Subscriber only lesson.
Sign up to this course to view this lesson.
About this lesson
Variation leads to uncertainty in process performance which requires extra management and buffers elsewhere in the business environment. One of the primary goals of a Lean Six Sigma project is to identify sources of variation in process performance and eliminating or reducing those sources of variation.
When to use
All processes have variation. Every Lean Six Sigma project should be seeking to identify sources of variation and reduce or eliminate those sources. This is one of the fundamental purposes of a project.
Since all processes have variation, an objective of Lean Six Sigma projects is to identify the variation and its sources so that these can be reduced or eliminated. Understanding the variation is part of understanding process stability. A process is considered stable if the variation is predictable. The process managers can then allow for the variation and optimize the overall system relative to the levels of variation in each of the process steps.
One of the techniques used to understand the impact of variation is the Taguchi Loss Function. Dr. Taguchi challenged the common approach to quality that was being used in the 1980s, which was that if the process result was within the allowable specification limits, the quality was good, and if it was outside the limits, the quality was bad. Dr. Taguchi believed that whenever the process performance was missing the ideal target, that losses in the system occurred. Those losses increased rapidly the further the deviation was from ideal process performance.
He created an equation to show this relationship:
Loss = k (y-m)2
- Where Loss is the system loss of both actual failures and errors and the additional costs to the system that are needed to accommodate the uncertainty from large deviations
- k is a factor that represents the cost structure of the system
- y is the actual process output
- m is the target process output
As you can see, this is the equation for a parabola. As the process output deviates from the target, the loss increases. This occurs regardless of where the upper and lower specification limits are located.
Dr. Taguchi would plot this function with the normal process output to show that if the variation was very small, there was little loss to the system, but as the variation grew, the losses grew, even if the process performance was within specification.
This illustrates the need for very little variation and demonstrates the power of the process sigma measurement. Sigma is a measure of the spread or variation within a process. Virtually all of the process output occurs between approximately minus 3 ½ sigma to plus 3 ½ sigma. The six sigma objective is to reduce the sigma value enough in order for the range from minus 6 sigma to plus 6 sigma to fit within the allowable specification limits.
Of course this has some implications. These include that the process is stable and predictable, that the process can be centered on the target value, and that the process can be controlled so that it does not drift.
Hints & tips
- Variation is the enemy of stability. When analyzing a process, strive to identify all sources of variation – don’t assume some of them away.
- A six sigma process can drift one or two sigma in either direction and still have virtually a 100% yield. If the sigma level is only about 3 to 3 ½, even a slight drift higher or lower will immediately start to create scrap or rework conditions.
- Often the largest of the system losses described by Dr. Taguchi occur in downstream processes that must add inspections or design robustness to accommodate a wide range of inputs.
Lesson notes are only available for subscribers.
PMI, PMP and PMBOK are registered marks of the Project Management Institute, Inc.