Statistical Process Control - A key tool for process understanding in the process validation life cycle

(Im Auftrag der European Compliance Academy)

Statistical Process Control - A key tool for process understanding in the process validation life cycle <p>(Im Auftrag der European Compliance Academy)

Heidelberg, Germany

Seminar Nr. 15592


Die Veranstaltung hat bereits stattgefunden

Rückfragen unter:
Tel.: 06221 / 84 44 0 E-Mail:


Dr Ingolf Stückrath, Sanofi-Aventis Frankfurt, Germany

Dr Sven Wedemeyer, Merck KGaA, Germany

Dr Björn Wiese, Zimmer GmbH, Switzerland


The new process Validation life cycle is now split up into 3 stages:

1. Process design
2. Process Qualification
3. Continued Process Verification

The new “catchword” is process understanding. Trends should be evaluated in the Stage 3.

One element to show process understanding and to monitor trends can be Statistical Process Control.

On the one hand the seminar will explain the theory of control charts e.g. how to calculate and read them. On the other hand the seminar will explore how to practically apply Control Charts, e.g. implementing control charts in production or QC and setting up a good review process. This balance of class room sessions and exercises supports a hands-on approach to manage and use Control Charts in different environments, like validation and process improvement.

Examples and case studies from the experience of the speakers will give evidence of the success and possibilities the use of Control Charts adds to your enterprise. Additionally, there is a view on the software for SPC and its GMP relevance.


With the FDA Guidance on Process Validation of January 2011 the FDA gives a new interpretation of validation. Not more than 3 validation batches are the evidence that a process is valid. The FDA now expects a validation life cycle with continued process verification throughout the commercial phase. Also the EMA stated in a Question and Answer paper, that they focus on continuous validation too. Both authorities mention that a process is in statistical control and capable. One element to show this is Statistical Process Control (SPC) as mentioned by the FDA.

Also in the ICH Q9 document “Quality Risk Management” control charts and process capability are mentioned as statistical possibilities within risk assessments.


This course is directed to staff who is involved in process understanding and optimization (e.g. process owners, validation managers, etc.) in R&D, production and quality control. It also addresses quality assurance staff.

Note: The number of participants is limited.


Six Sigma Definitions

  • A short introduction to Six Sigma
  • Six Sigma Terms
Objectives of Statistical Process Control
  • Create visibility of process performance
  • Increase process knowledge
  • Show process stability
  • Prove process capability
  • Support the continuous improvement process
Some mandatory Basic Statistics
  • Mean Value, Median, Range
  • Standard Deviation
  • Normal Distribution
  • Histogram and Time Series Plot
The two Types of Variability
  • Common cause variability
  • Special cause variability
Control Charts
  • Types of control charts
  • Design a control chart
  • Setting up control charts in Minitab®
  • Control limits and specification limits
  • Why is 3s taken as limit?
  • Changing control limits
Reading Control Charts to improve the Process
  • Statistical rules
  • Identifying patterns
  • Performance windows
  • General rules
Deploying and managing SPC - Connecting SPC to Continuous Improvement
  • Deployment Top-Down versus Bottom-Up
  • Root cause analysis
  • Paper based versus electronic control charts
  • Management system / cycle
Reasons to implement Control Charts
  • Link to quality control
  • Link to quality assurance
  • Benefits from SPC
Measurement System Analysis and SPC
  • Using control charts to do a MSA
  • Accuracy of data
  • Triangle of Variability
SPC as tool for Continued Process Verification
  • Continued Process Verification: Requirements
  • Case Study Sanofi-Aventis
Process Capability – What is the risk of failure of my process?
  • Cp, Cpk versus Pp, Ppk
  • Long term versus short term capability
  • Process robustness
Case Study Control Charts and Trending of Microbiological Data
  • Trending Monitoring Data as Part of the Facility
  • Control Concept
  • Smart Setting of Alert- and Action levels
  • Definition of Adverse Trends
  • Periodic Data Review
  • Designing a Reduced EM Program
Exercise 1
Control chart
Setting up a Control Chart and control a process to standard manually

Implementation of the use of a Control Chart in the local environment
What are the Dos and Don’ts?
How do I create commitment in senior management and my team?

Exercise 2
Control Chart
Detecting changes and analysing potential causes


GMP Seminare nach Thema

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