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.

Areas Covered

How to understand control charts and their underlying statistics, how to choose variables to monitor, how to maintain the records and to plan adjustments. There will be examples and walkthroughs of control chart implementation and use. A review of the relevant statistics will also be done

Who Should Attend

Chemists and laboratory assistants who perform analyses under GLP or ISO 17025.

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.

Setting up intermediate monitoring of key stages in the methodology can observe deviations from the desired behavior before a non-compliance occurs. How to choose these is individual to each?.