By the end of this task, you will be able to analyze spot weld shear strength
data using MS Excel’s DataAnalysisToolPak to create
histograms, accurately determine the minimum required shear strength, and
provide evidence-based recommendations on whether the spot welding robot meets
the manufacturing company’s strength requirements. This task will enhance your
ability to interpret and present technical data, facilitating informed
decision-making in engineering contexts.
A manufacturing company is testing a spot-welding robot to see if it can
provide spot welds that are strong enough for their needs, see
Fig. 3.10 that shows a FANUC R-2000iD/210FH
spot welding robot with hollow arm and internal cable dressing. An engineer has
data on \(100\) spot weld shear strength tests in Mega Pascals
(\(\mega\pascal\)) and wants to analyze the data to make an evidence-based
decision about whether to purchase the robot.
Note
Click on this link to know more about spot-welding robot.
In the Calculation Section, use built-in MS Excel functions to
calculate the descriptive statistics for the data; including minimum,
maximum, range, mean, median, mode, variance, and standard deviation.
If the required minimum shear strength is \(780 \ksi\) (kilo pound per
square inch), should the company buy the welding robot? Justify your
answer using the data.
Save the ex3_ind_1_username.xlsx file as
ex3_ind_1_values_username.pdf
displaying the values and
ex3_ind_1_formulas_username.pdf
displaying the formula.
Submit both files to Gradescope.
Note
Given are \(100\) measurements of strength tests. It is not of interest to compute statistics for just these \(100\) tests. \(100\) tests were done to get a good grasp of how the true underlying distribution looks like. Given more time and resources, one would probably conduct another \(100\) tests to improve the accuracy of the tests conclusions, correct? Thus, the test results are a sample from a much larger (in this case infinite) population. Imagine only \(2\) tests were done. It would not make sense to call this the entire population, correct? If one can without problem increase or decrease the number of given data points, it is most likely a sample, like in this case.