Many business owners are assessing the current quality and efficiency of their product development processes. Process capability analysis is a tool these businesses can use to determine the current condition of their product development processes—to help assess how well their product development process meets a set of predetermined specifications. This analysis can also help business stakeholders develop quality improvement initiatives.
To use an example for the remainder of this guide, let’s say Bobby is the owner of Bobby’s Bats. He wants to assess how well his bats meet the length standards for Major League Baseball (MLB). He’ll use process capability analysis to determine if his process can meet the standards and the extent to which his production is centered between the specification limits. Bobby can then use the results of this analysis to measure and control the variation of his process to stay ahead of the competition.
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What is Process Capability?
Before we discuss the importance of process capability, let’s first define what a process means.
A process can be any combination of tools, resources, or personnel working in tandem to produce a specific product or output. At Bobby’s Bats, these include the staff, the saws and sanders, the wood and stain used to make the bats—and computer software.
Ideally, this process would run each time consistently, producing a bat cut to the exact MLB specifications. However, we know that it’s more likely there will be some variation in the output of the process. This is where a process capability analysis becomes useful.
Process capability provides two critical pieces of information. First, it provides a measure of the variability in the output of a given process. Second, it compares the capability of a proposed specification and provides critical data that enables production efficiency—while also identifying potential problem areas.
Process capability requires a data set from an in-control process, which means that the output measures of the process in question and then creates a normal bell-curve distribution over time. Using standard, in-control data sets is key to the success of process capability analysis.
Difference Between Cp, Cpk, and Pp, PPk
It is essential to understand the differences between the various calculations. The potential capability (Cp) is used to measure how capable a process is of making parts within predetermined limits or specification limits. These limits are defined by a lower specification limit (LSL) and an upper specification limit (USL). The spread between the current process and the process capability is measured using six process standard deviation units.
In Bobby’s case, the LSL and USL would specify how short or long the bats should meet MLB specifications, respectively.
The actual capability during production (Cpk) measures whether the process is centered between the previously determined specification limits. The k is the factor that centralizes the data. If you picture a bell curve, the Cpk measures how centered the curve is between the LSL and USL limits of the curve.
Both the Cp and Cpk measurements assume that the sampling comes from a normal distribution of a large (more than 50 measurements), randomly selected sample.
The preliminary process capability (Pp) and its respective preliminary process capability index (Ppk) are used more commonly to evaluate new processes that haven’t been established yet or processes that don’t come from a normal distribution of data.
In Bobby’s case, he may want to calculate a Pp and Ppk if he decides to change his process to accommodate a higher production volume.
How to Measure and Calculate Process Capability
There are several steps one should follow when performing a capability analysis. The first step is to determine the upper and lower specification limits for the process. The customer, client, or personnel involved in the production of the product can define these limits.
The second step is to collect a sampling of the current production process to determine the mean and standard deviation of the existing product output. In this step, obtaining a large sample size (typically 50 or more measurements) and collecting samples over a long period in one production run is vital to ensure robust and accurate sampling.
Potential capability is calculated by dividing the specification width by the process.
Because potential capability is calculated using six standard deviations, Bobby will multiply six times the standard deviation he calculated from his sample to get the process width. He’ll also subtract the LSL from the USL to get the specification width, which looks like this:
Bobby is looking for a process capability that is greater than one (1). If this is the case, it means that his process has the potential to be capable of producing the specifications required, depending on the way the process centers. To determine process centering, we need to calculate the actual capability during production (Cpk).
The Cpk is a measurement of how centered the process is between the specifications. This is determined by calculating the process capability of both the lower specification (Cpl) and the upper specification (Cpu):
Once those are calculated, we take the smallest value of the Cpl or Cpu, which can be calculated as follows:
If the minimum value is lower than one (1), the process can’t be accepted and won’t meet the required specifications. While a minimum of one (1) could be considered acceptable, numbers closer to two (2) and three (3) are more desirable. Note that a Cpk higher than 1.33 is the standard most companies require as a satisfactory process capability.
If Bobby’s actual capability during production is just below this capability, he’ll need to make some changes if he wants to produce more volume going into the summer. To accomplish this, he could work toward a more robust reduction in the process’s variability or towards centering the midpoint of the process output.
Process Capability for Non-Normal Data
Calculating a preliminary process capability should only be used when a new process is being established and has not yet reached statistical control. The critical difference between a preliminary process capability index (Ppk) and the actual process capability index (Cpk) is that Ppk can only assess information from the past due to the lack of current data on the process. Unfortunately, this calculation can’t be used to predict future process outcomes reliably.
It’s also important to note that Cpk and Ppk values will vary greatly when the process is not under statistical control. Understanding these differences will ensure that you’ll choose the capability analysis most appropriate for your data set.
The importance of process capability lies in its ability to inform businesses both what they’re doing well and where they can afford to improve.
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