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organization theory and design

Questions and Answers of Organization Theory and Design

Consider the 26−2 IV design.(a) Suppose that the design had been folded over by changing the signs in column B instead of column A. What changes would have resulted in the effects that can be
An article by L. B. Hare (“In the Soup: A Case Study to Identify Contributors to Filling Variability,” Journal of Quality Technology, Vol. 20, pp. 36–43) describes a factorial experiment used
Heat treating is often used to carbonize metal parts, such as gears. The thickness of the carbonized layer is a critical output variable from this process, and it is usually measured by performing a
An experiment is run in a semiconductor factory to investigate the effect of six factors on transistor gain. The design selected is the 26−2 IV shown in Table P8.15.(a) Use a normal plot of the
A 16-run fractional factorial experiment in nine factors was conducted by Chrysler Motors Engineering and described in the article “Sheet Molded Compound Process Improvement,”by P. I. Hsieh and
A 16-run fractional factorial experiment in 10 factors on sand-casting of engine manifolds was conducted by engineers at the Essex Aluminum Plant of the Ford Motor Company and described in the
In an article in Quality Engineering (“An Application of Fractional Factorial Experimental Designs,” 1988, Vol. 1, pp. 19–23), M. B. Kilgo describes an experiment to determine the effect of CO2
Consider the following design:Std A B C D E y 1 −1 −1 −1 1 1 40 2 1 −1 −1 −1 1 10 3 −1 1 −1 −1 −1 30 4 1 1 −1 1 −1 20 5 −1 −1 1 −1 −1 40 6 1 −1 1 1 −1 30 7 −1 1
Consider the following design:Run A B C D E y 1 −1 −1 −1 1 −1 50 2 1 −1 −1 −1 −1 20 3 −1 1 −1 −1 1 40 4 1 1 −1 1 1 25 5 −1 −1 1 −1 1 45 6 1 −1 1 1 1 30 7 −1 1 1 1
Consider the following design:Run A B C D E y 1 −1 −1 −1 −1 −1 65 2 1 −1 −1 −1 1 25 3 −1 1 −1 −1 1 30 4 1 1 −1 −1 −1 89 5 −1 −1 1 −1 1 25 6 1 −1 1 −1 −1 60 7
Consider the following design:Run A B C D E y 1 −1 −1 −1 −1 −1 63 2 1 −1 −1 −1 1 21 3 −1 1 −1 −1 1 36 4 1 1 −1 −1 −1 99 5 −1 −1 1 −1 1 24 6 1 −1 1 −1 −1 66 7
A 26−2 factorial experiment with three replicates has been run in a pharmaceutical drug manufacturing process. The experimenter has used the following factors:Factor Natural Levels Coded Levels
An unreplicated 24−1 fractional factorial experiment has been run. The experimenter has used the following factors:Factor Natural Levels Coded Levels (x’s)A 20, 50 −1, 1 B 200, 280 −1, 1 C
An unreplicated 24−1 fractional factorial experiment with four center points has been run. The experimenter has used the following factors:Factor Natural Levels Coded Levels (x’s)A - time 10, 50
An unreplicated 25−1 fractional factorial experiment with four center points has been run in a chemical process.The response variable is molecular weight. The experimenter has used the following
An article in the International Journal of Research in Marketing (“Experimental design on the front lines of marketing: Testing new ideas to increase direct mail sales,”2006, Vol. 23, pp.
An article in Soldering & Surface Mount Technology(“Characterization of a Solder Paste Printing Process and Its Optimization,” 1999, Vol. 11, No. 3, pp. 23–26) describes the use of a 28−3
An article in Thin Solid Films (504, “A Study of Si/SiGe Selective Epitaxial Growth by Experimental Design Approach,” 2006, Vol. 504, pp. 95–100) describes the use of a fractional factorial
An article in the Journal of Chromatography A(“Simultaneous Supercritical Fluid Derivatization and Extraction of Formaldehyde by the Hantzsch Reaction,” 2000, Vol. 896, pp. 51–59) describes an
Consider the 24 factorial experiment in Problem 6.46.Suppose that the experimenters could only afford eight runs.Set up the 24−1 fractional factorial design with I = ABCD and select the responses
Consider the 24 factorial experiment for surfactin production in Problem 6.44. Suppose that the experimenters could only afford eight runs. Set up the 24−1 fractional factorial design with I = ABCD
Consider the 25 factorial in Problem 6.43. Suppose that the experimenters could only afford 16 runs. Set up the 25−1 fractional factorial design with I = ABCDE and select the responses for the runs
Consider the isatin yield data from the experiment described in Problem 6.42. The original experiment was a 24 full factorial. Suppose that the original experimenters could only afford eight runs.
Harry Peterson-Nedry (a friend of the author) owns a vineyard and winery in Newberg, Oregon. He grows several varieties of grapes and produces wine. Harry has used factorial designs for process and
A spin coater is used to apply photoresist to a bare silicon wafer. This operation usually occurs early in the semiconductor manufacturing process, and the average coating thickness and the
A 16-run experiment was performed in a semiconductor manufacturing plant to study the effects of six factors on the curvature or camber of the substrate devices produced. The six variables and their
Carbon anodes used in a smelting process are baked in a ring furnace. An experiment is run in the furnace to determine which factors influence the weight of packing material that is stuck to the
Nonregular fractions of the 2k [John (1971)].Consider a 24 design. We must estimate the four main effects and the six two-factor interactions, but the full 24 factorial cannot be run. The largest
Construct a 27−2 design. Show how the design may be run in four blocks of eight observations each. Are any main effects or two-factor interactions confounded with blocks?
Construct a 25−1 design. Show how the design may be run in two blocks of eight observations each. Are any main effects or two-factor interactions confounded with blocks?
An industrial engineer is conducting an experiment using a Monte Carlo simulation model of an inventory system.The independent variables in her model are the order quantity(A), the reorder point (B),
Fold over a 25−2 III design to produce a six-factor design.Verify that the resulting design is a 26−2 IV design. Compare this design to the 26−2 IV design in Table 8.10.
Fold over the 27−4 III design in Table 8.19 to produce an eight-factor design. Verify that the resulting design is a 28−4 IV design. Is this a minimal design?
Consider the 26−3 III design in Problem 8.19. Determine the effects that may be estimated if a single factor fold over of this design is run with the signs for factor A reversed.
Construct a 26−3 III design. Determine the effects that may be estimated if a full fold over of this design is performed.
Construct a 25−2 III design. Determine the effects that may be estimated if a full fold over of this design is performed.
Project the 24−1 IV design in Example 8.1 into two replicates of a 22 design in the factors A and B. Analyze the data and draw conclusions.
Repeat Problem 8.15 using I = −ABCD. Does the use of the alternate fraction change your interpretation of the data?
Analyze the data in Problem 6.32 as if it came from a 24−1 IV design with I = ABCD. Project the design into a full factorial in the subset of the original four factors that appear to be significant.
Consider the 25 design in Problem 6.30. Suppose that only a one-half fraction could be run. Furthermore, two days were required to take the 16 observations, and it was necessary to confound the
Construct a 27−2 design by choosing two four-factor interactions as the independent generators. Write down the complete alias structure for this design. Outline the analysis of variance table. What
Consider the leaf spring experiment in Problem 8.10.Suppose that factor E (quench oil temperature) is very difficult to control during manufacturing. Where would you set factors A, B, C, and D to
An article in Industrial and Engineering Chemistry(“More on Planning Experiments to Increase Research Efficiency,”1970, pp. 60–65) uses a 25−2 design to investigate the effect of A =
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 fractional factorial to investigate the
R. D. Snee (“Experimenting with a Large Number of Variables,” in Experiments in Industry: Design, Analysis and Interpretation of Results, by R. D. Snee, L. B. Hare, and J. B.Trout, Editors, ASQC,
Continuation of Problem 8.6. Reconsider the 24−1 fractional factorial design with I = ABCD from Problem 8.6.Set a partial fold over of this fraction to isolate the AB interaction.Select the
Continuation of Problem 8.6. In Problem 6.6, we found that all four main effects and the two-factor AB interaction were significant. Show that if the alternate fraction(I = −ABCD) is added to the
In Example 6.10, a 24 factorial design was used to improve the response rate to a credit card mail marketing offer. Suppose that the researchers had used the 24−1 fractional factorial design with I
Continuation of Problem 8.4. Suppose you have made the eight runs in the 25−2 design in Problem 8.4. What additional runs would be required to identify the factor effects that are of interest? What
Problem 6.30 describes a process improvement study in the manufacturing process of an integrated circuit. Suppose that only eight runs could be made in this process. Set up an appropriate 25−2
Consider the plasma etch experiment described in Example 6.1. Suppose that only a one-half fraction of the design could be run. Set up the design and analyze the data.
Suppose that in Problem 6.19, only a one-half fraction of the 24 design could be run. Construct the design and perform the analysis, using the data from replicate I.
Suppose that in the chemical process development experiment described in Problem 6.11, it was only possible to run a one-half fraction of the 24 design. Construct the design and perform the
Suppose that you are designing an experiment for four factors and that due to material properties it is necessary to conduct the experiment in blocks. Material availability restricts you to the use
Suppose that you are designing an experiment for four factors and that due to material properties it is necessary to conduct the experiment in blocks. Material availability restricts you to the use
Consider the full 25 factorial design in Problem 6.51.Suppose that this experiment had been run in two blocks with ABCDE confounded with the blocks. Set up the blocked design and perform the
The information on the interaction confounded with the block can always be separated from the block effect.(a) True(b) False
Consider the 25 factorial design in two blocks.If ABCDE is confounded with blocks, then which of the following runs is in the same block as run acde?(a) a (b) acd (c) bcd(d) be (e) abe (f) None of
When constructing the 27 design confounded in eight blocks, three independent effects are chosen to generate the blocks, and there are a total of eight interactions confounded with blocks.(a) True(b)
Suppose that a 22 design has been conducted. There are four replicates and the experiment has been conducted in four blocks. The error sum of squares is 500 and the block sum of squares is 250. If
Construct a 23 design with ABC confounded in the first two replicates and BC confounded in the third. Outline the analysis of variance and comment on the information obtained.
Suppose that in Problem 6.11 ABCD was confounded in replicate I and ABC was confounded in replicate II. Perform the statistical analysis of this design.
Repeat the analysis of Problem 6.5 assuming that ABC was confounded with blocks in each replicate.
Suppose that in Problem 6.5 we had confounded ABC in replicate I, AB in replicate II, and BC in replicate III.Calculate the factor effect estimates. Construct the analysis of variance table.
Consider the data in Example 7.2. Suppose that all the observations in block 2 are increased by 20. Analyze the data that would result. Estimate the block effect. Can you explain its magnitude? Do
Consider the 22 design in two blocks with AB confounded. Prove algebraically that SSAB = SSBlocks.
Consider the 26 design in eight blocks of eight runs each with ABCD, ACE, and ABEF as the independent effects chosen to be confounded with blocks. Generate the design.Find the other effects
Design an experiment for confounding a 26 factorial in four blocks. Suggest an appropriate confounding scheme, different from the one shown in Table 7.9.
The design in Problem 6.46 is a 23 factorial replicated twice. Suppose that each replicate was a block. Analyze all of the responses from this blocked design. Are the results comparable to those from
The design in Problem 6.44 is a 24 factorial. Set up this experiment in two blocks with ABCD confounded. Analyze the data from this design. Is the block effect large?
Repeat Problem 7.16 using a design in two blocks.
The experiment in Problem 6.43 is a 25 factorial.Suppose that this design had been run in four blocks of eight runs each.(a) Recommend a blocking scheme and set up the design.(b) Analyze the data
Consider the isatin yield experiment in Problem 6.42.Set up the 24 experiment in this problem in two blocks with ABCD confounded. Analyze the data from this design. Is the block effect large?
Consider the direct mail experiment in Problem 6.28.Suppose that each group of customers is in a different part of the country. Suggest an appropriate analysis for the experiment.
Using the data from the 24 design in Problem 6.26, construct and analyze a design in two blocks with ABCD confounded with blocks.
Consider the putting experiment in Problem 6.25. Analyze the data considering each replicate as a block.
Consider the fill height deviation experiment in Problem 6.24. Suppose that only four runs could be made on each shift. Set up a design with ABC confounded in replicate I and AC confounded in
Consider the fill height deviation experiment in Problem 6.24. Suppose that each replicate was run on a separate day. Analyze the data assuming that days are blocks.
Consider the data from the 25 design in Problem 6.30.Suppose that it was necessary to run this design in four blocks with ACDE and BCD (and consequently ABE) confounded.Analyze the data from this
Repeat Problem 7.7 assuming that four blocks are necessary. Suggest a reasonable confounding scheme.
Using the data from the 25 design in Problem 6.30, construct and analyze a design in two blocks with ABCDE confounded with blocks.
Repeat Problem 7.5 assuming that four blocks are required. Confound ABD and ABC (and consequently CD)with blocks.
Consider the data from the first replicate of Problem 6.11. Construct a design with two blocks of eight observations each with ABCD confounded. Analyze the data.
Consider the data from the first replicate of Problem 6.5. Suppose that these observations could not all be run using the same bar stock. Set up a design to run these observations in two blocks of
Consider the alloy cracking experiment described in Problem 6.19. Suppose that only 16 runs could be made on a single day, so each replicate was treated as a block. Analyze the experiment and draw
Consider the experiment described in Problem 6.9.Analyze this experiment assuming that each one of the four replicates represents a block.
Consider the experiment described in Problem 6.5.Analyze this experiment assuming that each replicate represents a block of a single production shift.
The display below summarizes the results of analyzing a 24 factorial design.Term Intercept Effect Estimate Sum of Squares %Contribution A 6.25 3.25945 B 5.25 110.25 57.4967 C 3.5 49 25.5541 D 0.75
Suppose that you want to replicate 2 of the 8 runs in a 23 factorial design. How many ways are there to choose the 2 runs to replicate? Suppose that you decide to replicate the run with all three
If a D-optimal design algorithm is used to create a 12-run design for fitting a first-order model in three variables with all three two-factor interactions, the algorithm will construct a 23
A 2k factorial design is a D-optimal design for fitting a first-order model.(a) True(b) False
The mean square for pure error in a replicated factorial design can get smaller if nonsignificant terms are added to a model.(a) True(b) False
Adding center runs to a 2k design affects the estimate of the intercept term but not the estimates of any other factor effects.(a) True(b) False
In a replicated 23 design (16 runs), the estimate of the model intercept is equal to one-half of the total of all 16 runs.(a) True(b) False
In an unreplicated design, the degrees of freedom associated with the “pure error” component of error are zero.(a) True(b) False
A half-normal plot of factor effects plots the expected normal percentile versus the effect estimate.(a) True(b) False
Consider the 23 shown below:When running a designed experiment, it is sometimes difficult to reach and hold the precise factor levels required by the design. Small discrepancies are not important,
An article in Quality and Reliability Engineering International(2010, Vol. 26, pp. 223–233) presents a 25 factorial design. The experiment is shown in Table P6.15.(a) Analyze the data from this
Suppose that a full 24 factorial uses the following factor levels:Factor Low (−) High(+)A: Acid strength (%) 85 95 B: Reaction time (min) 15 35 C: Amount of acid (mL) 35 45 D: Reaction temperature
Suppose that you want to run a 23 factorial design. The variance of an individual observation is expected to be about 4. Suppose that you want the length of a 95 percent confidence interval on any

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