BO 205

BO 205 – JMP Training : Advanced Statistical Process Control – 2 days

Statistical process control is a statistically-based family of tools used to monitor, control and improve processes. However, selecting and setting up the right type of SPC control chart for a given process is crucial to getting the most benefit from statistical process control.

Developing a comprehensive understanding of advanced statistical process control techniques can take months or even years and often involves building an extensive library of SPC books and reference materials. But now, all of the information needed to achieve a thorough understanding of SPC is contained in this compact yet comprehensive course. By using the Advanced SPC online training course, your Six Sigma Black Belts or lean manufacturing in-house experts can learn how to apply advanced statistical techniques and concepts throughout your operation.

Key learning points:
Understand the concepts of advanced SPC
Navigate the JMP Advanced SPC interface
Setting up real time advanced control chart through JMP software
Triggering of process violation rules
Effective root cause analysis through JMP software
Interpretation of analysis results

Training Approach
This practical course combines classroom teaching, practical exercises, and group discussion with actual factory based projects to provide a complete action learning experience. The course has been designed to enable all participants leave the training room with a set of new knowledge, tools, skills and direct experience of how to use JMP software for advanced statistical process control in a real company setting.

Prerequisite: Statistical Data Analysis Through JMP Software, Quality Control and Statistical Process Control
Training facilities: Computer installed with JMP software and LCD projector

Course contents :

Section 1 : Review of basic SPC
Assumptions that underly Shewhart Charts
SPC common mistakes
Issues in sampling and rational subgrouping
Issues in dealing with non-normal and independent data

Section 2 : Statistical techniques to determine sampling size and interval
Average Run Length (ARL) characteristics
Statistical techniques to determine sampling size and interval
Consideration of economic and manufacturing factors
When to shorten sampling interval
Zone rules / Western Electric rules to increase sensitivity
Rational subgroup concept
What is autocorrelation ?
Practical application exercise

Section 3 : Cumulative Sum (CUSUM) Control Chart
What is a CUSUM ?
The features and application of CUSUM
CUSUM vs normal control chart
V-mask and algorithmic CUSUM
The procedure to construct CUSUM control chart
Practical application exercise through JMP software


Section 4 : EWMA and UWMA control chart
Understanding of concepts
The features and application
The procedure to construct EWMA UWMA chart
Interpretation of results
Practical application exercise through JMP software

Section 5 : Other Advanced Control Chart
Levey Jennings control chart
Presummarize control chart
Multivariate control chart
Understanding of basic concepts
The features and application
Interpretation of results
Practical application exercise through JMP software

Section 6 : Handling of Non-normal data & advanced root cause analysis
The consequences of using non-normal data
The features of non-normal data
Techniques to identify non-normal data
Various transformation methods (graphical & numerical analysis)
Cpk calculation & establishment of SPC for non-normal data
Statistical tools for advanced root cause analysis
Practical application exercise through JMP software

Who should attend: Managers, engineers, executives and supervisors who will use JMP software to perform advanced process capability study and SPC implementation.

Delivery: Classroom lecture, hands-on practice, assignments and case studies.

Duration: 2 days (9am – 5pm)

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