Motorola used the normal distribution to determine the probability of defects and the number of defects expected in a production process. Assume a production process produces items with a mean weight of 11 ounces. a. The process standard deviation is 0.10, and the process control is set at plus or minus 2 standard deviations. Units with weights less than 10.8 or greater than 11.2 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)? b. Through process design improvements, the process standard deviation can be reduced to 0.08. Assume the process control remains the samg, with weights less than 10.8 or greater than 11.2 ounces being classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)? c. What is the advantage of reducing process variation, thereby causing a problem limits to be at a greater number of standard deviations from the mean?
Motorola used the normal distribution to determine the probability of defects and the number of defects expected in a production process. Assume a production process produces items with a mean weight of 11 ounces. a. The process standard deviation is 0.10, and the process control is set at plus or minus 2 standard deviations. Units with weights less than 10.8 or greater than 11.2 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)? b. Through process design improvements, the process standard deviation can be reduced to 0.08. Assume the process control remains the samg, with weights less than 10.8 or greater than 11.2 ounces being classified as defects. What is the probability of a defect (to 4 decimals)? In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)? c. What is the advantage of reducing process variation, thereby causing a problem limits to be at a greater number of standard deviations from the mean?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Motorola used the normal distribution to determine the probability of defects and the number of defects expected in a production process. Assume a production process produces items with a mean weight of 11 ounces.
**a.** The process standard deviation is 0.10, and the process control is set at plus or minus 2 standard deviations. Units with weights less than 10.8 or greater than 11.2 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)?
**In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)?**
**b.** Through process design improvements, the process standard deviation can be reduced to 0.08. Assume the process control remains the same, with weights less than 10.8 or greater than 11.2 ounces being classified as defects. What is the probability of a defect (to 4 decimals)?
**In a production run of 1,000 parts, how many defects would be found (to the nearest whole number)?**
**c.** What is the advantage of reducing process variation, thereby causing a problem limit to be at a greater number of standard deviations from the mean?
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