Key Points

• Variation can arise in any production line.
• Figuring out if your variances conform to production specifications is vital.
• You can have variances, as long as they fit quality standards and specifications.

It is well established that there exist eight dimensions of quality:

1. Conformance
2. Performance
3. Features
4. Reliability
5. Durability
6. Serviceability
7. Aesthetics
8. Perceived quality

Each dimension can be explicitly defined and is self-exclusive from the other dimensions of quality. A customer may rate your service or product high in conformance, but low in reliability. Or they may view two dimensions to work in conjunction with each other, such as durability and reliability.

This article will discuss the dimension of conformance and how process variation should be interpreted. Process variation is important in the Six Sigma methodology because the customer is always evaluating our services, products, and processes to determine how well they are meeting their critical to quality (CTQs); in other words, how well they conform to the standards.

Understanding Conformance

Conformance can simply be defined as the degree to which your service or product meets the CTQs and predefined standards. For this article, it should be noted that your organization’s services and products are a function of your internal processes, as well as your supplier’s processes. (We know that everything in business is a process, right?)

Here are a few examples:

1. You manufacture tires and the tread depth needs to be 5/8 inch plus or minus 0.05 inch.
2. You approve loans and you promise a response to the customer within 24 business hours of receipt.
3. You write code and your manager expects less than five bugs found over the life of the product per thousand lines of code written.
4. You process invoices for healthcare services and your customers expect zero errors on their bills.

A simple way to teach the concept of how well your service or product conforms to the CTQs is with a picture of a target. A target, like those used in archery or shooting, has a series of concentric circles that alternate color. In the center of the target is the bullseye.

When services or products are developed by your organization, the bullseye is defined by CTQs, the parts are defined by dimensional standards, and the materials are defined by purity requirements. As we see from the four examples above, the conformance CTQs usually involve a target dimension (the exact center of the target), as well as a permissible range of variation (center yellow area).

In Figure 1, three pictures help explain the variation in a process. The picture on the left displays a process that covers the entire target. While all the bullets appear to have hit the target, very few are in the bullseye. This is an example of a process that is centered around the target, but very seldomly meets the CTQs of the customer.

The middle picture in Figure 1 displays a process that is well grouped on the target (all the bullets hit the target near each other) but is well off target. In this picture – like in the first picture – almost every service or product produced fails to meet the customer’s CTQs.

The far right picture in Figure 1 displays a process that is well grouped on the target, and all the bullets are within the bullseye. This case displays a process that is centered and is within the tolerance of the customer CTQs.

Because this definition of conformance defines “good quality” with all of the bullets landing within the bullseye tolerance band, there is little interest in whether the bullets are exactly centered. For the most part, variation (or dispersion) within the CTQ specification limits is not an issue for the customer.

Is Variation Normal?

Variation is going to occur in your processes, regardless of safeguards. Don’t fret, that’s a normal occurrence. However, learning how this relates both to customer specifications and your internal control limits for acceptable quality is key. As such, variation is going to happen, but it might be out of spec with the limits you’ve placed.

Relating the Bullseye to Frequency Curves

In the real world, we seldom view our processes as bullseyes (unless we work at a shooting range). So how can you determine if your process is scattered around the target, grouped well but off the bullseye, or grouped well on the bullseye? We can display our data in frequency distributions showing the number (percentage) of our process outputs having the indicated dimensions.

One can easily see the direct relationship of Figure 2 to Figure 1. In Figure 2, the far left picture displays a wide variation that is centered on the target. The middle picture shows little variation but is off-target. And the far right picture displays little variation centered on the target. Shaded areas falling between the specification limits indicate process output dimensions meeting specifications; shaded areas falling either to the left of the lower specification limit or to the right of the upper specification limit indicate items falling outside specification limits.

Interpreting Process Variation

Most Black Belts have little time to completely understand the variation of their process before they move into the improvement phase of DMAIC (Define, Measure, Analyze, Improve, Control). For instance, does the critical X‘s of your process have a larger impact on variation (spread) or central tendency (centering)? Segmentation or subgrouping the data can help you find the correct critical X. Hypothesis testing will help you prove that it is so.

Other Useful Tools and Concepts

What we’ve covered today isn’t the only thing you need to keep in mind with variations. Learning about special cause variations is going to make or break your business. These are unforeseen circumstances, power fluctuations, machine failures, and so forth.

Additionally, learning how to address common cause variation is also vital. This sort of variation is just the normal fluctuation you’ll experience when measuring production output.

Conclusion

Improvements in meeting customer CTQs and specification limits are objective measures of quality that translate directly into quality gains, because transactional processing errors, late deliveries, and product defects are regarded as undesirable by all customers.