Exam 3: Statistical Process Control

Consider a service process such as a fast food drive through window. The target for a customer's waiting time is 3.0 minutes. A manager observes the process and randomly collects a sample of four waiting times each hour over a 12 hour period. The sum of the average waiting time for each of the 12 samples is 35.4. The sum of the range for each of the 12 samples is 18.0. The UCL for the process control chart reporting variability between the sample means is

Dumplings -To-Go (DTG) provides take-out dumplings and noodle dishes to customers at its chain of drive-through restaurants. The target for a customer's waiting time is 3.0 minutes +/- 1 minute. Each month, one of the managers observes the drive-through process and collects a sample of 4 waiting times a day over a 6 day period. The data from one restaurant appears below. If DTG were to construct an R-chart from this data, the centerline would be INSERT TABLE HERE

Pizazz manufactures a 5.0 oz. energy drink of the same name. Because the cans are so small, consumers are concerned that they are not receiving the full 5 ounces in each can. A quality engineer at the company is charged with analyzing the filling process and ensuring accurate readings. On 15 different occasions over the past month, she has taken a sample of 6 energy drinks off the production line and recorded their weight. If the sum of the sample means is 80.20 ounces and the sum of the sample ranges is 12.68 ounces, the centerline for an X-bar chart of this process would be

If the points plotted on a control chart display a pattern, it is called a run.

Control charts visually show when a process is not within statistical control limits.

When a control chart is first developed, if the process is found to be out of control,

The process capability index indicates how much a process mean differs from the target specification value.

Some companies that strive to provide extremely high quality use Z=6 (six sigma) vs. Z=3 (three sigma) when constructing control limits.

With a c-chart, the sample size is small and often may only contains only one item.

Common cause (random) variation provides evidence that the process is not in control.

The R-chart is used for monitoring and controlling variation within samples.

The process capability ratio measures the nonrandom variation (6 sigma) specification limits over the specification limitscontrol limits.

One goal of statistical process control is to prevent a process from producing items that have to be scrapped or reworked.

Dumplings -To-Go (DTG) provides take-out dumplings and noodle dishes to customers at its chain of drive-through restaurants. The target for a customer's waiting time is 3.0 minutes +/- 1 minute. Each month, one of the managers observes the drive-through process and collects a sample of 4 waiting times a day over a 6 day period. The data from one restaurant appears below. If DTG were to construct an X-bar chart from this data, the 3-sigma LCL would be Insert table here

102. A company produces a product which is designed to weigh 10 oz., with a tolerance of + 0.5 oz. The process produces products with an average weight of 9.95 oz. and a standard deviation of 0.10 oz. The process capability ratio for this process is with z = 3.

A sequence of sample points that display a pattern is known as a run.

The formula used to determine the upper and lower control limits are based on product specification limits.

A process that is determined to be in control contains no variation.

99. In general, a process is considered to be in control for all the following conditions except

Consider a production process that produces batteries. A quality engineer has taken 20 samples each containing 100 batterieslight bulbs. The total number of defective batteriesunits observed over the 20 samples is 1200. The UCL for the control chart constructed using two sigma is a. 0..088 b. 0.094 c. 0.104 d. 0.11660