Anyone
who has faced a production problem with a need to solve it by using production
data can relate to the notion of a brain teaser. The brain teasers presented
here are based on real-world situations encountered by workers in manufacturing
environments. The brain teasers have three parts: (1) the situation, (2)
available data or other supporting information and (3) questions that various
workers need answered for continual improvement. Recommended solutions follow
in the next issue and on the Web at Quality Online (www.qualitymag.com).
Situation
Wesley
is a product engineer for a company that makes housings for a variety of
printer manufacturers. Customers submit specifications for each critical
characteristic and Wesley’s company automatically cuts the specifications to
about 60% of what the customer sets. Production is then required to meet these
tightened “internal” specifications for the housings. Difficulties occur when
production cannot meet the internal specifications and Wesley tries to work out
a solution. Until the conflict is resolved, all products that do not meet the
internal specification must be reworked or sometimes scrapped even if the
product meets the customer’s specification. The additional labor and material
usage add cost to the product that production considers unnecessary. The most
recent dispute involves a clearance between two parts of the housing and Wesley
has not yet reached a resolution with production.
Available data
The
clearance specification involved in the dispute was set by the customer as 1
millimeter ±0.2 millimeter. The internal specification was set as 1 millimeter
±0.12 millimeter. Current clearance data for the past two weeks of production
for this printer housing are summarized in the table, “Clearance Data for
Printer Housing.”
Questions
- What do the data provided reveal about
process behavior for clearance?
- What is the capability of clearance based on the specifications given
to production?
- Based on the customer’s requirements, what is the capability of
clearance?
- In what way is the company penalizing itself by working to the
internal specifications? How can they evaluate the cost of this practice?
Answers to May Brain Teaser
Fiona
is a production manager for a company that makes equipment that sorts product
by weight. One customer says that the equipment does not always sort the
product correctly and some product goes in the wrong bin. Fiona assigned a
quality technician, Fred, to the customer to determine what is occurring and
how to fix the machine.
Q:
What can be learned from an analysis of the 50 days of calibration data on the
sizing scale?
A: A process behavior chart shows the impact of adjusting the scale in the
sizing machine without an understanding of the standard deviation of repeated
measurements of the same unit (repeatability) for the scale. These daily values
show a predominately zigzag pattern and the moving ranges show a cyclic
pattern. Clearly, these patterns must be connected to specific causes. The
standard deviation calculated from the average moving range is 1.864 which is
inflated from the zigzag pattern, while the calculation = 1.261. The
measurement study will reveal just how much this latter value might be
inflated.
Q: What do the data from the measurement study reveal about the scale and the
operators?
A: The range chart of repeated measurements by each operator for the different
weight standards shows a predictable amount of measurement process variation.
The standard deviation of repeated measurements is 0.55, which is much lower
than either standard deviation from the calibration data. Also, when the value
of the different standard weights is subtracted from the data, a process
behavior chart shows no difference in the operators or the standards. From 100
to 180, the scale is consistent.
Q: How do the results from the calibration data and the measurement study
compare?
A: The measurement study shows a much lower standard deviation for the
repeatability of the scale. The standard deviation from the calibration data is
inflated by unnecessary adjustments to the scale.
Q:
How can Fred explain the results from these two sets of data to Fiona and the
customer?
A: Fred can start the explanation by showing the process behavior chart from
the measurement study that illustrates how well the scale works across the full
range of weights. See the chart, “Measurement Study at Different Weights.” Fred
also can show the histogram for the calibration data as well as the histograms
for the measurement study where the values are represented as deviations from
the standard value. See the two histograms, “Calibration Data Histogram” and
“Measurement Study Histogram.” The data values on the histogram for the calibration
data have more than twice the variation as do the values from the measurement
study. This indicates that there is more than routine variation in the
calibration data.