Production and Operations Analysis, Seventh Edition
7th Edition
ISBN: 9781478623069
Author: Steven Nahmias, Tava Lennon Olsen
Publisher: Waveland Press, Inc.
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Chapter 12.2, Problem 9P
Summary Introduction
Interpretation: Control Limits needs to be determined with the help of given data.
Concept Introduction: X bar chart monitors the change in mean over time helps organizations makes better improvement decisions.
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Using the proper control chart, determine two-sigma control limits for the situation below.
a. An examiner found an average of 4.9 scratches in the outer paint of each of the vehicles being made for delivery to dealers.
b. Before delivery of lawn mowers to dealers, an examiner tries to start each mower and notes any that do not start on the first try. The lot size is 200 mowers, and an average of 5 did not start (2.5 percent)
At Quick Car Wash, the wash process is advertised to take less than 7 minutes. Consequently, management has set a target average of 390 seconds for the wash process. Suppose the average range for a sample of 10 cars is 11 seconds. Use the accompanying table to establish control limits for sample means and ranges for the car wash process.
The
UCL Subscript x overbar equals seconds and the LCL Subscript x overbar equals seconds. (Enter your responses rounded to two decimal places.)
The following data represents the number of weld defects observed in 24 samples of five printed circuit boards: 7 6 8 10 24 6 5 4 8 11 15 8 4 16 11 12 8 6 5 9 7 14 8 21.
a) Using all the data, calculate the control limits.
b) Can it be concluded that the process is in control? If not, suppose they can find the assignable causes, and recalculates the control limits once out of control points eliminated.
Chapter 12 Solutions
Production and Operations Analysis, Seventh Edition
Ch. 12.1 - Prob. 2PCh. 12.1 - Prob. 3PCh. 12.1 - Prob. 4PCh. 12.1 - Prob. 5PCh. 12.1 - Prob. 6PCh. 12.2 - Prob. 7PCh. 12.2 - Prob. 8PCh. 12.2 - Prob. 9PCh. 12.2 - Prob. 10PCh. 12.2 - Prob. 11P
Ch. 12.2 - Prob. 12PCh. 12.2 - Prob. 13PCh. 12.3 - Prob. 14PCh. 12.3 - Prob. 15PCh. 12.3 - Prob. 16PCh. 12.3 - Prob. 17PCh. 12.4 - Prob. 18PCh. 12.4 - Prob. 19PCh. 12.4 - Prob. 20PCh. 12.4 - Prob. 21PCh. 12.5 - Prob. 22PCh. 12.6 - Prob. 23PCh. 12.6 - Prob. 24PCh. 12.6 - Prob. 25PCh. 12.6 - Prob. 26PCh. 12.6 - Prob. 27PCh. 12.6 - Prob. 28PCh. 12.9 - Prob. 29PCh. 12.9 - Prob. 30PCh. 12.9 - Prob. 31PCh. 12.9 - Prob. 32PCh. 12.9 - Prob. 33PCh. 12.10 - Prob. 34PCh. 12.10 - Prob. 35PCh. 12.10 - Prob. 37PCh. 12.10 - Prob. 38PCh. 12.10 - Prob. 39PCh. 12.10 - Prob. 40PCh. 12.11 - Prob. 41PCh. 12.11 - Prob. 42PCh. 12.11 - Prob. 43PCh. 12.11 - Prob. 44PCh. 12.12 - Prob. 46PCh. 12.12 - Prob. 47PCh. 12.12 - Prob. 48PCh. 12 - Prob. 49APCh. 12 - Prob. 50APCh. 12 - Prob. 51APCh. 12 - Prob. 52APCh. 12 - Prob. 53APCh. 12 - Prob. 54APCh. 12 - Prob. 55APCh. 12 - Prob. 57APCh. 12 - Prob. 58APCh. 12 - Prob. 59APCh. 12 - Prob. 60APCh. 12 - Prob. 61APCh. 12 - Prob. 62APCh. 12 - Prob. 63APCh. 12 - Prob. 64APCh. 12 - Prob. 65APCh. 12 - Prob. 66APCh. 12 - Prob. 67APCh. 12 - Prob. 68APCh. 12 - Prob. 69APCh. 12 - Prob. 70AP
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- Which of the following is NOT true when a process is in-control select one: a. the process includes a high precentage of satisfactory results b. the process includes random variation c. All points lie within the control limits d. the process includes variation due to special or assignable causesarrow_forwardA Quality Analyst wants to construct a control chart for determining whether three machines, all producing the same product, are under control with regard to a particular quality variable. Accordingly, he sampled four units of output from each machine, with the following results: For upper and lower control limits of 23.29 and 16.71, which machine(s), if any, appear(s) to have an out-of-control process mean?arrow_forwardThe chair of the operations management department at Quality University wants to construct a p-chart for determining whether the four faculty teaching the basic P/OM course are in control with regard to the number of students who fail the course. Accordingly, he sampled 100 final grades from last year for each instructor, with the following results Instructor Number of Failures Prof. A 13 Prof. B 0 Prof. C 11 Prof. D 16 What is the estimate of the mean proportion of failures for these instructors?arrow_forward
- At Webster Chemical Company, lumps in the caulking compound could cause difficulties in dispensing a smooth bead from the tube. Even when the process is in control, an average of four lumps per tube of caulk will remain. Testing for the presence of lumps destroys the product, so an analyst takes random samples. The following results are obtained: Tube No. Lumps Tube No. Lumps Tube No. Lumps 1 6 5 6 9 5 2 5 6 4 10 0 3 0 7 1 11 9 4 4 8 6 12 2 Determine the c-chart two-sigma upper and lower control limits for this process. Is the process in statistical control?arrow_forwardCan we say the process is under control by observing one subgroup out of control limit?arrow_forwardEach day 500 inventory control records are cycle-counted for errors. These counts have been made over a period of 20 days and have resulted in the following proportion of records found in erroreach day: .0025 .0075 .0050 .0150 .0125 .0100 .0050 .0025 .0175 .0200 .0150 .0050 .0150 .0125 .0075 .0150 .0250 .0125 .0075 .0100a. Calculate the center line, upper control limit, andlower control limit for a p control chart.b. Plot the 20 points on the chart and determine which ones are in control.c. Is the process stable enough to begin using these data for quality control purposes?arrow_forward
- Please do not give solution in image format thanku A restaurant wants to make sure that they are serving customers quickly enough. Every day for 10 days, they sample 16 random customers, and measure how long it is until the waiter shows up. Uisng this sample data, the company calculates the 3-sigma control limits as LCL = 3.5 minutes and UCL = 6.5 minutes. What would be the LCL and UCL if the company uses 2-sigma control limits instead? 1. LCL = 4.5 minutes and UCL = 7.5 minutes 2. LCL = 3 minutes and UCL = 7 minutes 3. LCL = 4 minutes and UCL = 6 minutes 4. LCL = 4.5 minutes and UCL = 5.5 minutesarrow_forwardA woodworker is concerned about the quality of the finished appearance of her work. She has finished a total of 50 unit split-willow hand-woven baskets. However, she has found the following number of finish defects in ten units sampled: 4,0,3,1,2,0,1,2,0,2. Calculate the average number of defects per basket. If 3-sigma control limits are used, calculate the lower control limit and upper control limit.arrow_forwardThe mean processing time (x¯) of a job on a machine is 11 minutes with a standard deviation (σ)of 0.23 minutes. Upper specification limit (USL) is 11.5 minutes, whereas lower specification limit (LSL) is 10.5 minutes. What is the process capability ratio (cp) for this process? Is the process capable? Cp=1, not capable Cp=1.5, capable Cp=0.72, capable Cp=1, capable Cp=0.72, not capablearrow_forward
- At Quick Car Wash, the wash process is advertised to take less than 7 minutes. Consequently, management has set a target average of 390 seconds for the wash process. Suppose the average range for a sample of 9 cars is 8 seconds. Use the accompanying table to establish control limits for sample means and ranges for the car wash process. LOADING... Click the icon to view the table of factors for calculating three-sigma limits for the x overbarx-chart and R-chart. Factors for calculating three-sigma limits for the x overbarx-chart and R-chart Size of Sample (n) Factor for UCL and LCL for x overbarx-chart (Upper A 2A2) Factor for LCL for R-Chart (Upper D 3D3) Factor for UCL for R-Chart (Upper D 4D4) 2 1.8801.880 00 3.2673.267 3 1.0231.023 00 2.5752.575 4 0.7290.729 00 2.2822.282 5 0.5770.577 00 2.1152.115 6 0.4830.483 00 2.0042.004 7 0.4190.419 0.0760.076 1.9241.924 8 0.3730.373…arrow_forwardAt Quick Car Wash, the wash process is advertised to take less than 7 minutes. Consequently, management has set a target average of 390 seconds for the wash process. Suppose the average range for a sample of 9 cars is 8 seconds. Use the accompanying table to establish control limits for sample means and ranges for the car wash process. LOADING... Click the icon to view the table of factors for calculating three-sigma limits for the x overbarx-chart and R-chart. Factors for calculating three-sigma limits for the x overbarx-chart and R-chart Size of Sample (n) Factor for UCL and LCL for x overbarx-chart (Upper A 2A2) Factor for LCL for R-Chart (Upper D 3D3) Factor for UCL for R-Chart (Upper D 4D4) 2 1.8801.880 00 3.2673.267 3 1.0231.023 00 2.5752.575 4 0.7290.729 00 2.2822.282 5 0.5770.577 00 2.1152.115 6 0.4830.483 00 2.0042.004 7 0.4190.419 0.0760.076 1.9241.924 8 0.3730.373…arrow_forwardType I error (alpha risk). After several investigations of points outside control limits revealed nothing, a manager began to wonder about the probability of a Type I error for the control limits used(z = 1.90).a. Determine the alpha risk (i.e., P [Type I error]) for this value of z.b. What z would provide an alpha risk of about 2 percent?arrow_forward
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