Statistical Process Control (SPC): The Use of SPC Using Control Charts to Maintain the Laboratory Compliance
Understanding Control Charts and Their Underlying Statistics!
Instructor :
John Fetzer
Webinar ID:
4683
Date: OCT 16, 2024 (WED)
Start Time: 10 am PT
Duration: 90 Mins.
What you will learn
- How to Understand Control Charts and Their Underlying Statistics
- How to Choose Variables to Monitor
- How to Maintain the Records and to Plan Adjustments
- How to Understand Control Charts and Their Underlying Statistics
- How to Choose Variables to Monitor
- How to Maintain the Records and to Plan Adjustments
- Examples and Walkthroughs of Control Chart Implementation and Use
- A review of the Relevant Statistics will also be Done
- Trends with Real Examples of Testing Problems and so much more..
Course Description
Under GLP only the occurrence of a 3-sigma result is used as a statistical sign for bad performance.
There are several others that are based on trends in data behaviors, such as non-randomness and a change in the spread of the data distribution.
These trends will be presented with real examples of testing problems that cause the trends. How to choose what is monitored and how to create a new control chart will be taught.
Join Now!
Under GLP only the occurrence of a 3-sigma result is used as a statistical sign for bad performance.
There are several others that are based on trends in data behaviors, such as non-randomness and a change in the spread of the data distribution.
These trends will be presented with real examples of testing problems that cause the trends. How to choose what is monitored and how to create a new control chart will be taught.
Join Now!
Why you should attend
Compliance under GLP can be difficult. Setting up a system to monitor the 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 behavior 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 helpful.
Guidelines for excellent or unacceptable behavior are well known. The most common are Nelson Rules, in use for over a century. With a wise selection of the variables to monitor, assessing performance can be simple.
Enroll Now!
Compliance under GLP can be difficult. Setting up a system to monitor the 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 behavior 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 helpful.
Guidelines for excellent or unacceptable behavior are well known. The most common are Nelson Rules, in use for over a century. With a wise selection of the variables to monitor, assessing performance can be simple.
Enroll Now!
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
- Examples and Walkthroughs of Control Chart Implementation and Use
- A review of the Relevant Statistics will also be Done
- Trends with Real Examples of Testing Problems and so much more..
- How to Understand Control Charts and Their Underlying Statistics
- How to Choose Variables to Monitor
- How to Maintain the Records and to Plan Adjustments
- Examples and Walkthroughs of Control Chart Implementation and Use
- A review of the Relevant Statistics will also be Done
- Trends with Real Examples of Testing Problems and so much more..
Who is this course for
- Managers, Quality Professionals, Engineers
- Lab Chemists
- Lab Managers
- Lab Technicians
- Lab Analysts
- Industries into Compliance Methodology (Biotech, Pharma)
- Companies into Environmental Compliance or EPA
- Managers, Quality Professionals, Engineers
- Lab Chemists
- Lab Managers
- Lab Technicians
- Lab Analysts
- Industries into Compliance Methodology (Biotech, Pharma)
- Companies into Environmental Compliance or EPA
Instructor Profile
John C. Fetzer, has had over 30 year experience in HPLC methods development. He has authored or co-authored over 50 peer-reviewed papers on liquid chromatography, has served on the editorial advisory boards of the Journal of Chromatography, Analytical Chemistry, and Analytical and Bioanalytical Chemistry.
