can provide a clear window for a complex multidimensional data visualization.
QbD Aligned Toward Industry 4.0
With the power of a multivariate analysis, projecting the effect of all variables into one design space, it becomes possible to observe the same information from a completely different angle, adding a new layer to the knowledge of the process.This allows a high dimensional preventive action in line with QbD framework implementation on the way to the industry 4.0.
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