All Matches

Solution Library

Expert Answer

Textbooks

Search Textbook questions, tutors and Books

Oops, something went wrong!

Change your search query and then try again

Result Not Found

Books FREE
Tutors
Study Help
Hire a Tutor
AI Tutor New

Search
Sign In
Register

study help
business
introduction to statistical investigations

Questions and Answers of Introduction To Statistical Investigations

. Compare the plans developed in Exercise 15-16 in terms of average frac-tion inspected and their operating-char-acteristic curves. Which plan would you prefer if p = 0.0375?
. Suppose that CSP-1 is used for a manu-facturing process where it is desired to maintain an ADQL of 1.90%. Specify.two CSP-1 plans that would meet this AOQL target.
. For the sampling plans developed in Exercise 15-14, compare the plans' per-formance in terms of average fraction inspected, given that the process is in control at an average fallout level of
. An electronics manufacturer buys mern-ory devices in lots of 30,000 from a sup-plier. The supplier has a long record of good quality performance, with an aver-age fraction defective of
. Consider a single-sampling plan with it =25, c = 0. Draw the OC curve for this plan. Now consider chainsampling plans with n = 25, c = 0, and i = 1, 2, 5, 7.Sketch the OC curves for these
.A standard of 0.3 ppm has been estab-lished for formaldehyde emission levels in wood products. Suppose that the stan-dard deviation of emissions in an indi-vidual board is o = 0.10 ppm. Any lot that
.A chemical ingredient is packed in metal containers. A large shipment of these containers has been delivered to a manufacturing facility. The mean bulk density of this ingredient should not be less
.A soft-drink bottler purchases nonreturn-able glass bottles from a supplier. The lower specification on bursting strength in the bottles is 225 psi. The bottler wishes to use variables sampling to
.A lot of 500 items is submitted for inspection. Suppose that we wish to find a plan from MIL STD 414, using inspection level Il. If the AQL is 4%, find the Procedure 1 sampling plan from the
.How does the sample size found in Exercise 15-4 compare with what would have been used under MIL STD 105E?
. A belt that is used in a drive mechanism in a copier machine is required to have a minimum tensile strength of LSL =150 lb. It is known from long experience that o = 5 1b for this particular
. The density of a plastic part used in a cellular telephone is required to be at least 0.70 g/cm. The parts are supplied in large lots, and a variables sampling plan is to be used to sentence the
. A product is supplied in lots of size N =10,000. The AQL has been specified at 0.10%. Find the normal, tightened, and reduced single-sampling plans from MIL STD 105E, assuming general inspection
. Repeat Exercise 14-16, using general inspection level I. Discuss the differ-ences in the various sampling plans.
. Consider rectifying inspection for single sampling. Develop an AOQ equation assuming that all defective items are removed but not replaced with good oncs.
. (a) Derive an item-by-item sequential-sampling plan for which p1 = 0.01,(x=0.05, p =0.10, and B=0.10.(b) Draw the OC curve for this plan.
. (a) Derive an item-by-item sequential-sampling plan for which p1 = 0.01.a=0.05, p2 = 0.10, and 0=0.10.(b) Draw the OC curve for this plan.
. Draw the primary and supplementary OC curves for a double-sampling plan with my = 50, c; = 2, n = 100, c2 = 6. If the incoming lots have fraction noncon-forming p = 0.05, what is the probability of
.Consider the single-sampling plan found in Exercise 14-4. Suppose that lots of N = 2000 are submitted. Draw the ATI curve for this plan. Draw the AOQ curve and find the AOQL.
. A company uses the following accep-tance-sampling procedure. A sample equal to 10% of the lot is taken. If 2% or less of the items in the sample are defec-tive, the lot is accepted; otherwise, It
. Find a single-sampling plan for which p1=0,02, cx= 0.01, p2 = 0.06, and @=0.10.
.Find a single-sampling plan for which P1=0.05, a=0.05. p2= 0.15, and B=0.10.
. Find a single-sampling plan for which p1=0.01, a=0.05, p2 =0.10, and ₿=0.10.
. Consider the response model in equa-tion 13-5. Suppose that in the response model we allow for a complete second-order model in the noise factors so that h(x,2) = {YR + EE 8UHR;i=1+ 22,22+20,27
. Consider the response model in equa-tion 13-5 and the transmission of error approach to finding the variance model(equation 13-7). Suppose that in the response model we use h(x,z) = EYR; + [ 2
. Reconsider the crystal growth experi-ment from Exercise 13-10. Suppose that x] = z is now a noise variable, and that the modified experimental design shown here has been conducted. The
. The following data were collected by a chemical engineer. The response y is fil- tration time, x, is temperature, and x is pressure. Fit a second-order model.(a) What operating conditions would you
. The data shown in the following table were collected in an experiment to opti-mize crystal growth as a function of three variables .x1, x2, and x5. Large val-ues of y (yield in grams) are
.Consider the leaf spring experiment in Exercise 13-7. Rework this problem, assuming that factors A, B, and C are easy to control but factors D and E are hard to control.
.Consider the leaf spring experiment in Exercise 13-7. Suppose that factor E(quench oil temperature) is very difficult to control during manufacturing. We want to have the mean spring height as close
. An article by J. J. Pignatiello, Jr. and J.S. Ramberg in the Journal of Quality Technology (Vol. 17, 1985, pp. 198-206)"describes the use of a replicated frac-tional factorial to investigate the
. In their book Empirical Model Building and Response Surfaces (John Wiley, 1987), G. E. P. Box and N. R. Draper describe an experiment with three fre-tors. The data shown in the following table are
. An article in Rubber Chemistry and Technology (Vol. 47. 1974, pp.825-836) describes an experiment that studies the relationship of the Mooney viscosity of rubber to several variables, including
. A second-order response surface model in two variables is y= 69.0+1.6x| +1.1x2 -1x]-1.2.x +0.3x *2(a) Generate a two-dimensional contour plot for this model over the region 4-25x) ≤+2, 1=1,2, and
. An experiment was run to study the effect of two factors, time and tempera-ture, on the inorganic impurity levels in paper pulp. The results of this experi-ment are shown here:(a) What type of
. Consider the first-order model 9 = 50+2x1 - 15x2 + 3x3 where -1 ≤ x/ S + 1, 1 = 1, 2, 3. Find the direction of steepest ascent.
. Consider the first-order model§ =75+10×1 +6.17(a) Sketch the contours of constant pre-dicted response over the range-1 ≤x|≤+1,{=1,2.(b) Find the direction of steepest ascent.
. A 24℃) design has been used to investi-gate the effect of four factors on the(a) Estimate the factor effects. Plot the effect estimates on a normal proba-bility scale.(b) Identify a tentative
. Set up a 2 -4 fractional factorial design.Verify that this is a resolution IV design.Discuss the advantage of a resolution IV design relative to one of lower resolu-tion.
. Reconsider the data in Exercise 12-12.Suppose that four center points were added to this experiment. The molecular weights at the center point are 90, 87, 86, and 93.(a) Analyze the data as you did
. A 2ª factorial design has been run in a pilot plant to investigate the effect of four factors on the molecular weight of a polymer. The data from this experi-ment are as follows (values are coded
. An article in Industrial and Engineering Chemistry ("More on Planning Experi-ments to Increase Research Efficiency."1970, pp. 60-65) uses a 25-2 design to investigate the effect of A =
. R. D. Snee ("Experimenting with a Large Number of Variables," i Experiments in Industry: Design, Analysis and Interpretation of Results, by R. D. Snee, L. B. Hare, and J. B.Trout, Editors, ASQC,
.Show how a 25 experiment could be set up in two blocks of 16 runs each.Specifically, which runs would be made in cach block?
. Suppose that only one replicate of the 24 design in Exercise 12-4 could be run, and we could only conduct eight tests each day. Set up a design that would block out the day effect. Show
.Suppose that only the data from repli-cate I in Exercise 12-4 were available.Analyze the data and draw appropriate conclusions.
.Find the standard error of the effects for the experiment in Exercise 12-4. Using the standard errors as a guide, what fac-tors appear significant?
. Consider the experiment in Exercise 12-4. Plot the residuals against the levels of factors A, B, C, and D. Also construct a normal probability plot of the residu-als. Comment on these plots.
. Four factors are thought to possibly influence the taste of a soft drink bever-age: type of sweetener (A), ratio of syrup to water (B), carbonation level(C), and temperature (D). Each factor can be
. Find the residuals from the tool life experiment in Exercise 12-2. Construct a normal probability plot of the residu-als. Plot the residuals versus the pre-dicted values, Comment on the plots.
. A process engineer is trying to improve the life of a cutting tool. He has run a 23 experiment using cutting speed (A), metal hardness (B), and cutting angle (C) as the factors. The data from two
. An article in Industrial Quality Control (1956, pp. 5-8) describes an experiment to investigate the effect of glass type and phosphor type on the brightness of a television tube. The response mea-
. Use the data in Exercise 11-9 to con- struct a bounded adjustment chart. Use =0.2 and set L = 4. How does the bounded adjustment chart perform rela- tive to the integral control adjustment
. Consider the observations in the follow-ing table. The target value for this process is 50.(a) Set up an integral controller for this process. Assume that the gain for the adjustment variable is g
.Rework Exercise 11-7 using A = 0.4 and L = 15. What differences in the results are obtained?
. Use the data in Exercise 11-6 to con-struct a bounded adjustment chart. Use A= 0.2 and set L = 12. How does the bounded adjustment chart perform rela-tive to the integral control adjustment
.Consider the observanons shown in the following table. The target value for this process is 200.(a) Set up an integral controller for this process. Assume that the gain for the adjustment variable
. The Variogram. Consider the variance of observations that are an periods apart;that is, Vm = VON" - y)). A graph of V./V1 versus m is called a variogram. It is a nice way to check a data series for
. Consider the data in Table 11-1. Suppose that an adjustment is made to the output variable after every observation.Compare the performance of this chart'to the one in Table 11-1 and Fig. 11-12.
.Consider, the data in Table 11-1.Construct a bounded adjustment chant using 2 = 0.4 and Z = 10. Compare the performance of this chart to the one in Table 11-1 and Fig. 11-12.
.Consider the data in Table 11-1.Construct a bounded adjustment chart using A = 0.3 and L = 10. Compare the performance of this chart to the one in Table 11-1 and Fig. 11-12.
. If y, are the observations and z, is the EWMA, show that the following rela-dionships are true,(a) 4 -4-1 = 20. - 2-1)(b) 4, - (1 - M)em-1=)-Yı-
. Consider the p = 9 process variables in Table 10-5.(a) Perform a PCA on the first 30 obser-vations. Be sure to work with the standardized variables.(b) How much variability is explained if only the
. Consider the p = 4 process variables in Table 10-6. After applying the PCA pro-cedure to the first 20 observations data(see Table 10-7), suppose that the first three principal components are
. Continuation of Exercise 10-19. Using the residuals from the regression models in Exercise 10-19, set up EWMA con-trol charts. Compare these EWMA con-trol charts to the Shewhart charts for
. Consider the cascade process data in Table 10-5. In fitting regression models to both y, and y2 you will find that not all of the process variables are required"to obtain a satisfactory regression
. Consider the cascade process data in Table 10-5.(a) Set up an individuals control chart on y2-(b) Fit a regression model to y2, and set up an individuals control chart on the residuals. Comment on
. Suppose that there are p = 2 quallty characteristics, and in correlation form both variables have variance unity and the correlation coefficient is 0.8. The In-control value of the process mean
. Suppose that there are p = 4 quality characteristics, and in correlation form all four variables have variance unity and that all pairwise correlation coeffi-cients are 0.9. The in-control value
. Suppose that there are p = 4 quality characteristics, and in correlation form all four variables have variance unity and all pairwise correlation coefficients are 0.75. The in-control value of the
. Consider all 30 observations on the first two process variables in Table 10-6.Calculate an estimate of the sample.covariance matrix using both estimators S1 and S2 discussed in Section 10-3.2.Are
. Consider the first three process variables in Table 10-5. Calculate an estimate of the sample covariance matrix using both estimators S, and S2 discussed in Section 10-3.2.
. Consider the first two process variables in Table 10-5. Calculate an estimate of the sample covariance matrix using both estimators S, and S2 discussed in Section 10-3.2.
. Suppose that we have p3 quality char- acteristics, and in correlation form all three variables have variance unity and all pairwise correlation coefficients are 0.8. The in-control value of the
. Suppose that we have p = 4 quality char-acteristics, and in correlation form all four variables have variance unity and all pairwise correlation coefficients are 0.7. The in-control value of the
.Consider a 7" control chart for monitor-ing p= 10 quality characteristics.Suppose that the subgroup size is n = 3 and there are 25 preliminary samples available to estimate the sample covari-ance
.Rework Exercise 10-7, assuming that the subgroup size is n = 5.
. Consider a 7ª control chart for monitor-ing p=10 quality characteristics.Suppose that the subgroup size is n = 3 and there are 25 preliminary samples available to estimate the sample covari-ance
. Rework Exercise 10-5, assuming that the subgroup size is rt == 5.
.Consider a Tª control chart for moni-toring p=6 quality characteristics.Suppose that the subgroup size is n = 3 and there are 30 preliminary samples available to estimate the sample covari-ance
.Reconsider the situation in Exercise 10-2. Suppose that the sample mean vector and sample covariance matrix provided were the actual population parameters.What control limit would be appropriate for
. Reconsider the situation in Exercise 10-1. Suppose that the sample mean vector and sample covariance matrix provided were the actual population .parameters. What control limit would be appropriate
. A product has three quality characteris-tics. The nominal values of these quality characteristics and their sample covari-ance matrix have been determined from the analysis of 30 preliminary
. The data shown here come from a pro-duction process with two observable quality characteristics, x1 and X2. The data are sample means of each quality characteristic, based on samples of size n =
. A control chart for tool wear. A sam-ple of five units of product is taken from a production process every hour. The following results are obtained.Assume that the specifications on this quality
. An X chart is used to maintain current control of a process. The cost parame-ters are 21 = $2, Q2 = $0.50,a) = $50, aj = $75, and a= = $200. A single assignable cause occurs, with magni-tude 5 = 1,
.Consider the cost information given in Exercise 9-30. Suppose that the process model represented by equation 9-31 is appropriate. It requires 2 h to investigate a false alarm, the profit per hour of
. An X chart is used to maintain current control of a process. The cost parame-ters are d = $0.50, a2 = $0.10, ag = $25, a3 = $50, and a; = $100. A single assignable cause of magnitude 6 = 2 occurs,
. An # chart is used to maintain current control of a process. A single assignable cause of magnitude 20 occurs, and the time that the process remains in control is an exponential randoma variable
. The viscosity of a chemical product is read every 2 minutes. Some data from this process are shown in the table on the next page (read down, then across from left to right).(a) Is there a serious
. (a) Discuss the use of the moving range method to estimate the process stan-dard deviation when the data are positively autocorrelated,(b) Discuss the use of the sample vari-ance s' with positively
.Set up a moving center-line EWMA con-trol chart for the temperature data in Exercise 9-24. Compare it to the residuals control chart in Exercise 9-24, part (c).
.Consider the temperature data in Exercise 9-24. Set up an EWMA control chart on the residuals from the model you fit to the data in part (c) of that exer-cise. Compare it to the individuals chart
.Consider the temperature data in Exercise 9-24. Set up a cusum control chart on the residuals from the model you fit to the data in part (c) of that exer-cisc. Compare it to the individuals chart
. The data shown here are temperature measurements made every 2 minutes on an intermediate chemical product (read down, then across from left to right).(a) Calculate the sample autocorrela-tion
.Set up a moving center-line EWMA control chart for the concentration data in Exercise 9-20. Compare it to the residuals control chart in Exercise 9-20, part (c).
.Consider the concentration data in Exercise 9-20. Construct an EWMA control chart in the residuals from the model you fit in part (e) of that exercise.
. Consider the concentration data in Exercise 9-20. Construct a cusum chart in the residuals from the model you fit in part (e) of that exercise.
.The data shown here are concentration.readings from a chemical process, made every 30 minutes (read down, then across from left to right).(a) Calculate the sample aurocorrela-tion function and
. Set up a moving center-line EWMA control chart for the molecular weight data in Exercise 9-16. Compare it to the residual control chart in Exercise 9-16, part (c).

Showing 1 - 100 of 2939

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Last

Services

Sitemap
Fun
Definitions
Become Tutor
Study Help Categories
Recent Questions
Expert Questions

Company Info

Security
Copyrights
Privacy Policy
Terms & Conditions
SolutionInn Fee
Scholarship

Get In Touch

About Us
Contact Us
Career
Jobs
FAQ
Campus Ambassador

Secure Payment

Download Our App

© 2024 SolutionInn. All Rights Reserved