Concept explainers
a
Interpretation:
Hourly cost of operating the system is to be determined.
Concept Introduction:
Probability Distribution Function is a likelihood of an event to occur for discrete random variables. Graphically, it shows how likely variables will fall under the probability area.
b
Interpretation:
The optimal value of k for n = 6 is to be determined.
Concept Introduction:
Probability Distribution Function is a likelihood of an event to occur for discrete random variables. Graphically, it shows how likely variables will fall under the probability area.
c
The optimal values by using the spreadsheet program and the approximations suggested in the chapter are to be determined.
Concept Introduction:
Probability Distribution Function is a likelihood of an event to occur for discrete random variables. Graphically, it shows how likely variables will fall under the probability area.
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EBK PRODUCTION AND OPERATIONS ANALYSIS
- A machine is used to fill cans of motor oil additive. A single sample can is selected every hour and the net weight of the can is obtained. Since the filling process is automated, it has very stable variability, and long experience indicates that s = 0.02 oz. The process target (process mean when in control) is 8.02 oz. A tabular cusum is being used for this process with standardized values h=4.5 and k=0.5. If the values of Cumulative sums at the end of measurement 7 were C," + = 0.030 and C,¯ = 0.0 , and measurement 8 is equal to Xg = 8.071, what will be the Cumulative sum at the end of measurement 8, that is C3 + = ? 0.041 0.071 0.051 0.046 0.061arrow_forwardA manufacturer is selling pharmaceuticals that have a weight specification 199.8 to 200.2 mg, with a target value of 200 mg. Before sending its next shipment, the company collects a large sample of product and determines the mean weight of the sample is 199.89 mg, with a standard deviation of 0.035 mg. The process capability index for the current process is ____. Round to three decimal places.arrow_forwardLinda Boardman, Inc., an equipment manufacturer in Boston, has submitted a sample cutoff valve to improve your manufacturing process. Your process engineering department has conducted experiments and found that the valve has a mean (u) of 12.00 and a standard deviation (a) of 0.04. Your desired performance is μ = 12.00 +3 standard deviations, where a = 0.045. For the given information, the process capability index (Cpk) - (round your response to three decimal places).arrow_forward
- When using a control chart (say X-bar and S) to monitor a process, if the process goes out of control, we can continue to operate the process for a short time if we apply a well designed acceptance sampling plan until we find what caused the process to go out of control. True Falsearrow_forwardC-Spec, Inc., is attempting to determine whether an existing machine is capable of milling an engine part that has a key specification of 5 ± 0.006 inches. After a trial run on this machine, C-Spec has determined that the machine has a sample mean of 5.001 inches with a standard deviation of 0.005 inch. Calculate the Cpk for this machine. (Round your answer to 3 decimal places.)arrow_forwardLinda Boardman, Inc., an equipment manufacturer in Boston, has submitted a sample cutoff valve to improve your manufacturing process. Your process engineering department has conducted experiments and found that the valve has a mean (u) of 12.00 and a standard deviation (o) of 0.06. Your desired performance is u = 12.00 ±3 standard deviations, where o = 0.070. For the given information, the process capability index (Cpk) = (round your response to three decimal places)arrow_forward
- The specifications for a gasket that installs between two engine parts calls for a thickness of 6.0 mm ± .2 mm. The standard deviation of the process is estimated to be 0.05 mm. The process is known to operate at a mean thickness of 6.1 mm What are the upper and lower specification limits for the gasket? What are the Cp and Cpk values for this process? Is this process capable of producing the desired part?arrow_forwardLinda Boardman, Inc., an equipment manufacturer in Boston, has submitted a sample cutoff valve to improve your manufacturing process. Your process engineering department has conducted experiments and found that the valve has a mean of 8.00 and a standard deviation of .04. Your desired performance is = 8.0 ± 30, where o = 0.047. Is the following statement true or false? Can Boardman produce the valve within the specified tolerance? (TRUE=yes, it can; FALSE=no, it cannot) O True O Falsearrow_forwardAn airline operates a call center to handle customer questions and complaints. The airline monitors a sample of calls to help ensure that the service being provided is of high quality. Ten random samples of 100 calls each were monitored under normal conditions. The center can be thought of as being in control when these 10 samples were taken. The number of calls in each sample not resulting in a satisfactory resolution for the customer is as follows. (a) What is an estimate of the proportion of calls not resulting in a satisfactory outcome for the customer when the center is in control? 0.04 (b) Construct the upper and lower limits for a p chart for the manufacturing process, assuming each sample has 100 calls. (Round your answers to four decimal places.) UCL = 0.0988 ✓ X LCL = 0.0188 (c) With the results of part (b), what conclusion should be made if a sample of 100 has 13 calls not resulting in a satisfactory resolution for the customer? Since p = is outside of ✔✔✔ the control…arrow_forward
- Refer to Table S6.1 - Factors for Computing Control Chart Limits (3 sigma) for this problem. Twelve samples, each containing five parts, were taken from a process that produces steel rods at Emmanual Kodzi's factory. The length of each rod in the samples was determined. The results were tabulated and sample means and ranges were computed. The results were: Sample Mean (in.) Range (in.) Sample Sample Sample Mean (in.) Range (in.) 1 9.404 0.044 7 9.403 0.021 2 9.402 0.051 8 9.405 0.058 3 9.393 0.042 9.395 0.039 4 9.404 0.037 10 9.401 0.038 9.399 0.048 11 9.401 0.054 9.397 0.053 12 9.404 0.061 For the given data, the x = inches (round your response to four decimal places). Based on the sampling done, the control limits for 3-sigma x chart are: Upper Control Limit (UCL;) = inches (round your response to four decimal places). Lower Control Limit (LCL;) = inches (round your response to four decimal places).arrow_forwardDesigning an x -Chart Using the Process Standard DeviationThe Sunny Dale Bank monitors the time required to serve customers at the drive-through window because it is an important quality factor in competing with other banks in the city. After analyzing the data gathered in an extensive study of the window operation, bank management determined that the mean time to process a customer at the peak demand period is 5 minutes, with a standard deviation of 1.5 minutes. Management wants to monitor the mean time to process a customer by periodically using a sample size of six customers. Assume that the process variability is in statistical control. Design an x-chart that has a type I error of 5 percent. That is, set the control limits so that there is a 2.5 percent chance a sample result will fall below the LCL and a 2.5 percent chance that a sample result will fall above the UCL. After several weeks of sampling, two successive samples came in at 3.70 and 3.68 minutes, respectively. Is the…arrow_forwardQuality control programs often establish control limits that are three standard deviationsfrom the target mean of a process. If the mean of a sample taken from the process iswithin the control limits, the process is deemed satisfactory.A process is designed to fill bottles with 16 ounces of soda with a standard deviationof 0.5 ounces. Determine the control limits above and below the mean for this processusing a sample size of n = 30.arrow_forward
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