Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 1 ICH Q9 QUALITY.

Slides:



Advertisements
Similar presentations
Quality control tools
Advertisements

Design of Experiments Lecture I
Descriptive Measures MARE 250 Dr. Jason Turner.
Control Charts for Variables
1 Manufacturing Process A sequence of activities that is intended to achieve a result (Juran). Quality of Manufacturing Process depends on Entry Criteria.
S6 - 1© 2011 Pearson Education, Inc. publishing as Prentice Hall S6 Statistical Process Control PowerPoint presentation to accompany Heizer and Render.
BPT2423 – STATISTICAL PROCESS CONTROL
©2014 IDBS, Confidential Statistical Process Control Workshop An Introduction to the Principles behind SPC Ilca Croufer.
Seven Quality Tools The Seven Tools
Mitigating Risk of Out-of-Specification Results During Stability Testing of Biopharmaceutical Products Jeff Gardner Principal Consultant 36 th Annual Midwest.
Chapter 5. Methods and Philosophy of Statistical Process Control
Agenda Review homework Lecture/discussion Week 10 assignment
Introduction to Control Charts.
Copyright (c) 2009 John Wiley & Sons, Inc.
S6 - 1© 2011 Pearson Education, Inc. publishing as Prentice Hall S6 Statistical Process Control PowerPoint presentation to accompany Heizer and Render.
© 2008 Prentice Hall, Inc.S6 – 1 Operations Management Supplement 6 – Statistical Process Control PowerPoint presentation to accompany Heizer/Render Principles.
Tools of quality control A-Team. Basic tools of quality control  control chart  histogram  Pareto chart  check sheet  cause-and-effect diagram 
Chapter 8: Quality Management Project Quality Management
8-1 Quality Improvement and Statistics Definitions of Quality Quality means fitness for use - quality of design - quality of conformance Quality is.
Control Charts for Variables
Copyright © 2014 by McGraw-Hill Higher Education. All rights reserved. Essentials of Business Statistics: Communicating with Numbers By Sanjiv Jaggia and.
Total Quality Management BUS 3 – 142 Statistics for Variables Week of Mar 14, 2011.
15 Statistical Quality Control CHAPTER OUTLINE
Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 1 ICH Q9 QUALITY.
Quality Risk Management ICH Q9 Annex I: Methods & Tools
The Bell Shaped Curve By the definition of the bell shaped curve, we expect to find certain percentages of the population between the standard deviations.
Statistical Process Control
TTMG 5103 Module Techniques and Tools for problem diagnosis and improvement prior to commercialization Shiva Biradar TIM Program, Carleton University.
Quality Control McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
THE MANAGEMENT AND CONTROL OF QUALITY, 5e, © 2002 South-Western/Thomson Learning TM 1 Chapter 12 Statistical Process Control.
Quality Control Tools A committee for developing QC tools affiliated with JUSE was set up in April Their aim was to develop QC techniques for.
Census A survey to collect data on the entire population.   Data The facts and figures collected, analyzed, and summarized for presentation and.
Chapter 36 Quality Engineering Part 2 (Review) EIN 3390 Manufacturing Processes Summer A, 2012.
Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 1 ICH Q9 QUALITY.
Statistical Process Control Chapters A B C D E F G H.
6.1 What is Statistics? Definition: Statistics – science of collecting, analyzing, and interpreting data in such a way that the conclusions can be objectively.
Worked examples and exercises are in the text STROUD PROGRAMME 27 STATISTICS.
Chapter 2 Describing Data.
Quality Control Lecture 5
Welcome to MM305 Unit 8 Seminar Diallo Wallace Statistical Quality Control.
Statistical Process Control (SPC)
1 Chapter 3 Looking at Data: Distributions Introduction 3.1 Displaying Distributions with Graphs Chapter Three Looking At Data: Distributions.
Seven Quality Tools The Seven Tools –Histograms, Pareto Charts, Cause and Effect Diagrams, Run Charts, Scatter Diagrams, Flow Charts, Control Charts.
Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 1 ICH Q9 QUALITY.
Measures of central tendency are statistics that express the most typical or average scores in a distribution These measures are: The Mode The Median.
FREQUANCY DISTRIBUTION 8, 24, 18, 5, 6, 12, 4, 3, 3, 2, 3, 23, 9, 18, 16, 1, 2, 3, 5, 11, 13, 15, 9, 11, 11, 7, 10, 6, 5, 16, 20, 4, 3, 3, 3, 10, 3, 2,
Project quality management. Introduction Project quality management includes the process required to ensure that the project satisfies the needs for which.
Statistical Process Control
QUALITY MANAGEMENT TOOLS. COMPREHENSIVE QUALITY MANAGEMENT PROGRAM EQUIPMENT QUALITY CONTROL ADMINISTRATIVE RESPONSIBILITIES RISK MANAGEMENT RADIATION.
Quality Improvement Tools CHAPTER SIX SUPPLEMENT McGraw-Hill/Irwin Copyright © 2011 by the McGraw-Hill Companies, Inc. All rights reserved.
Annex II: Potential Applications prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 1 ICH Q9.
1 SMU EMIS 7364 NTU TO-570-N Control Charts Basic Concepts and Mathematical Basis Updated: 3/2/04 Statistical Quality Control Dr. Jerrell T. Stracener,
Quality Control  Statistical Process Control (SPC)
1 Project Quality Management QA and QC Tools & Techniques Lec#10 Ghazala Amin.
The seven traditional tools of quality I - Pareto chart II – Flowchart III - Cause-and-Effect Diagrams IV - Check Sheets V- Histograms VI - Scatter Diagrams.
Why do we analyze data?  It is important to analyze data because you need to determine the extent to which the hypothesized relationship does or does.
10 March 2016Materi ke-3 Lecture 3 Statistical Process Control Using Control Charts.
1 Collecting and Interpreting Quantitative Data Deborah K. van Alphen and Robert W. Lingard California State University, Northridge.
Chapter 51Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012 John Wiley & Sons, Inc.
Annex II: Potential Applications prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 1 ICH Q9.
Chapter 7 Process Control.
Process Capability and Capability Index
Statistical Process Control
Agenda Review homework Lecture/discussion Week 10 assignment
Process Capability Process capability For Variables
Process Capability.
3. Use an in-line sensor to sense when the effects of tool wear...
DESIGN OF EXPERIMENT (DOE)
BENEFITS OF AUTOMATED SPC
Presentation transcript:

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 1 ICH Q9 QUALITY RISK MANAGEMENT Annex I.9 Supporting statistical tools

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 2 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools  Control Charts (for example): >Shewhart Control Charts (see ISO 8258) >Control Charts with Arithmetic Average and Warning Limits (see ISO 7873) >Acceptance Control Charts (see ISO 7966) >Cumulative Sum Charts (ISO 7871) >Weighted Moving Average  Design of Experiments (DOE)  Pareto Charts  Process Capability Analysis Aid for: - Effective data assessment - Aid in determining the significance of the data set(s) ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 3 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control charts (ISO 7870)  Indicates the range of variability that is built into a system  Shows statistically determined upper and lower control limits drawn on either side of the process average  The bounds of the control chart are marked by upper and lower control limits >Calculated by applying statistical formulas to data >Data points that fall outside these bounds represent variations due to special causes >Can be found and eliminated  Improvements require changes in the process ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 4 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control charts Potential Areas of Use(s)  Monitoring critical parameters  Provides information to determine >Process capability >Variability >Control  Some charts are dealing with warning limits or trend analysis Example ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 5 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control Chart: Shewhart Control Charts (ISO 8258)  Use warning limits  Analysis trend patterns Example Potential Areas of Use(s)  Statistical control of the process ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 6 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control Charts with Arithmetic Average and Warning Limits (ISO 7873)  A control chart with warning and action limits Potential Areas of Use(s)  Enable a base period of quality measure  Provide a basis for the construction of relationships between a process and product quality  Producing recommendations for the adjustment of the process  Can be applied with process Analytical technology tools ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 7 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control Chart: Acceptance Control Charts (ISO 7966)  Chart with a central line within an acceptable process zone  Ideal the average should be the target value Potential Areas of Use(s)  During regular batch manufacturing can give guidance for determine sample size, action limits and decision criteria  Ongoing improvements under process robustness/six sigma program can be initiated ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 8 ICH Q9 QUALITY RISK MANAGEMENT Compilation of limits and ranges EXAMPLE S. Rönninger, Roche

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 9 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control Charts: Cumulative Sum Charts (ISO 7871)  Sum of deviations from the mean or predefined value and plot against time or number of occurrences (e.g. V-mask)  Determines if a monitored process is changing  They will detect shifts of.5 sigma to 2 sigma in about half the time of Shewhart charts with the same sample size

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 10 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control Charts: Cumulative Sum Charts (ISO 7871) Potential Areas of Use(s)  Analyze process parameters or analytical results (e.g. PAT)  Allow the detection of slight discrepancies in a process before a trend is visible using other control charts Example ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 11 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control Charts: Cumulative Sum Charts (ISO 7871) EXAMPLE Assay

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 12 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Control Chart: Weighted Moving Average  A simple, or arithmetic, moving average is calculated by adding the closing results of the security for a number of time periods and then dividing this total by the number of time periods Potential Areas of Use(s)  Analyze process parameters or analytical results (e.g. PAT)  Allow the detection of slight discrepancies in a process before a trend is visible using other control charts ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 13 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Design of Experiments (DoE)  Design experiments based on statistical considerations  Analyze data and results to determine >establish key parameters >process variables >explore potential interactions

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 14 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Design of Experiments (DOE) Potential Areas of Use(s)  Research and development area  Retrospective evaluation of established parameters (Proven Acceptable Ranges  Systematically choosing certain combinations of variables it is possible to separate their individual effects  A special variant: focus on optimizing design parameters to minimize variation BEFORE optimizing design to hit mean target values for output parameters ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 15 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Design of Experiments (DOE) in a submission  Type of experimental design used e.g. full/ fractional factorial  Justification of the selection of factors and responses  As an appendix >Number and levels of factors under study >The experimental matrix with the values of the responses for each combination of factors  Graphical representation >Coefficient plot of the relative significance of the factors under study and interactions between them Reflection paper on…PAT: EMEA/INS/277260/2005, March 20, 2006 EXAMPLE

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 16 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Design of Experiments (DOE) in a submission  Statistical evaluation of the model derived from DoE (e.g. ANOVA table)  Graphical representation of the relationship of the significant factors under study with the responses (e.g. response surface and contour plots) providing a clear overview of the conclusions.  The Design Space (based on real test results and/or on the model) as defined in ICH Q8 should be described  Verification of the model derived from DoE Reflection paper on…PAT: EMEA/INS/277260/2005, March 20, 2006 EXAMPLE

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 17 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Pareto Charts  Created by plotting the cumulative frequencies of the relative frequency data in descending order  The most essential factors for the analysis are graphically apparent, and in an orderly format Potential Areas of Use(s)  Identify those factors that have the greatest cumulative effect on a system  Few important factors in a process: Screen out the less significant factors ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 18 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools  Pareto Chart EXAMPLE

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 19 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Process Capability Analysis  Estimate the potential percent of defective product

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 20 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Process Capability Analysis Potential Areas of Use(s)  Monitor / measure process variability  Analyze data retrospectively >Annual Product Review  Determine the relationship between process variability and specification  Requirement: Process specific data  Tool for both regulator and industry ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 21 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Histogram  A simple, graphical view of accumulated data >including its dispersion and central tendency  Provide the easiest way to evaluate the distribution of data Example Process compatibility ICH Q9

Annex I: Methods & Tools prepared by some members of the ICH Q9 EWG for example only; not an official policy/guidance July 2006, slide 22 ICH Q9 QUALITY RISK MANAGEMENT I.9: Supporting statistical tools Scatter diagrams (x/y-diagram)  To depict the influence that one variable has on another  Usually displays points representing the observed value of one variable corresponding to the value of another variable  How to perform: plot two parameters x and y in a two dimensional way ICH Q9