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1 | In the Measure phase of DMAIC, what are the items needed? |
A)![](/olcweb/styles/shared/spacer.gif) | A solution to the problem. |
B)![](/olcweb/styles/shared/spacer.gif) | Data for doing a Design of Experiments. |
C)![](/olcweb/styles/shared/spacer.gif) | Data to help break down the problem. |
D)![](/olcweb/styles/shared/spacer.gif) | A problem, a process, a financial benefit, a metric and a goal, and a customer metric. |
E)![](/olcweb/styles/shared/spacer.gif) | A valid measurement system. |
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2 | In the Measure phase, we are going to establish a defect rate, but black belts typically see the defect rate go down. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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3 | What is one of the first important milestones that indicates that a black belt is on track? |
A)![](/olcweb/styles/shared/spacer.gif) | Lack of buy-in from the team members. |
B)![](/olcweb/styles/shared/spacer.gif) | No data is available. |
C)![](/olcweb/styles/shared/spacer.gif) | The champion does not know the project benefit. |
D)![](/olcweb/styles/shared/spacer.gif) | The process map is complete. |
E)![](/olcweb/styles/shared/spacer.gif) | When the team adopts a desire to constantly learn |
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4 | How many data points do you need to have a short-term capability? |
A)![](/olcweb/styles/shared/spacer.gif) | Two data points. |
B)![](/olcweb/styles/shared/spacer.gif) | Over 100 data points. |
C)![](/olcweb/styles/shared/spacer.gif) | Fewer than five data points. |
D)![](/olcweb/styles/shared/spacer.gif) | Between 30 and 50 data points. |
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5 | Process mapping is a: |
A)![](/olcweb/styles/shared/spacer.gif) | A one-time event. |
B)![](/olcweb/styles/shared/spacer.gif) | A tool used for statistical validation. |
C)![](/olcweb/styles/shared/spacer.gif) | A tool used at the end of the DMAIC process. |
D)![](/olcweb/styles/shared/spacer.gif) | An ongoing living document used throughout the DMAIC process. |
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6 | A failure modes and effects analysis FMEA describes the following. |
A)![](/olcweb/styles/shared/spacer.gif) | Potential defects |
B)![](/olcweb/styles/shared/spacer.gif) | The risk of the problem |
C)![](/olcweb/styles/shared/spacer.gif) | Capability of the process |
D)![](/olcweb/styles/shared/spacer.gif) | Root cause |
E)![](/olcweb/styles/shared/spacer.gif) | What you want to know about a type of defect |
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7 | An FMEA is complete during the Measure phase. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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8 | In an FMEA, what is the RPN if POCC is 5, PDET is 4, and the PSEV is 9? |
A)![](/olcweb/styles/shared/spacer.gif) | 0 |
B)![](/olcweb/styles/shared/spacer.gif) | 20 |
C)![](/olcweb/styles/shared/spacer.gif) | 9 |
D)![](/olcweb/styles/shared/spacer.gif) | 180 |
E)![](/olcweb/styles/shared/spacer.gif) | None of the above |
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9 | Measurement system analysis MSA is used: |
A)![](/olcweb/styles/shared/spacer.gif) | To assess capability |
B)![](/olcweb/styles/shared/spacer.gif) | To validate the data used for analysis |
C)![](/olcweb/styles/shared/spacer.gif) | As an optional tool during the DMAIC process |
D)![](/olcweb/styles/shared/spacer.gif) | A nonstatistical assessment of the process |
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10 | MSA is a tool that can be omitted in the DMAIC model. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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11 | Cp is a capability index with the units measured in: |
A)![](/olcweb/styles/shared/spacer.gif) | Meters |
B)![](/olcweb/styles/shared/spacer.gif) | Gallons |
C)![](/olcweb/styles/shared/spacer.gif) | Yards |
D)![](/olcweb/styles/shared/spacer.gif) | Productivity |
E)![](/olcweb/styles/shared/spacer.gif) | Defect rate or yield |
F)![](/olcweb/styles/shared/spacer.gif) | No units |
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12 | If the Cp is 1.0, what is the sigma value? |
A)![](/olcweb/styles/shared/spacer.gif) | 1 |
B)![](/olcweb/styles/shared/spacer.gif) | 2 |
C)![](/olcweb/styles/shared/spacer.gif) | 3 |
D)![](/olcweb/styles/shared/spacer.gif) | 6 |
E)![](/olcweb/styles/shared/spacer.gif) | None of above |
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13 | Can Cp be greater than Cpk? |
A)![](/olcweb/styles/shared/spacer.gif) | Yes |
B)![](/olcweb/styles/shared/spacer.gif) | No |
C)![](/olcweb/styles/shared/spacer.gif) | Sometimes |
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14 | What is the Cp and Cpk index number when you have a six-sigma capability? |
A)![](/olcweb/styles/shared/spacer.gif) | Cp = 1.0 and Cpk = 0.5 |
B)![](/olcweb/styles/shared/spacer.gif) | Cp = 1.5 and Cpk = 2.0 |
C)![](/olcweb/styles/shared/spacer.gif) | Cp = 3.0 and Cpk = 6.0 |
D)![](/olcweb/styles/shared/spacer.gif) | Cp = 2.0, and Cpk = 1.5 |
E)![](/olcweb/styles/shared/spacer.gif) | None of the above |
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15 | What is the purpose for gauge R&R? |
A)![](/olcweb/styles/shared/spacer.gif) | Statistical analysis to evaluate measure error |
B)![](/olcweb/styles/shared/spacer.gif) | To understand repeatability and reproducibility of your MSA |
C)![](/olcweb/styles/shared/spacer.gif) | To help validate what is a defect and what is not
d. Look for variation within operator and between operators |
D)![](/olcweb/styles/shared/spacer.gif) | To gauge the rest and relaxation needed for a black belt |
E)![](/olcweb/styles/shared/spacer.gif) | a through d |
F)![](/olcweb/styles/shared/spacer.gif) | None of the above |
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16 | If your data are nonnormal, you are stuck in the Measure phase. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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17 | What is the layperson’s description of a hypothesis test? |
A)![](/olcweb/styles/shared/spacer.gif) | Helps to solve problems |
B)![](/olcweb/styles/shared/spacer.gif) | Breaking the problem up |
C)![](/olcweb/styles/shared/spacer.gif) | Dissecting the data |
D)![](/olcweb/styles/shared/spacer.gif) | There is no way to make it simple |
E)![](/olcweb/styles/shared/spacer.gif) | A tool to compare stuff |
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18 | What are the reasons for nonnormality? |
A)![](/olcweb/styles/shared/spacer.gif) | a. All data have that pattern |
B)![](/olcweb/styles/shared/spacer.gif) | Due to abnormal conditions |
C)![](/olcweb/styles/shared/spacer.gif) | Bimodal conditions exist |
D)![](/olcweb/styles/shared/spacer.gif) | Different normal distributions are within the data set |
E)![](/olcweb/styles/shared/spacer.gif) | a and d |
F)![](/olcweb/styles/shared/spacer.gif) | None of the above |
G)![](/olcweb/styles/shared/spacer.gif) | c and d |
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19 | If you have a nonnormal data set, does transforming the data fix the nonnormal causes of the problem? |
A)![](/olcweb/styles/shared/spacer.gif) | Yes |
B)![](/olcweb/styles/shared/spacer.gif) | No |
C)![](/olcweb/styles/shared/spacer.gif) | None of the above |
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20 | What would best describe a bimodal distribution? |
A)![](/olcweb/styles/shared/spacer.gif) | A manufacturing process |
B)![](/olcweb/styles/shared/spacer.gif) | Material variance |
C)![](/olcweb/styles/shared/spacer.gif) | Transactional defects |
D)![](/olcweb/styles/shared/spacer.gif) | Mutlivari chart |
E)![](/olcweb/styles/shared/spacer.gif) | Within-part variation |
F)![](/olcweb/styles/shared/spacer.gif) | An X-factor that has two different Y-output distributions |
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21 | How does comparing factors help solve the problem? |
A)![](/olcweb/styles/shared/spacer.gif) | It breaks down the problem into the vital X’s. |
B)![](/olcweb/styles/shared/spacer.gif) | It contrasts the trivial many versus the vital few. |
C)![](/olcweb/styles/shared/spacer.gif) | It helps answer the hypothesis question. |
D)![](/olcweb/styles/shared/spacer.gif) | It deals with data facts that can be proven. |
E)![](/olcweb/styles/shared/spacer.gif) | It focuses the team on data, not opinion. |
F)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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22 | Tool wear can cause nonnormal distributions. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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23 | What plot describes the many distributions in one graph in quartiles? |
A)![](/olcweb/styles/shared/spacer.gif) | Interval plot |
B)![](/olcweb/styles/shared/spacer.gif) | Capability plot |
C)![](/olcweb/styles/shared/spacer.gif) | Probability plot |
D)![](/olcweb/styles/shared/spacer.gif) | Median plot |
E)![](/olcweb/styles/shared/spacer.gif) | Box plot |
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24 | Is it okay to remove outliers in a data set that cause an increase in standard deviation? |
A)![](/olcweb/styles/shared/spacer.gif) | Yes |
B)![](/olcweb/styles/shared/spacer.gif) | No |
C)![](/olcweb/styles/shared/spacer.gif) | Yes, only if you know the cause of stopping it |
D)![](/olcweb/styles/shared/spacer.gif) | b and c |
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25 | What is the best way to show multimode distributions? |
A)![](/olcweb/styles/shared/spacer.gif) | a. Bimodal graph |
B)![](/olcweb/styles/shared/spacer.gif) | b. Interval plot |
C)![](/olcweb/styles/shared/spacer.gif) | Dot plot |
D)![](/olcweb/styles/shared/spacer.gif) | One-way ANOVA |
E)![](/olcweb/styles/shared/spacer.gif) | Box plot |
F)![](/olcweb/styles/shared/spacer.gif) | a and b |
G)![](/olcweb/styles/shared/spacer.gif) | b through d |
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26 | Lowess analysis fits a robust line through the data to display a relationship between X and Y. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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27 | In a multivari analysis, the X levels are randomly selected levels during the study. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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28 | Different operators producing the same Y cannot cause nonsymmetrical distributions: |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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29 | Two-way interaction cannot cause asymmetrical distributions. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
C)![](/olcweb/styles/shared/spacer.gif) | Sometimes |
D)![](/olcweb/styles/shared/spacer.gif) | None of the above |
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30 | In simple terms, what is meant by a p-value of less than 0.05? |
A)![](/olcweb/styles/shared/spacer.gif) | That there are no significant difference |
B)![](/olcweb/styles/shared/spacer.gif) | The variance terms are equal |
C)![](/olcweb/styles/shared/spacer.gif) | The mean has a shift of 1.5 sigma |
D)![](/olcweb/styles/shared/spacer.gif) | You’re 95 percent confident that there is a statistical difference |
E)![](/olcweb/styles/shared/spacer.gif) | All the above |
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31 | The 95 percent confidence interval increases as the standard deviation decreases. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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32 | A multvari analysis is an active form of comparing within- and between-part variation over time. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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33 | You do not need a capable measurement system for multivari analysis. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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34 | Shift-to-shift variation can be measured on one shift. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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35 | A hypothesis test can show the interaction of the factors. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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36 | Sample size has no effect on the width of a distribution. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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37 | If an X has been identified as statistically significant, do you disregard it owing to an expert telling you to ignore it? |
A)![](/olcweb/styles/shared/spacer.gif) | No |
B)![](/olcweb/styles/shared/spacer.gif) | Yes |
C)![](/olcweb/styles/shared/spacer.gif) | Ask what data does the expert have to show to ignore it |
D)![](/olcweb/styles/shared/spacer.gif) | None of the above |
E)![](/olcweb/styles/shared/spacer.gif) | a and c |
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38 | If you were told to purchase new technology for over $2 million to make the business more productive, but the hypothesis of the new technology shows no statistical difference in productivity, do you purchase it? |
A)![](/olcweb/styles/shared/spacer.gif) | No |
B)![](/olcweb/styles/shared/spacer.gif) | Yes |
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39 | What does hypothesis testing fundamentally change? |
A)![](/olcweb/styles/shared/spacer.gif) | It’s a departure from the “I think” and “I feel” culture |
B)![](/olcweb/styles/shared/spacer.gif) | Destroys the emotions of the problem |
C)![](/olcweb/styles/shared/spacer.gif) | Turns the problem into a fact-based process |
D)![](/olcweb/styles/shared/spacer.gif) | Data are now used to drive decisions |
E)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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40 | If you changed an X that was proven to be statistically significant and the Y was given to you with 3 months prior to the change and 1 month after, could you show a before and after hypothesis to validate the change? |
A)![](/olcweb/styles/shared/spacer.gif) | No |
B)![](/olcweb/styles/shared/spacer.gif) | Yes |
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41 | Using an Anderson-Darling normality test, normal data have a p-value of less than 0.5. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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42 | How many runs does a 23 full factorial experiment consist of ? |
A)![](/olcweb/styles/shared/spacer.gif) | 6 |
B)![](/olcweb/styles/shared/spacer.gif) | 5 |
C)![](/olcweb/styles/shared/spacer.gif) | 8 |
D)![](/olcweb/styles/shared/spacer.gif) | 12 |
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43 | In an experiment, inputs are allowed to vary randomly throughout the specification range. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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44 | One-factor-at-a-time experiments generate more powerful data than a full factorial experiment. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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45 | What is an experimental factor? |
A)![](/olcweb/styles/shared/spacer.gif) | The input variables for the experiment |
B)![](/olcweb/styles/shared/spacer.gif) | The metrics of the process |
C)![](/olcweb/styles/shared/spacer.gif) | A covariant |
D)![](/olcweb/styles/shared/spacer.gif) | The largest standard deviation |
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46 | What does orthogonal mean? |
A)![](/olcweb/styles/shared/spacer.gif) | One or more effects that cannot unambiguously be attributed to a single factor or factor interaction |
B)![](/olcweb/styles/shared/spacer.gif) | Involves running the experimental runs in random order |
C)![](/olcweb/styles/shared/spacer.gif) | A property that ensures that all experimental factors are independent of each other; no correlation exists between X’s. |
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47 | What is a “Balanced Design?” |
A)![](/olcweb/styles/shared/spacer.gif) | A design in which each of the variables has a different number of runs at the high and low levels |
B)![](/olcweb/styles/shared/spacer.gif) | A design in which each of the variables or factors has the same number of runs at the high and low levels |
C)![](/olcweb/styles/shared/spacer.gif) | A design in which two of the variables has a different number of runs at the high and low levels |
D)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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48 | Standard order is the same as run order. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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49 | Why use factorial plots? |
A)![](/olcweb/styles/shared/spacer.gif) | Allow you to see the plots of the main effects |
B)![](/olcweb/styles/shared/spacer.gif) | Allow you to see the interaction plots |
C)![](/olcweb/styles/shared/spacer.gif) | Allow you to see the cube plots |
D)![](/olcweb/styles/shared/spacer.gif) | Show how to set each factor to either maximize or minimize the response |
E)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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50 | What tools can be used to determine if factors have interaction? |
A)![](/olcweb/styles/shared/spacer.gif) | Balanced ANOVA |
B)![](/olcweb/styles/shared/spacer.gif) | Standardized effects |
C)![](/olcweb/styles/shared/spacer.gif) | Interaction plots |
D)![](/olcweb/styles/shared/spacer.gif) | Fractional factorial fits |
E)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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51 | What does it mean when no p-values are presented in the ANOVA output? |
A)![](/olcweb/styles/shared/spacer.gif) | Means the factors are statistically significant |
B)![](/olcweb/styles/shared/spacer.gif) | Means the factors are not different |
C)![](/olcweb/styles/shared/spacer.gif) | Only one repetition was run at each treatment combination |
D)![](/olcweb/styles/shared/spacer.gif) | Had no center points |
E)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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52 | Why do we replicate our experimental runs? |
A)![](/olcweb/styles/shared/spacer.gif) | So we can look for special causes |
B)![](/olcweb/styles/shared/spacer.gif) | To obtain a better estimate of the error and look at interactions |
C)![](/olcweb/styles/shared/spacer.gif) | To determine the factor levels |
D)![](/olcweb/styles/shared/spacer.gif) | So we can look at the same thing run again |
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53 | To use a center point in your experimental design, at least one factor must be able to be set at its midpoint coded value = 0. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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54 | Why use center points in your experimental design? |
A)![](/olcweb/styles/shared/spacer.gif) | To check for linearity |
B)![](/olcweb/styles/shared/spacer.gif) | To check for interactions |
C)![](/olcweb/styles/shared/spacer.gif) | To detect curvature |
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55 | If a center point is significant, its p-value in the ANOVA table will be greater than 0.05. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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56 | Fractional factorial designs require more runs than full factorial designs given the same number of factors. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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57 | What is the main reason for using a fractional factorial design? |
A)![](/olcweb/styles/shared/spacer.gif) | Allows you to test and screen a large number of factors in fewer runs |
B)![](/olcweb/styles/shared/spacer.gif) | Gives you good estimates of low order interactions |
C)![](/olcweb/styles/shared/spacer.gif) | Gives you relative significance of the factors |
D)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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58 | Given three factors, A, B, and C, the highest-order interaction would be ABC. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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59 | In a four-factor 1/2 fractionated design, the AB interaction is confounded with the CD interaction. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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60 | What does it mean when A is confounded with BC? |
A)![](/olcweb/styles/shared/spacer.gif) | A is contributing to the result. |
B)![](/olcweb/styles/shared/spacer.gif) | BC is contributing to the result. |
C)![](/olcweb/styles/shared/spacer.gif) | The computed coefficients are related to the sum of the two individual effects. |
D)![](/olcweb/styles/shared/spacer.gif) | The sums of squares are related to the sum of the two individual effects. |
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61 | In a resolution IV design, two-factor interactions are aliased with three-factor interactions. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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62 | In a resolution III design, single factors are not aliased with any other factors. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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63 | The identity expression I + ABCD is used to generate the confounding pattern. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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64 | Why are resolution V designs preferred over resolution III and resolution IV designs? |
A)![](/olcweb/styles/shared/spacer.gif) | No main effect is confounded with any other main effect or second-order interactions. |
B)![](/olcweb/styles/shared/spacer.gif) | No second-order interactions are confounded with any other second-order interaction, and second-order interactions are confounded with third-order interactions. |
C)![](/olcweb/styles/shared/spacer.gif) | Allows for the differentiation of the effects down to the second order, assuming that the effects of third-order interactions are negligible. |
D)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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65 | Why should you do a hypothesis test before running a DOE? |
A)![](/olcweb/styles/shared/spacer.gif) | Statistically test for the correct factors |
B)![](/olcweb/styles/shared/spacer.gif) | Find the trivial many |
C)![](/olcweb/styles/shared/spacer.gif) | To ensure that your measurement system is good |
D)![](/olcweb/styles/shared/spacer.gif) | To ensure that you have all the process steps identified |
E)![](/olcweb/styles/shared/spacer.gif) | To identify as many of the vital few factors prior to DOE |
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66 | What is the mission of the Improve phase? |
A)![](/olcweb/styles/shared/spacer.gif) | Find the relationships between X and Y |
B)![](/olcweb/styles/shared/spacer.gif) | Validate hypothesis tests |
C)![](/olcweb/styles/shared/spacer.gif) | Which inputs to control in the next phase |
D)![](/olcweb/styles/shared/spacer.gif) | Run a pilot to validate experiment |
E)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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67 | Can you calculate epsilon-square percent contribution for the DOE given that the degree of freedom for each factor is different in the ANOVA? |
A)![](/olcweb/styles/shared/spacer.gif) | Yes |
B)![](/olcweb/styles/shared/spacer.gif) | No |
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68 | The WECO (Western Electric Company) rules are based on probability. We know that for a normal distribution, the probability of encountering a point outside ±2.5 is 0.3 percent. This is a rare event. Therefore, if we observe a point outside the control limits, we conclude that the process has shifted and is unstable. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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69 | Outliers usually have a significant effect on an equation derived with regression analysis. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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70 | Using Y = f(X), do we set tolerance limits for Y? |
A)![](/olcweb/styles/shared/spacer.gif) | Yes |
B)![](/olcweb/styles/shared/spacer.gif) | No |
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71 | What is the residual? |
A)![](/olcweb/styles/shared/spacer.gif) | It is the equation from the data. |
B)![](/olcweb/styles/shared/spacer.gif) | It is the standard error of the equation. |
C)![](/olcweb/styles/shared/spacer.gif) | It indicates how well the equation fits. |
D)![](/olcweb/styles/shared/spacer.gif) | It is a calculation of the expected value minus the observed value. |
E)![](/olcweb/styles/shared/spacer.gif) | c and d |
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72 | What are control charts? |
A)![](/olcweb/styles/shared/spacer.gif) | Design of experiment (DOE) |
B)![](/olcweb/styles/shared/spacer.gif) | A plot showing the Y over time |
C)![](/olcweb/styles/shared/spacer.gif) | Charts showing average control |
D)![](/olcweb/styles/shared/spacer.gif) | Charts used to routinely monitor quality |
E)![](/olcweb/styles/shared/spacer.gif) | None of the above |
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73 | What does a P-chart track? |
A)![](/olcweb/styles/shared/spacer.gif) | Process chart showing the main factors |
B)![](/olcweb/styles/shared/spacer.gif) | Sample size of the process over time |
C)![](/olcweb/styles/shared/spacer.gif) | Simple chart used to track the number of nonconforming units, percentage of defective parts, assuming that sample size is not necessarily constant |
D)![](/olcweb/styles/shared/spacer.gif) | None of the above |
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74 | A DOE is always needed to solve process issues. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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75 | The purpose of performing a designed experiment is to determine what? |
A)![](/olcweb/styles/shared/spacer.gif) | The mathematical relationship Y = F(x1, x2, x3, . . .) |
B)![](/olcweb/styles/shared/spacer.gif) | Which X’s most impact Y and therefore need to be controlled |
C)![](/olcweb/styles/shared/spacer.gif) | The level of each X to achieve the desired mean Y |
D)![](/olcweb/styles/shared/spacer.gif) | The level of each X to minimize the variability of Y |
E)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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76 | Within the DOE, the easiest way to test for curvature is to include center points. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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77 | The most common response surface design is called the central composite design. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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78 | Control plans provide a written description of the actions that are required at each phase of the process to ensure that all process inputs and outputs will be in a state of control. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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79 | Control plans are only generated at the start of the life cycle of a product. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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80 | SPC is a statistically based graphing technique that compares current process data to a set of stable control limits established from normal process variation. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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81 | Control limits and specification limits are the same thing: |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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82 | Control limits are typically set at plus or minus 2 standard deviations from the target of the control chart. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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83 | Regular residuals are the actual values of the residuals calculated by subtracting the expected value from the observed value. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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84 | What is the best description of a data transform? |
A)![](/olcweb/styles/shared/spacer.gif) | A transformation of the data using a power table to treat linearity in the data |
B)![](/olcweb/styles/shared/spacer.gif) | A transformation of the data using a power table to treat nonlinearity in the data |
C)![](/olcweb/styles/shared/spacer.gif) | Improves the variance within the data |
D)![](/olcweb/styles/shared/spacer.gif) | A transformation of the data using a power table to treat the units of the data |
E)![](/olcweb/styles/shared/spacer.gif) | It transforms data into a more approximate normal distribution |
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85 | Outliers usually have a significant effect on an equation derived with regression analysis. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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86 | When an “out of control” situation is signaled on a control chart, the person using the chart will know why the data are giving the signal. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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87 | Once the special causes of variation in a process have been discovered and eliminated, the long-term goal of anyone managing a process will be to reduce common cause variation by improving the process or system itself. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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88 | An "out of control" situation in a production process may be signaled by a sample f output that generates a data point outside the control limits on either the Xbar–R range chart. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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89 | Mistakeproofing seeks to gain permanence by eliminating or rigidly controlling human intervention in a process. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |
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90 | Six Sigma product and process design or process changes made to the product or process that eliminate the error condition from occurring are called what? |
A)![](/olcweb/styles/shared/spacer.gif) | TQM |
B)![](/olcweb/styles/shared/spacer.gif) | Mistakeproofing |
C)![](/olcweb/styles/shared/spacer.gif) | Mistake elimination |
D)![](/olcweb/styles/shared/spacer.gif) | Foolproofing |
E)![](/olcweb/styles/shared/spacer.gif) | All of the above |
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91 | Systems that monitor the process and automatically adjust critical X’s to correct settings are called what? |
A)![](/olcweb/styles/shared/spacer.gif) | Full automation |
B)![](/olcweb/styles/shared/spacer.gif) | Process interruption |
C)![](/olcweb/styles/shared/spacer.gif) | Mechanism |
D)![](/olcweb/styles/shared/spacer.gif) | SPC |
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92 | In order for mistakeproofing systems to operate effectively, the following rules must not be observed. |
A)![](/olcweb/styles/shared/spacer.gif) | The systems must be installed and properly adjusted before process startup. |
B)![](/olcweb/styles/shared/spacer.gif) | The systems must be periodically audited and maintained. |
C)![](/olcweb/styles/shared/spacer.gif) | Systems are periodically disabled. |
D)![](/olcweb/styles/shared/spacer.gif) | Inoperative or missing systems must be repaired or replaced before operating the process. |
E)![](/olcweb/styles/shared/spacer.gif) | System overrides must not be used except in an emergency. |
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93 | The EWMA or Exponentially Weighted Moving Average chart is a variable data control chart. |
A)![](/olcweb/styles/shared/spacer.gif) | True |
B)![](/olcweb/styles/shared/spacer.gif) | False |