At the beginning of this chapter, we discussed rubber-edge manufacturing for speaker woofer drivers and a criterion for classifying process capability.
Recall that each process for manufacturing rubber edges requires a production weight specification that consists of a lower specification limit (LSL), a target weight (T ), and an upper specification limit (USL). The actual mean and standard deviation of the weights of the rubber edges being produced are called the process mean (μ) and process standard deviation (σ). A process that is on target (μ = T) is called super if σ < (USL − LSL)/12.
The table on page 514 provides data on rubber-edge weight for a sample of 60 observations. Use those data and the procedures discussed in this chapter to solve the following problems:
a. Find a99%confidence interval for the process standard deviation.
b. The process under consideration is known to be on target, and its production weight specification is LSL = 16.72, T = 17.60, and USL = 18.48. Do the data provide sufficient evidence to conclude that the process is super? Perform the required hypothesis test at the 1% significance level.
c. Obtain a normal probability plot of the data.
d. Based on your plot in part (c), was conducting the inferences that you did in parts (a) and (b) reasonable? Explain your answer.