Pouring over the latest control data, you take a look over the mean and control limits, verifying that the system is in control. The data shows where it went out of control, you made system changes, and now it appears to be back in control. Unfortunately, just because the system is in control does not mean it’s satisfying customer requirements.
How do you know when a value is good enough for the customer? Specification limits? What is the lower specification limit, anyway?
An overview: What is a lower specification limit?
The lower specification limit, or LSL, represents the lowest limit that a measurement or reading can reach and still be acceptable to the customer.
To understand why we need specification limits, it helps to understand control limits. A control limit represents the expectations of a process for a sample to be outside a given percentage range expectation. If we use a 95% range expectation, or +/- two standard deviations, it can help demonstrate the expectation of a reading being within a range with 95% certainty.
Specification limits are different from control limits, as they are not calculated using means and standard deviations, but are instead values determined by the designers via the customer to be within acceptable quality boundaries. They are what is acceptable to the customer. If the specifications, either upper or lower, are inside of the of the control limits boundaries, then the process is considered not capable, as the process could be operating within acceptable variation parameters and still deliver a product that is not within specification.
Let’s look at the example below. The X-bar R chart shows the data over a period of time, the mean, specification limits, and control limits (set at 95%, or +/- 2-sigma). It shows when the process went out of control (during readings 12-15). When the process was out of control, it ran the risk of being out of specification, though in this example, it did not pass the upper or lower specification limit ranges, meaning the process was in acceptable parameters for the customer.
3 benefits of attending to lower specification limits
Seeing where it compares with the lower control limit
If the lower control limit is higher than the lower specification limit, then the process can be considered capable, assuming that the inverse is said regarding the upper control and upper specification limits.
If not, the process is considered not capable of reliably providing a product that will meet customer requirements.
Easy spotlight for process improvement opportunities
Spotting readings that pass or come uncomfortably close to the lower specification limits is an easy to spot red flag for process concerns. Monitor the process and investigate whenever a reading is lower than the lower specification limit. There may be special circumstances that cause the lower specification limit to be breached, or there may be common causes in play with an out-of-control process.
Yield improvements through comparing LSL with the mean and USL
Take some time and compare where the upper and lower specification limits compare with the mean. If you see a shift, where one specification limit is much closer to the mean, and one is much farther away, you may have an opportunity to adjust the process that helps raise or drop the mean to a value that is closer to the halfway point between upper and lower specification limits.
3 lower specification limit best practices
- Verify with the customer that the correct specification level is set. Sometimes it can be expensive and time-consuming to meet the lower specification level, and you might find out that the level was set arbitrarily. You might find out that the customer does not mind having an even smaller LSL.
- Automate the data collection process as much as possible when collecting data to review. This type of data can be manpower intensive to collect, yet often there is a technological solution that collects the data for far less time and money.
- Be sure to not only regularly measure processes for specification limit data, but to review that data regularly. Many companies collect this type of information but wait too long between data reviews, resulting in time lost and money spent.
Frequently Asked Questions (FAQ) about lower specification limit
Can I have a lower specification limit that is higher than my lower control limit and still satisfy my customer?
It can be done, but not without an extremely high cost.
When a process is not capable, it does not mean that all products will fail, but it does show that there will be a large quantity of product that will not meet customer requirements. These products will require rework or scrap. No company would willingly wish to do business this way, which is the entire point of comparing control limits with specification limits.
The short answer is that you do not stay in business long if your lower specification limits are higher than your lower control limits.
All my values are within the lower specification limit, though many are close to the boundary. Is my system still capable?
Yes, it is still considered capable, though the system may not be in control. If you see a lot of values near the specification boundary, it is cause for concern. If you can make it so, you always want every value to be an optimal value, with as little variation as possible. Barely passing values today can become out-of-specification values tomorrow.
Can specification limits be used on other charts than the X-bar R chart shown earlier?
Any chart that can show an upper and lower control limit can also show specification limits. Here is another example, a histogram, with the limits demonstrated. In this example, since the LSL is higher than the LCL, this system is considered not capable.
Lower specification limits
Lower specification limit, or LSL, represents the lowest limit that a measurement or reading can reach and still be acceptable to the customer. It’s important to compare with the lower control limit to determine if the system is capable of meeting customer expectations over time. Reviewing regularly will help maintain quality levels, identify future process improvements, and confirm that customer requirements are met.