MiC Quality: SIX SIGMA eLearning in SPC, DOE, MSA Measurement Systems Analysis (MSA/ Gage R&R)
Statistical Process Control (SPC)
Design of Experiments (DOE)
Six Sigma, six sigma methodology, six sigma training, six sigma approach, six sigma black belt, six sigma job, six sigma quality, six sigma certification, six sigma green belt
Home | Contact | SPC | DOE | MSA | Statistics | Excel | Books | License | Enroll Online Six Sigma Training

:: MiC Quality: Statistical Process Control (SPC)


Six Sigma Courses Instructor:  Glen Netherwood
e-Learning

Glen Netherwood


:: SPC Course Summary

- 3 ASQ RUs
- self-paced, interactive
- 4 weeks of access
- 2 weeks free extension
- 30 hours of work
- 24/7 individual support
- certificate of completion
- cost:
~US$190/ =AUS$275/~UK£130)
- recommended books



TRY FREE PRIMER
ENROLL
LOGIN

Introduction

Welcome to the online course in Statistical Process Control (SPC). After completing this course you will understand the fundamental concepts of SPC, and be able to apply them in practice.

The SPC course is interactive, it includes frequent exercises and activities. Please carry them out. Even if you think you understand the material, the exercises might reveal things you haven't considered, and will prepare you to apply the methods in your job.

If you want to get the full benefit you should allow about 30 hours to work through all course material.

You will also have full individual email support. Please don't hesitate to use it, I always welcome questions and look forward to hearing from you. You can ask about anything that isn't clear, or you can discuss how you can apply SPC to your work processes. I can often suggest approaches that go beyond the course material.

I will welcome you as one of our students.

Glen Netherwood
MiC Quality

:: Overview

The online course in Statistical Process Control is intended for quality practitioners, engineers and managers who are responsible for introducing and using SPC. Statistical Process Control is used by many industries to monitor the performance of their processes.

Statistical Process Control is easy to use. It is based on simple charts that can be kept up to date, and interpreted with a minimum of training. It is also easy to computerize, and many excellent software packages are available.

Despite its simplicity, SPC is based on sound and subtle statistical concepts. These are often misunderstood leading to SPC being used incorrectly and give misleading results. Managers and engineers responsible for the operation and implementation of SPC should be sure they understand it properly.

Statistical Process Control is about identifying process changes quickly, but not overreacting to normal part-to-part Variation. The first section of our SPC course explores 'process variation', ways of measuring it, and the distinction between 'common' and 'special causes'. It also emphasizes the importance of Normal Distribution.

After becoming familiar with variation, we move on to 'Process Capability' and 'process performance'. These are important requirements of supplier accreditation systems and powerful tools in predicting process yield. They also help to identify opportunities for process improvement.

The next section covers Control Charts for Variables. I've approached control charts by building up from run charts. This allows me to emphasize the importance of subgroups in separating process accuracy and process precision. We then go on to look at how to apply control charts in practice, and how to interpret the results from control charts.

The fourth, and final, section covers Control Charts for Attributes. By now you are familiar with control charts and will have little difficulty grasping the principles and operation of this type of control chart.

After completing the course you will be able to apply Statistical Process Control effectively in your workplace. You will also be able to interpret the results from SPC systems properly, avoiding common misconceptions and using them to identify opportunities for process improvement.

Measurement Systems Analysis (MSA/ Gage R&R) | Statistical Process Control (SPC) for TS16949 and SIX SIGMA Training
Design of Experiments (DOE) for Process Improvement and SIX SIGMA Training
Copyright 2008 MiC Quality Legal Notices and Privacy Statement   Top