Statistical Process Control

Statistical Process Control Workshop

Participants will study the 6 M’s of variation and the means to eliminate and/or abate them. The class will learn and develop attibute and variable control charts. Other tools that will be discussed are: cause and effects diagrams, simple linear regression analysis, Analysis of Variance (ANOVA), and pre-control. Emphasis will be placed on when, why, and which charts to use as well as how to solve/graph the data. Classroom workshops will be conducted to enable students to exercise what they have learned.

Data can tell you how well your process is doing or how badly. Your process may have too much variation in it because of special causes. SPC can tell you when to investigate these causes. SPC control charts will help you and your team decide if the variation comes from special causes or common causes.

Objectives:
In this course you will: identify the purpose of and advantages of using SPC to control a process, learn what SPC is and how it differs from the usual method of quality control, identify the difference between quality control by inspection versus prevention, be able to classify data as either discrete or continuous and identify and define the variation in the data as either common causes or special causes.

The intent of this course is to provide a brief overview on the use of Minitab for new users. It is not for nor will you become a "power user" of Minitab at the end of this course.

Objectives:
In this course you will: launch the program and understand the key features of the various windows and menus used to perform exploratory data analysis, understand the various functions of the Menu Bar, Tool Bar, Session Window and Data Window, populate a Minitab worksheet and perform basic graphical and numerical data analysis and save the various outputs in different formats for use by other programs.

SPC can be thought of as the mother concept for Six Sigma. SPC can be used in virtually any situation where you need to understand and analyse a process from base lining current performance, through evaluating measurement systems, comparing before and after improvement to the provision of on going process controls. This course is aimed at giving delegates a thorough understanding of control chart principles, the different types of charts , their application and how to interpret control charts to identify common and special causes of variation.

Objectives
This two day course which includes a number of group exercises based on both manufacturing and service examples will enable Six Sigma Green and Black Belts to understand:

The principles and application of control charts in a Six Sigma environment.

How to develop a variety of control charts dealing with variable and attribute data.

How to interpret control charts and identify common and special cause of variation.

How to manage out-of-control processes.

The steps required to implement control charts for a particular process.


Course Content
Introduction and key principles

Process control using variables

X bar and R charts

Individuals charts

Multi-variate charts

Moving mean, range and exponentially weighted moving average charts

Charts for Standard Deviation

Techniques for Short and Small Runs


Process control for attributes

np charts

p charts

c charts

u charts


Cumulative sum (cusum) charts

Analysing control charts

Managing out of control processes

Control charts and process capability

Implementing control charts

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