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 10 ounces. a. The process standard deviation is 0.10 , and the process control is set at plus or minus 1 standard deviation. Units with weights less than 9.9 or greater than 10.1 ounces will be classified as defects. What is the probability of a defect (to 4 decimals)?
Motorola used the
a. The process standard deviation is 0.10 , and the process control is set at plus or minus 1 standard deviation. Units with weights less than 9.9 or greater than 10.1 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 0.05. Assume the process control remains the same, with weights less than 9.9 or greater than 10.1 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? (It can substantially reduce the number of defects/It has no effects on the number of defects)
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