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6. Step 4 - Six Sigma Implementation - Statistical Process Control

Step 4 - Six Sigma Implementation - Statistical Process Control

The step focuses on reducing variation in a stable process that is created in the first three steps. The objective is to increase predictability, quality and customer satisfaction. This is a long term strategy to improve performance by reducing variation.

At this stage statistical tools will be applied to analyses the performance of processes and products. In order to apply statistics, data is needed. Therefore at this stage it is important to have a performance measurement system in place that is able to deliver data of the process performance and at the level of the products that are produced.

Besides statistical tools Six Sigma also offers a structured approach for executing and improvement project. This approach is called the DMAIC roadmap which stand for define-measure-analyses-improve-control. Although the DMAIC roadmap finds its origin in six sigma, it can be applied to Lean projects as well. The approach is too complex though for smaller projects like Kaizen initiatives. For these type of projects it is recommend to follow the PDCA roadmap.

Rather than increasing quality with a step- by-step approach like Kaizen proclaims, Six Sigma focuses on quality break thorough improvement project. An improvement project will take a few weeks or a few months rather than a few days. As a consequence the Six Sigma approach is much more top- down driven than the Kaizen bottom-up approach.

Other Topics

What is Six Sigma?
Why does Lean Six Sigma Go Hand in Hand?
Step 1 - Setting the House in Order for Lean Six Sigma Transformation
Step 2 - Creating a Continuous Improvement Culture
Step 3 - Creating Predictable Processes
Step 4 - Six Sigma Implementation - Statistical Process Control
Step 5 - Design for Six Sigma (DfSS)
Short Interval Management
What is DMAIC?
What is Kaizen?