ENGR 1181

College of EngineeringEngineering Education Innovation Center

Collecting Measured Data

Pre-Class Reading

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Measurements

• Engineers collect and use measurement data to analyze, create or verify the design of products or processes.

• Correctly collecting and analyzing measured data are critical skills for engineers.

• High quality data is VERY important and there are many possible pitfalls in dealing with measured data that must be understood and avoided.

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Collecting Data

• It is important to determine what needs to be measured before taking measurements. Engineering problems may require careful thought to determine what is most important characteristic to measure.

• Typically in engineering, multiple measurements are collected because a single measurement rarely provides enough information

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Collecting Data Example

A coffee shop chain has received

complaints at a number of their

stores that their coffee has

inconsistent temperature. The

manager decides to hire an

engineering consultant to

determine what is causing this

temperature variation.

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Collecting Data Example

An engineer goes to several

stores to take measurements.

One temperature measurement

would not be sufficient to perform

a proper analysis, so in order to

fully understand the problem,

many cups of coffee throughout

the day have their temperatures

measured at the stores.

The sampling will provide the engineer with a large data sample that will help analyze the problem.

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Collecting Data Example

• After collecting the temperature data, it is seen that during peak selling times the measured temperature is much lower than other times during the day. (see graph)

• By collecting multiple measurements throughout the day, the engineer is able to focus attention on the real problem - why the coffee machines are not working properly during peak selling hours and solve the problem.

6 7 8 9 10 11 12 13 14 15100

150

200

Coffee Temp. Throughout the Day

Time of Day (24hr)

Te

mp

era

ture

(F

)

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Measurement System• Measured data is collected by people using some type of

equipment. (an engineer using a thermometer in the coffee example)

• This combination of human and instrumentation can be defined as a measurement system.

• In studying measurement data we need to understand each component of the measurement system and its effect on the quality of the data.

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Measured Data

• Two important aspects of measured data:– The “expected value” (the coffee machine’s desired

temperature)– The variation

• Even when the coffee machine was working correctly, the measured coffee temperature will vary slightly from the desired coffee temperature

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Variation• Variation in measured data is to be expected and is a

natural aspect of the “real world”

• When designing or evaluating a product, a range of acceptable variation needs to be established. It is the engineers job to establish this limit.

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What Creates Variation?

• To understand what creates variation we need to understand the following terms:– Accuracy– Repeatability (also known as Precision)– Resolution– Systematic Variation– Random Variation

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Accuracy vs. Repeatability

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Resolution

• The resolution of an instrument is the smallest increment the tool displays or is capable of measuring reliably

• Some electronic instruments will display values that are beyond their measurement resolution as show below:

Electronic Bathroom Scale Example• Typically displays a value to the nearest tenth of a pound

e.g. (170.6 lbs)• Inexpensive bathroom scales are not built well enough to measure to that

resolution

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Random vs. Systematic Variation

Random Systematic

(Unpredictable) (Predictable)

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Random Variation Example

• Mechanical and electrical instruments– Random variation can result from using instruments

near the limits of their resolution

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Random Variation Example

ParallaxYour eye needs to consistently be at position 2 (pictured) to get accurate readings off the ruler.

If your eye position varies randomly between positions 1,2 and 3 for each reading, then your measurements will vary randomly.

1

2

3

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Systematic Variation• Systematic Variation can be caused by human error and/or

instrumentation error

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Variation from Human Error

Dial indicators can also easily be misread.

Interchanging the large and small dial readings

is a common error.

Readings are composed of two parts:

• Small hand: Keeps track of each revolution

of the large hand, marks correspond to

0.100 inch

• Large hand: Divided by 100 equally spaced

marks that correspond to 0.001 inch

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Systematic Variation from Human Error

Example of not understanding how to correctly use measurement instrument• A new engineer is measuring the deflection of a beam

with a dial indicator. However, the engineer is not familiar with how to correctly read the dial, and reverses the readings of the small hand with the large hand. All of the measured deflections are off by a similar magnitude.

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Systematic Variation from Instrumentation Error

Example of not zeroing a scale• If there is nothing on the scale,

but it is not reading zero, this will create errors

• Every measurement will be off by 0.02 g