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1 Quality Test 2: SPC NAME:_________________________ Show all work, be neat, explain anything you feel needs explaining. 1. The following data (20 samples) was collected on a production line to determine whether or not the process was in a state of statistical control and to hopefully use SPC to monitor the process in the future. Sample 1 2 … 19 20 X1 135.83 126.56 … 121.24 140.04 X2 134.22 126.74 … 134.49 137.39 X3 121.07 128.10 … 131.86 123.55 X4 125.70 127.97 … 125.29 130.72 X5 X-Bar R 137.62 130.89 16.55 126.56 127.19 1.54 … … … 121.06 126.79 13.44 113.45 129.03 26.59 X-Bar-Bar = 130.30 R-Bar = 12.53 X-Bar X-Bar Chart 138 134 130 126 122 1 3 5 7 9 11 13 15 17 19 Sample R R Chart 30 25 20 15 10 5 0 1 3 5 7 9 11 13 15 17 19 Sample a. Calculate control limits for X-Bar and R chart. b. Show the control chart limits on control charts and determine if process appears to be in a state of statistical control. 2 2. When setting up a control chart to determine if a process was stable, 20 samples of size 5 were collected with X-Bar-Bar = 130.3 and R-Bar = 12.53. After the process was determined to be stable, you are asked the following questions. a. What is the standard deviation of the process? b. What is the capability index Cp assuming the spec is 130 + 20? c. What is the capability index Cpk assuming the spec is 130 + 20? d. Explain why you would consider this process either capable or not capable. e. Draw a picture of the process and show spec limits as well as the edges of the process. 3 3. You are currently using X-Bar and R charts to monitor a process that has been very stable for some time. During today’s production run, the first 9 values for X-Bar and R are shown below reflecting a process that is still in control. Show what you would expect the charts to look like for the next 11 observations if the mean were to dramatically decrease and the standard deviation were to stay the same after the 9th observation (that means obs. 10 -20). MAKE IT OBVIOUS. X-bar Chart for X Bar X-bar 123 UCL = 122.47 122 CTR = 119.79 121 LCL = 117.10 120 119 118 117 0 2 4 6 8 10 12 14 16 18 20 Subgroup Range Chart for R 10 UCL = 9.84 Range 8 CTR = 4.66 LCL = 0.00 6 4 2 0 0 2 4 6 8 10 12 Subgroup 14 16 18 20 4 4. You are currently using X-Bar and R charts to monitor a process that has been very stable for some time. During today’s production run, the first 9 values for X-Bar and R are shown below reflecting a process that is still in control. Show what you would expect the charts to look like for the next 11 observations if the mean were to dramatically increase and the standard deviation were to dramatically increase after the 9th observation (that means obs. 10-20). MAKE IT OBVIOUS. X-bar Chart for X Bar X-bar 123 UCL = 122.47 122 CTR = 119.79 121 LCL = 117.10 120 119 118 117 0 2 4 6 8 10 12 14 16 18 20 Subgroup Range Chart for R 10 UCL = 9.84 Range 8 CTR = 4.66 LCL = 0.00 6 4 2 0 0 2 4 6 8 10 12 Subgroup 14 16 18 20 5 5. The government is concerned about the population of golden eagles in the national forests because they are considered an endangered species. They do not want the number of eagles to get too large since there is a limited supply of food and too many eagles would result in starvation. Also, they do not want the number of eagles to decline because they are considered a national treasure. Your boss has suggested that you fly over a randomly selected number of acres each spring and count the number of eagles seen. A young intern who just completed a course in quality control suggest that your boss use SPC to monitor the eagle population. Everyone agrees that an acceptable state for the eagle population is 16 eagles/100 acres. The intern suggests that they randomly select 100 acres each spring and count the number of eagles spotted. If the count exceeds the upper control limit, they could capture some eagles in the park and transport them elsewhere. If the count was below the lower control limit, they could put out eagle food and bring in eagle doctors to cure any diseases that the population of eagles may have until the population increases back to the desired level. a. Suggest what control chart would be appropriate for this application. b. Calculate the control chart limits for the one you selected. 6 6. When setting up X-Bar and R charts, discuss the following issues a. How large should your sample size be at each point in time? Use power curves to help explain the impact sample size has on the effectiveness of the control charts. b. How frequent should you take your samples? What are the issues that would influence the frequency of your samples [every 5 minutes, every 15 minutes, etc.] 7. Briefly explain Type I and Type II errors as they pertain to control charts. 7 8. Your boss has ask you to set up X-Bar and R control charts to monitor the fill volume of 12 oz. cans of Koke. The spec for Koke is 12 + 0.6 oz. [Target mean is 12 and maximum allowable standard deviation is 0.2]. After collecting data [25 samples of size 4 during an eight hour production run] your X-Bar-Bar was 11.8 oz. resulting in your X-Bar control chart being centered at 11.8 oz. rather than the target value of 12.0 oz. When you boss saw this, she became very upset because “the mean fill is suppose to be 12.0, not 11.8”. She told you to go get X-Bar and R control charts that would force the process to meet spec [Mean = 12.0 and standard deviation equal to 0.2]. In other words, assume the mean and standard deviation of the process was 12.0 and 0.2 respectively. Use these values to determine the upper and lower limits for your X-Bar and R control charts. a. X-Bar Chart: UCL = Center line = LCL = b. R-Chart: UCL = Center line = LCL =