Five batteries were taken in each sample to measure how long (in hours) every battery will last. The inspection team randomly picked samples every two hours during the day. The data for four samples is shown in the following table.     Please help the inspection team construct appropriate control limits using 3-sigma to monitor the quality of battery life (keep two decimal places if necessary). Which of the following statements is FALSE based on the control limits?   Select one: a. More than one control charts can be used. b. The process is in control. c. The sample size is 5. d. One of the control limits is 40.71. e. If every battery is designed to have an average life of 60 hours, the process is still in control.

Twenty samples of 100 items each were inspected when a process was considered to be operating satisfactorily. In the 20 samples, a total of 140 items were found to be defective. (a) What is an estimate of the proportion defective when the process is in control? (b) What is the standard error of the proportion if samples of size 100 will be used for statistical process control? (Round your answer to four decimal places.) (c) Compute the upper and lower control limits for the control chart. (Round your answers to four decimal places.) UCL = LCL =

Consider a process with lower process control limit as 1.338  and upper process control limit as 1.342 . The lower specification limit is 1.335 and the upper specification limit is 1.345. Utilizing the information provided, is the process is capable of meeting design specifications?

Refer to Table 56.1-Factors for Computing Control Chart Limits.(3.sigma) for this problem. Auto pistons at Wemming Chung's plant in Shanghai are produced in a forging process, and the diameter is a critical factor that must be controlled. From sample sizes of 10 pistons produced each day, the mean and the range of this diameter have been as follows: a) What is the value of x? mm (round your response to two decimal places). b) What is the value of R? R=mm (round your response to two decimal places). c) What are the UCL, and LCL; using 3-sigma? Day 1 2 3 4 5 Upper Control Limit (UCL;)mm (round your response to two decimal places) Lower Control Limit (LCL;)mm (round your response to two decimal places). d) What are the UCL and LCL using 3-sigma? Upper Control Limit (UCLR)-mm (round your response to two decimal places). Lower Control Limit (LCL)-mm (round your response to two decimal places) Mean x (mm) 154.9 151.2 155.6 155.5 154.6 Range R (mm) 4.4 4.8 4.3 5.0 4.7 Next

The smallest defect in a computer chip will render the entire chip worthless. Therefore, tight quality control measures must be established to monitor these chips. In the past, the percent defective at Chieh Lee's Computer Chips has been 1.5%. The sample size is 1,000. Determine upper and lower control chart limits for these computer chips. Use z = 3. Upper Control Limit (UCL) = (round your response to four decimal places). Lower Control Limit (LCLp) = (round your response to four decimal places).

Suppose that a quality characteristic is normally distributed with specifications at 100 ± 20. The process standard deviation is 6.(a) Suppose that the process mean is 100. What are the natural tolerance limits? Calculate Cp and Cpk and interpret these ratios. What fraction of parts do you expect to be defective?(b) Suppose that the process mean is 106. What are the natural tolerance limits? What is thefraction defective? Calculate Cp and Cpk and interpret these ratios.

The weights of boxes of Oat Flakes within a large production lot are sampled each hour.  Managers want to set control limits that include 99.73% of the sample means, and given is the population (process) standard deviation, which is 1.13. You are in charge of randomly selecting four boxes each hour, for three hours. The data you collected is located in the table below:Using an Xbar Chart, what are the upper and lower control limits?   Sample Avg. of 4 boxes 1 16.8 2 17.1 3 17.2

A company producing printed circuit boards is using a c-chart with an L = 2.75 to monitor the lamination process. The process is in-control and the data show that average number of defects per inspection unit of 100 boards is 2.5.   Unknowingly the process mean shifts to 4.5. What is the probability the shift will be caught on the next process sample?

In quality assurance, reduction of variations allows us to increase the control limits and have a safety buffer.  True or False.  Why?

Suppose a form has 10 fields of information. If 15 forms are sampled and 21 defects are found in the sample. What is the DPMO?