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15:40:34 Page 14
Repeated measurements made during any single test run or on a single batch are called repetitions.
Repetition helps to quantify the variation in a measured variable as it occurs during any one test or
batch while the operating conditions are held under nominal control. However, repetition will not
permit an assessment of how precisely the operating conditions can be set.
If the bearing manufacturer was interested in how closely bearing mean diameter was
controlled in day-in and day-out operations with a particular machine or test operator, duplicate
tests run on different days would be needed. An independent duplication of a set of measurements
using similar operating conditions is referred to as a replication. Replication allows for quantifying
the variation in a measured variable as it occurs between different tests, each having the same
nominal values of operating conditions.
Finally, if the bearing manufacturer were interested in how closely bearing mean diameter was
controlled when using different machines or different machine operators, duplicate tests using these
different configurations holds the answer. Here, replication provides a means to randomize the
interference effects of the different bearing machines or operators.
Replication allows us to assess the control of setting the operating conditions, that is, the ability
to reset the conditions to some desired value. Ultimately, replication provides the means to estimate
control over the procedure used.
Example 1.5
Consider a room furnace thermostat. Set to some temperature, we can make repeated measurements
(repetition) of room temperature and come to a conclusion about the average value and the variation
in room temperature at that particular thermostat setting. Repetition allows us to estimate the
variation in this measured variable. This repetition permits an assessment of how well we can
maintain (control) the operating condition.
Now suppose we change the set temperature to some arbitrary value but sometime later
return it to the original setting and duplicate the measurements. The two sets of test data are
replications of each other. We might find that the average temperature in the second test differs
from the first. The different averages suggest something about our ability to set and control the
temperature in the room. Replication permits the assessment of how well we can duplicate a set
of conditions.
Concomitant Methods
Is my test working? What value of result should I expect? To help answer these, a good strategy is to
incorporate concomitant methods in a measurement plan. The goal is to obtain two or more
estimates for the result, each based on a different method, which can be compared as a check for
agreement. This may affect the experimental design in that additional variables may need to be
measured. Or the different method could be an analysis that estimates an expected value of the
measurement. For example, suppose we want to establish the volume of a cylindrical rod of known
material. We could simply measure the diameter and length of the rod to compute this. Alternatively,
we could measure the weight of the rod and compute volume based on the specific weight of the
material. The second method complements the first and provides an important check on the
adequacy of the first estimate.
14 Chapter 1 Basic Concepts of Measurement Methods
15:40:34 Page 14
Repeated measurements made during any single test run or on a single batch are called repetitions.
Repetition helps to quantify the variation in a measured variable as it occurs during any one test or
batch while the operating conditions are held under nominal control. However, repetition will not
permit an assessment of how precisely the operating conditions can be set.
If the bearing manufacturer was interested in how closely bearing mean diameter was
controlled in day-in and day-out operations with a particular machine or test operator, duplicate
tests run on different days would be needed. An independent duplication of a set of measurements
using similar operating conditions is referred to as a replication. Replication allows for quantifying
the variation in a measured variable as it occurs between different tests, each having the same
nominal values of operating conditions.
Finally, if the bearing manufacturer were interested in how closely bearing mean diameter was
controlled when using different machines or different machine operators, duplicate tests using these
different configurations holds the answer. Here, replication provides a means to randomize the
interference effects of the different bearing machines or operators.
Replication allows us to assess the control of setting the operating conditions, that is, the ability
to reset the conditions to some desired value. Ultimately, replication provides the means to estimate
control over the procedure used.
Example 1.5
Consider a room furnace thermostat. Set to some temperature, we can make repeated measurements
(repetition) of room temperature and come to a conclusion about the average value and the variation
in room temperature at that particular thermostat setting. Repetition allows us to estimate the
variation in this measured variable. This repetition permits an assessment of how well we can
maintain (control) the operating condition.
Now suppose we change the set temperature to some arbitrary value but sometime later
return it to the original setting and duplicate the measurements. The two sets of test data are
replications of each other. We might find that the average temperature in the second test differs
from the first. The different averages suggest something about our ability to set and control the
temperature in the room. Replication permits the assessment of how well we can duplicate a set
of conditions.
Concomitant Methods
Is my test working? What value of result should I expect? To help answer these, a good strategy is to
incorporate concomitant methods in a measurement plan. The goal is to obtain two or more
estimates for the result, each based on a different method, which can be compared as a check for
agreement. This may affect the experimental design in that additional variables may need to be
measured. Or the different method could be an analysis that estimates an expected value of the
measurement. For example, suppose we want to establish the volume of a cylindrical rod of known
material. We could simply measure the diameter and length of the rod to compute this. Alternatively,
we could measure the weight of the rod and compute volume based on the specific weight of the
material. The second method complements the first and provides an important check on the
adequacy of the first estimate.
14 Chapter 1 Basic Concepts of Measurement Methods