Why Should You Attend:
Compliance under GLP can be difficult. The setting up of a system to monitor performance of methods and instruments can lessen this. Statistical Process Control (SPC) uses control charts and statistical guidelines to monitor a wide variety of things in the compliant laboratory. These generate a proactive system to assess problems early on and quickly to be handled by adjustments rather than the strict situation of a non-compliance event.
Control charts are based on the normal distribution of data expected in a laboratory operation, the Gaussian distribution of occurrences. There are well defined probabilities for the data. Whether it is the overall performance of a test method, the performance of a device or instrument, the behaviour of a calibration curve, the peak shapes in chromatography, or many other variables, the maintenance of good performance and the observation of statistically unlikely patterns can be useful. Guidelines for good or unacceptable behaviour are well known. The most common of these are Nelson Rules, in use for over a century. With wise selection of the variables to monitor, assessing performance can be simple.
In this webinar, learn how to maintain compliance in the laboratory using Statistical Process Control (SPC) Using Control Charts.
Areas Covered in the Webinar:
How to understand control charts and their underlying statistics
How to choose variables to monitor
How to maintain the records
How to plan adjustments
Examples and walkthroughs of control chart implementation and use
Review of the relevant statistics
Compliance under GLP can be difficult. The setting up of a system to monitor performance of methods and instruments can lessen this. Statistical Process Control (SPC) uses control charts and statistical guidelines to monitor a wide variety of things in the compliant laboratory. These generate a proactive system to assess problems early on and quickly to be handled by adjustments rather than the strict situation of a non-compliance event.
Control charts are based on the normal distribution of data expected in a laboratory operation, the Gaussian distribution of occurrences. There are well defined probabilities for the data. Whether it is the overall performance of a test method, the performance of a device or instrument, the behaviour of a calibration curve, the peak shapes in chromatography, or many other variables, the maintenance of good performance and the observation of statistically unlikely patterns can be useful. Guidelines for good or unacceptable behaviour are well known. The most common of these are Nelson Rules, in use for over a century. With wise selection of the variables to monitor, assessing performance can be simple.
In this webinar, learn how to maintain compliance in the laboratory using Statistical Process Control (SPC) Using Control Charts.
Areas Covered in the Webinar:
How to understand control charts and their underlying statistics
How to choose variables to monitor
How to maintain the records
How to plan adjustments
Examples and walkthroughs of control chart implementation and use
Review of the relevant statistics
