Consistency as a Measure of Wiper Quality
Quality is commonly defined as meeting or exceeding stated performance targets while consistency is, “the agreement or harmony of parts or features to one another or a whole.”1 Therefore, consistency is an integral parameter that allows the expected quality to be achieved. Here you will be able to read and see all the documents completed.
Determining Cleanroom Wiper Consistency
Wipers are used to control contamination in cleanroom environments in a variety of industries, from building the next-generation microchip to manufacturing the newest vaccine. Each of these settings may have different applications for a cleanroom wiper, but measuring the wiper quality should always be the same, i.e. consistent.
We demonstrate here three methods of evaluating wiper consistency using a common sample data set.
Statistical Process Control (SPC)
Statistical process control (SPC) is the application of statistical methods to the monitoring and control of a manufacturing process to ensure that it operates at its full potential to produce a conforming product. Wiper manufacturers should employ SPC programs to control the physical, chemical, and contamination characteristics for each wiper lot that is manufactured.
Typically SPC data are plotted by sample number (as shown in Figure1). However, if multiple lot or wipers are to be compared, determining the best quality wiper can quickly become confusing and uninformative (as shown in Figure 2).
The downside: With all these data points, it is often difficult to determine which wiper has the highest quality.
Data Averages and Standard Deviations
A commonly used method to compare cleanroom wiper quality is through data averages and standard deviations which assume a normal distribution. (Note: The same data set as represented in Figure 2 is compiled in Table 1.) Such a method reduces a very large set of available data that has been produced over time to two numbers that inadequately represent the data set.
The downside: Each data set is summarized by just two data points, and, as a result, much information is lost
Consistency Charts
Incomplete data summaries as represented by typical or average values misrepresent the true quality of a cleanroom wiper. A quicker, easier, and more statistically unbiased method to evaluate many large sets of data is a Consistency Chart. These may also be referred to as "Box and Whisker Charts."
The components of a Consistency Chart are:
- Line – represents the median or middle value of a ranked data set. (Extreme values do not affect the median value as much as an average could be affected.)
- Box – represents the range of values in which fifty percent of the data lie. If the median line is nearer to one end of the box, the data are skewed toward that end. A smaller box indicates that the values are more similar.
- Whisker – the line at each end of the box, expresses a range of values in which twenty-five percent of the data set lie. A short whisker indicates that values within the whisker range are similar to each other.
- Outlier – indicates points that are significantly different than the rest of the dataset
Conclusions
Selecting the best cleanroom wiper for a particular application requires the most unbiased scientific assessment of the available data for any given wiper. Texwipe specializes in developing best practices within our manufacturing operation to minimize variability in our processes. This translates into reduced variability in our wiper products.
The Consistency Chart comparison of the four wipers shown here allows for a quick determination that Wiper 1 is a better performing cleanroom wiper because it is more consistent in its quality measures. A user has greater assurance that Wiper 1 will perform as expected with a higher degree of confidence when compared to the other wipers shown in the data set, due to its greater consistency.
The quality of a cleanroom wiper should therefore be evaluated not merely through a typical or average value, but more importantly through a statistically valid assessment of how consistently that typical value is attained in practice over some time.
Click here to read the full document, see the example and charts explained.