Q&A Hero

Q: The upper and lower specifications for a service are 10 min. and 8 min., respectively. The process average is 9 min. and the process capability ratio is 1.33. What is the process standard deviation? A) 0.1 B) 0.15 C) 0.20 D) 0.25

Q: The upper and lower control limits for a component are 0.150 cm. and 0.120 cm., with a process target of .135 cm. The process standard deviation is 0.004 cm. and the process average is 0.138 cm. What is the process capability index? A) 1.00 B) 1.25 C) 1.50 D) 1.75

Q: A metal-cutting operation has a target value of 20 and consistently averages 19.8 with a standard deviation of 0.5. The design engineers have established an upper specification limit of 22 and a lower specification limit of 18. What is the process capability index? A) 1.20 B) 1.33 C) 1.46 D) 1.66

Q: A metal-cutting operation has a target value of 20 and consistently averages 19.8 with a standard deviation of 0.5. The design engineers have established an upper specification limit of 22 and a lower specification limit of 18. Which statement concerning this process is true? A) The process capability ratio is 1.46. B) The process capability index is 1.33. C) The process is in control. D) None of these is true.

Q: Process capability can be addressed when: A) assignable causes are present. B) a process is in statistical control. C) a process is in statistical control but assignable causes are present. D) the nominal value equals the tolerance regardless of assignable causes.

Q: Process capability determines whether a process is capable of producing the product or services that customers demand.

Q: The quality control technician grew weary of measuring pistons that came off the line, so he decided to make a fixture that would tell him whether the piston fell within product specifications. The fixture had two holes, one the exact width of the upper specification (24 cm) and one slightly smaller than the lower specification (21 cm). If the piston fit through the smaller hole, it would be too small and therefore rejected. If the piston didn't fit through the larger hole, it was too large and would be rejected. Just to test his idea, he used the traditional measurement system and his new system on the next eight samples. The data and the two charts he constructed are shown below. Why aren't the plotted points forming similar shapes between the two graphs? Evaluate the advantages and disadvantages of his proposed system. Sample 1 29.5 23 20.9 24.9 Sample 2 22.9 20.1 23.7 26.9 Sample 3 25.9 23.6 23 24.3 Sample 4 25.3 23.2 29.8 22.3 Sample 5 24.7 25.1 20.6 23 Sample 6 28.4 29.7 27.1 23.7 Sample 7 21.9 23.5 24.9 24.2 Sample 8 26.9 21.1 28.1 20.2 Sample 9 25.5 27.6 26.3 27.2 Sample 10 23.9 28.6 21.7 20.6

Q: How does SPC help companies implement continuous improvement programs?

Q: Hassan was the company plotter. Give him any data set and he could plot a graph that was not only accurate, but also aesthetically pleasing. One afternoon he took some attribute data and plotted it as a p-chart. When Saba, his supervisor, saw the plot he insisted it be discarded and in its place a c-chart should be constructed. Hassan made the c-chart and noticed that when he placed the two charts one on top of the other, the lines created by the data points were exactly the same shape. Has our plotting colleague made a mistake? If not, why should there be these two types of charts when the data generate identical lines?

Q: The UCL and LCL for an chart are 100 ounces and 95 ounces, respectively. The sample size is 5. The inspector looks at the very next unit and finds that it is 108 ounces. What can you conclude? Why?

Q: What is the relationship between type I and type II errors and the width of the upper and lower control limits on SPC charts? Propose a mechanism for determining SPC chart limit widths based upon the financial consequences of type I and type II errors.

Q: When is it advantageous to use sampling rather than complete inspection?

Q: The poultry farmer was aghast when the grocery store revealed their new weapon in the war on poor quality. They planned to use a(n) ________ to monitor the rotten eggs found in the cartons of farm fresh free range eggs that he supplied. The poultry farmer was well-versed in quality and knew their choice to be the right one; nevertheless he was upset about this level of scrutiny and what he perceived as a lack of trust.

Q: Jerry watched in awe as Warren went to 2 sigma limits from the company-mandated 3 sigma limits, thereby increasing the likelihood of a type ________ error.

Q: A(n) ________ specifies the sample size, the time between successive samples, and decision rules that determine when action should be taken.

Q: ________ of variation include any variation-causing factors that can be identified and eliminated.

Q: ________ of variation are the purely random, unidentifiable sources of variation that are unavoidable with the current process.

Q: A hotel tracks the number of complaints per month. When the process is in control, there is an average of 35 complaints per month. Assume that a 2-sigma control limit is used. The next four months have 33, 27, 29, and 43 complaints. What should management do? A) Look for assignable causes because the process is in control. B) Look for assignable causes because the process is out of control. C) Look for common causes because the process is out of control. D) Do nothing; the process is in control.

Q: A hotel tracks the number of complaints per month. When the process is in control, there is an average of 35 complaints per month. Assume that a 2-sigma control limit is used. What is the upper control limit? A) less than or equal to 35 B) more than 35 but less than or equal to 45 C) more than 45 but less than or equal to 55 D) more than 55

Q: A hotel tracks the number of complaints per month. When the process is in control, there is an average of 35 complaints per month. Assume that a 2-sigma control limit is used. What is the lower control limit? A) less than or equal to 15 B) more than 15 but less than or equal to 20 C) more than 20 but less than or equal to 25 D) more than 25

Q: Table 5.4 The manager of Champion Cooling Company has recently implemented a statistical process control method. The accompanying table shows the recorded temperatures of five different samples of walk-in coolers that were produced in the previous month. Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Unit 1 104.0 100.1 101.1 102.0 102.7 Unit 2 106.4 104.4 100.4 105.9 105.4 Unit 3 101.8 103.6 103.0 104.6 106.1 Unit 4 105.6 101.4 101.0 102.1 102.5 Unit 5 100.6 100.7 104.9 107.0 102.0 If an x-bar chart is constructed using the data in Table 5.4, what conclusion can be reached? A) The process is in control. B) The process is out of control. C) The process is capable. D) The process is both capable and in control.

Q: Four samples of 100 each were taken from an assembly line, with the following results: Sample Number Number Defective 1 6 2 12 3 2 4 8 Using the historical average as the central line of the chart, which one of the following is the limit for an attributes control chart with z = 2? A) UCL > 0.1 and LCL > 0.03 B) UCL > 0.1 and LCL < 0.03 C) UCL < 0.1 and LCL > 0.03 D) UCL < 0.1 and LCL < 0.03

Q: Table 5.3 Sample Number Number Defective 1 1 2 4 3 2 4 4 5 0 Use the information from Table 5.3. What is the upper control limit (UCL) if the bank were to use z = 2 and a sample size of 100? A) less than or equal to 0.02 B) greater than 0.02 but less than or equal to 0.04 C) greater than 0.04 but less than or equal to 0.06 D) greater than 0.06

Q: Table 5.3 Sample Number Number Defective 1 1 2 4 3 2 4 4 5 0 Samples of 100 checks each were taken at a bank from an encoding machine (which records the amount of a check) over a five-day period. Details are summarized in Table 5.3. If the bank were to use the average proportion defective from these five samples as the central line for a process control chart, what would be the central line? A) less than or equal to 0.01 B) greater than 0.01 but less than or equal to 0.02 C) greater than 0.02 but less than or equal to 0.03 D) greater than 0.03

Q: Historically, the average proportion of defective bars has been 0.015. Samples will be of 100 bars each. Construct a p-chart using z = 3. What is the value of LCL? A) less than or equal to 0.01 B) greater than 0.01 but less than or equal to 0.02 C) greater than 0.02 but less than or equal to 0.03 D) greater than 0.03

Q: Historically, the average proportion of defective bars has been 0.015. Samples will be of 100 bars each. Construct a p-chart using z = 3. What is the value of UCL? A) less than or equal to 0.050 B) greater than 0.050 but less than or equal to 0.060 C) greater than 0.060 but less than or equal to 0.070 D) greater than 0.070

Q: The consultant suspiciously eyed the c-chart that Chickenverks used to monitor the number of broken eggs in each 100 egg carton. "You know you really should be using a p-chart," the consultant commented with an air of superiority. "What's the difference between a p-chart and a c-chart in this application?" the long time Chickenverks employee asked with an obvious edge to his voice. "Well," the consultant replied, "the difference is: A) the width of the three sigma limits for the c-chart is 100 times greater than those of the p-chart." B) the three-sigma p-chart will catch problems earlier than the three sigma c-chart." C) the three-sigma c-chart will catch problems earlier than the three sigma p-chart." D) well, OK, you got me. The charts will look and behave the same for all practical purposes."

Q: The defect rate for a product has historically been about 7.0%. What is the upper control chart limit if you wish to use a sample size of 20 and 3-sigma limits? A) 0.186 B) 0.203 C) 0.222 D) 0.241

Q: The defect rate for a product has historically been about 5.0%. What is the upper control chart limit if you wish to use a sample size of 50 and 3-sigma limits? A) 0.082 B) 0.112 C) 0.142 D) 0.172

Q: The defect rate for a product has historically been about 2.0%. What are the upper and lower control chart limits if you wish to use a sample size of 100 and 3-sigma limits? All answers are in (LCL,UCL) format. A) (0.00, 0.048) B) (0.00, 0.062) C) (0.00, 0.059) D) (0.00, 0.067)

Q: Construct 3-sigma X-bar and R-charts using the data in the table. What conclusions can you draw about the state of control for this process? Sample # Observation 1 Observation 2 Observation 3 Observation 4 1 0.486 0.499 0.493 0.511 2 0.499 0.506 0.516 0.494 3 0.496 0.5 0.515 0.488 4 0.495 0.506 0.483 0.487 5 0.472 0.502 0.526 0.469 6 0.473 0.495 0.507 0.493 7 0.495 0.512 0.49 0.471 8 0.525 0.501 0.498 0.474 9 0.497 0.501 0.517 0.506 10 0.495 0.505 0.516 0.511 A) X-bar chart is out of control but the R-chart is in control B) the X-bar chart is out of control and the R-chart is also out of control C) the X-bar chart and the R-chart are both in control D) the X-bar chart is in control but the R-chart is out of control

Q: Construct a 3-sigma x-bar chart for the length in centimeters of a part from the following table. What is the upper control limit? Sample # Observation 1 Observation 2 Observation 3 Observation 4 1 0.486 0.499 0.493 0.511 2 0.499 0.506 0.516 0.494 3 0.496 0.5 0.515 0.488 4 0.495 0.506 0.483 0.487 5 0.472 0.502 0.526 0.469 6 0.473 0.495 0.507 0.493 7 0.495 0.512 0.49 0.471 8 0.525 0.501 0.498 0.474 9 0.497 0.501 0.517 0.506 10 0.495 0.505 0.516 0.511 A) 0.522 B) 0.509 C) 0.496 D) 0.475

Q: Construct a 3-sigma R-chart for the length in centimeters of a part from the following table. What is the upper control limit of your R-chart? Sample # Observation 1 Observation 2 Observation 3 Observation 4 1 0.486 0.499 0.493 0.511 2 0.499 0.506 0.516 0.494 3 0.496 0.5 0.515 0.488 4 0.495 0.506 0.483 0.487 5 0.472 0.502 0.526 0.469 6 0.473 0.495 0.507 0.493 7 0.495 0.512 0.49 0.471 8 0.525 0.501 0.498 0.474 9 0.497 0.501 0.517 0.506 10 0.495 0.505 0.516 0.511 A) .032 B) 0.51 C) 0.73 D) 2.28

Q: Thermostats are subjected to rigorous testing before they are shipped to air conditioning technicians around the world. Results from the last five samples are shown in the table. Create control charts that will fully monitor the process and indicate the result of X-bar and R-chart analysis. Unit # Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 1 73.5 70.8 72.2 73.6 71.0 2 71.3 71.0 73.1 72.7 72.2 3 70.0 72.6 71.9 72.4 73.3 4 71.1 70.6 70.3 74.2 73.6 5 70.8 70.7 70.7 73.5 71.1 A) x bar and r chart are both out of control B) x bar chart is in control but r chart is out of control C) x bar chart is out of control but r chart is in control D) x bar and r chart are both in control

Q: Thermostats are subjected to rigorous testing before they are shipped to air conditioning technicians around the world. Results from the last five samples are shown in the table. Calculate control limits for a chart that will monitor process consistency. The correct control limits as (LCL,UCL) are: Unit # Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 1 73.5 70.8 72.2 73.6 71.0 2 71.3 71.0 73.1 72.7 72.2 3 70.0 72.6 71.9 72.4 73.3 4 71.1 70.6 70.3 74.2 73.6 5 70.8 70.7 70.7 73.5 71.1 A) (-5.37,5.. B) (0.00,5.. C) (0.00,6.03). D) (0.00,6.12).

Q: Thermostats are subjected to rigorous testing before they are shipped to air conditioning technicians around the world. Results from the last five samples are shown in the table. Calculate control limits for a chart that will monitor performance to target. The correct control limits as (LCL,UCL) are: Unit # Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 1 73.5 70.8 72.2 73.6 71.0 2 71.3 71.0 73.1 72.7 72.2 3 70.0 72.6 71.9 72.4 73.3 4 71.1 70.6 70.3 74.2 73.6 5 70.8 70.7 70.7 73.5 71.1 A) (70.46, 73.39). B) (68.94,74.89). C) (69.71,74.14). D) (69.80,74.05).

Q: Historically, the average time to service a customer complaint has been 3 days and the standard deviation has been 0.50 day. Management would like to specify the control limits for an chart with a sample size of 10- and 3- sigma limits. Suppose the average service time from the next 10 samples yielded the following result: 3.2, 2.1, 3.6, 2.8, 3.9, 3.5, 2.7, 4.1, 2.6, and 3.3 days. What conclusion can be drawn? A) Assuming the process variability is in control, the process average is also in statistical control. B) Assuming the process average is in control, the process average is out of statistical control. C) The sample size should be increased. D) No conclusion can be drawn because there is insufficient data.

Q: Historically, the average time to service a customer complaint has been 3 days and the standard deviation has been 0.50 day. Management would like to specify the control limits for an chart with a sample size of 10- and 3- sigma limits. The LCL for the chart would be: A) less than 2.40. B) greater than 2.40 but less than or equal to 2.45. C) greater than 2.45 but less than or equal to 2.50. D) greater than 2.50.

Q: Five samples of size 4 were taken from a process. A range chart was developed that had LCLR = 0 and UCLR = 2.50. Similarly, an average chart was developed with the average range from the five samples, with LCL = 15.0 and LCL = 24.0. The ranges for each of the five samples were 1.75, 2.42, 2.75, 2.04, and 2.80, respectively. The values of the sample average for each sample were 19.5, 22.3, 17.4, 20.1, and 18.9, respectively. What can you tell management from this analysis? A) The process variability is out of control, and we cannot make a statement about the process average. B) The process variability is out of control, but the process average is in control. C) The process variability and the process average are out of control. D) We cannot tell if the process variability or the process average is out of control.

Q: Which alternative will increase the probability of detecting a shift in the process average? A) increasing the control limit spread B) taking smaller samples C) taking smaller samples more frequently D) taking larger samples more frequently

Q: A company is interested in monitoring the number of scratches on Plexiglass panels. The appropriate control chart to use would be: A) an chart. B) a p-chart. C) a c-chart. D) an R-chart.

Q: A company is interested in monitoring the average time it takes to serve its customers. An appropriate control chart would be: A) an chart. B) a p-chart. C) a c-chart. D) an R-chart.

Q: A company is interested in monitoring the variability in the weight of the fertilizer bags it produces. An appropriate control chart would be: A) an chart. B) a p-chart. C) a c-chart. D) an R-chart.

Q: The underlying statistical distribution for the p-chart is: A) Poisson. B) binomial C) percentage. D) normal.

Q: The UCL and LCL for an chart are 25 and 15 respectively. The central line is 20, and the process variability is considered to be in statistical control. The results of the next six sample means are 18, 23, 17, 21, 24, and 16. What should you do? A) Nothing; the process is in control. B) Explore the assignable causes because the second, fourth, and fifth samples are above the mean. C) Explore the assignable causes because there is a run. D) Explore the assignable causes because there is a trend.

Q: Regarding control charts, changing from two-sigma limits to three-sigma limits: A) increases the probability of concluding nothing has changed, when in fact it has. B) increases the probability of searching for a cause when none exists. C) decreases the probability that the process average will change. D) decreases the probability that defects will be generated by the process.

Q: Regarding control charts, changing from three-sigma limits to two-sigma limits: A) increases the probability of concluding nothing has changed, when in fact it has. B) increases the probability of searching for an assignable cause when none exists. C) decreases the probability that the process average will change. D) decreases the probability that defects will be generated by the process.

Q: An example of a type II error would be: A) counting a student's True/False response incorrect when it is actually correct. B) convicting an innocent defendant. C) eating food that you were unaware was spoiled. D) counting a student's True/False response incorrect when it is actually incorrect.

Q: An example of a type I error would be: A) throwing away a perfectly good banana. B) counting a student's multiple choice response correct when it is actually incorrect. C) releasing a guilty defendant. D) counting a student's multiple choice response correct when it is actually correct.

Q: Regarding control charts, a type I error refers to concluding that the process is: A) in control when it is not in control. B) incapable when it is capable. C) out of control when it is in control. D) capable when it is not capable.

Q: The three sigma limits for a process whose distribution conforms to the normal distribution include approximately: A) 50% of the observed values, in the long run. B) 68% of the observed values, in the long run. C) 95% of the observed values in the long run. D) 99% of the observed values in the long run.

Q: In SPC, the distribution of sample means: A) can be approximated by the normal distribution. B) will have greater variability than the process distribution. C) will always have a mean greater than the process distribution because of the sample size. D) cannot be used for control charts because the variability is understated.

Q: An operator of a filling machine plotted the weights of each bag she filled for three weeks. At the same time, a quality inspector randomly took groups of five bags of the same output and plotted the average weights of the samples. The inspector's sampling distribution will: A) have greater variability than the operator's distribution. B) have less variability than the operator's distribution. C) show if the output has been produced to the operator's specifications. D) have a mean five times greater than the operator's distribution.

Q: When should complete inspection be used? A) when inspection tests are destructive B) when inspection tasks are monotonous C) when the cost of product failure is high relative to the inspection costs D) when quality is a competitive priority

Q: Which one of the following statements relating to quality is true? A) Sampling procedures based on measurement by variables should be used when quality specifications are complex. B) A distribution of sample means has more variance than the process distribution itself. C) The distribution of sample means can be approximated by the normal distribution. D) Sampling is a better approach than 100 percent inspection when the cost of accepting a defective item is very high.

Q: Which one of the following statements about quality control is true? A) Measurement by attributes is a simple yes or no decision. B) Complete inspection is used when inspection cost is high. C) Sampling inspection is used when the cost of passing a defective unit is high relative to the cost of inspection. D) Measurement by variables is often used when the quality specifications are complex.

Q: A sampling plan is best for evaluating quality when: (1) Inspection costs are high (2) Inspection costs are low (3) Non-destructive testing is available (4) Destructive testing is required A) 1 and 3 B) 1 and 4 C) 2 and 3 D) 2 and 4

Q: In Statistical Process Control, ________ are used to detect defects and determine if the process has deviated from design specifications. A) flowcharts B) cause-and-effect diagrams C) process capability charts D) control charts

Q: Which of the following would be a "common" cause of variation? A) random sources B) a machine in need of repair C) an untrained worker D) a defective raw material

Q: The advantage of variable measurements is that they can be quickly counted compared to attribute measurements.

Q: The process and R-charts are developed using a sample size of 5, but the technician mistakenly looks up A2, D3, and D4 values for a sample size of 7. If these charts are put into daily use, the manufacturer will mistakenly ship more bad product than had the charts been constructed correctly.

Q: Process centering is shown by an chart.

Q: One chart commonly used for quality measures based on product or service attributes is the chart.

Q: A process is monitored with a control chart. The process is correctly judged to be in-control once the results from the most recent sample are plotted. Therefore, all of the output produced at that time is good.

Q: Wider limits on a control chart result in lower probability of a type I error.

Q: Convicting an innocent defendant is an example of a type II error.

Q: On a control chart, a type I error occurs when the employee concludes that the process is in control when it is actually out of statistical control.

Q: Assignable causes of variation include any variable-causing factors that can be identified and eliminated.

Q: Common causes of variation are the purely random, unidentifiable sources of variation that are unavoidable with the current process.

Q: Statistical process control (SPC) is the application of statistical techniques to determine whether a quantity of material should be accepted or rejected.

Q: In acceptance sampling, the ________ is the proportion defective that the buyer will allow in an incoming shipment.

Q: ________ is the application of statistical techniques to determine if the quality of incoming materials should be accepted or rejected, based on the testing of a sample of parts.

Q: In acceptance sampling, when the random sample passes the buyer's incoming test (low number of defects found), the next action taken is to: A) accept the entire lot of incoming materials. B) do additional testing to reduce the risk of accepting a bad-quality lot. C) place the lot on hold and wait for additional lots from this seller to be tested to assure consistent good quality. D) 100% inspect the lot because some defects were found.

Q: In acceptance sampling, the proportion defective that the buyer will allow in an incoming shipment is: A) the acceptable random sample (ARS). B) the upper control limit (UCL). C) the lower control limit (LCL). D) the acceptable quality level (AQL).

Q: While acceptance sampling does determine if incoming materials should be accepted or rejected, it does not limit the buyer's risk of accepting bad-quality parts or rejecting good-quality parts.

Q: An acceptable quality level is measured as the proportion of defective items a buyer is willing to tolerate.

Q: Acceptance sampling is the application of statistics to determine if the quality of incoming materials should be accepted or rejected.

Q: What are the steps in the Six Sigma improvement model and how do they relate to the PDSA cycle?

Q: Why is employee empowerment important in a total quality management program?

Q: Provide examples of the three main tenets of total quality management as applied to this operations management course.