This set of Statistical Quality Control Multiple Choice Questions & Answers (MCQs) focuses on “Process Capability Analysis using Designed Experiments and Attribute Data”.
1. In the design of experiments, the ____ variables are adjusted first.
a) Output controllable
b) Output uncontrollable
c) Input uncontrollable
d) Input controllable
Explanation: In the design of experiments, the value of input controllable variables is varied to find the desired output quality of a process.
2. Which of these can be varied?
a) Input Controllable variables
b) Input uncontrollable variables
c) Output controllable variables
d) Output uncontrollable variables
Explanation: Only the input controllable variables can be varied. This is because all the other variables are uncontrollable like input uncontrollable variables etc.
3. Which of the following is not done in the designing of experiments?
a) Varying the input variables (controllable)
b) Observation of the output
c) Making a relationship between input and output
d) Process control
Explanation: In the design of experiments, the controllable inputs of a process are varied, and the output of the process is observed simultaneously, then a relationship between the inputs and the outputs, is made.
4. Which of these is not a function of designing of experiments?
a) To find the set of process variables influential on output
b) To determine the optimum level of the variables
c) To estimate maximum output possible with optimum value of variables
d) To eliminate some uncontrollable inputs
Explanation: Designed experiments are helpful in finding, which set of process variables is influential on the output, and at what levels these variables should be held to optimize the process performance.
5. Which of these is the easiest method for finding the sources of variability?
a) Designed Experiments
d) Acceptance sampling
Explanation: Designed experiments are useful in determining the optimum level of the process variables for a better process performance, so we can find the sources of variability simultaneously.
6. Which of these is not a method to judge the process capability?
a) Control charts
b) Attributes data
c) Acceptance sampling
d) Designed experiments
Explanation: Process capability can be determined by the usage of either of control charts, or attributes data or designed experiments. The process capability ratios, histogram and the probability plots also can be used.
7. DPU is ____
a) Decrement per unit
b) Defects per unit
c) Design per unit
d) Decimals per unit
Explanation: The term “DPU” is used in the determination of process capability by using the attribute data. Here, DPU stands for Defects per unit.
8. DPMO stands for ____
a) Defects per million opportunities
b) Decrement per minute opportunity
c) Defects per minute opportunity
d) Designation per million opportunities
Explanation: DPMO represents the defects per million opportunities. It takes the complexity of an unit into account when calculating the process capability.
Explanation: DPMO is calculated by using the following formula,
As this formula contains the number of opportunities, it takes the number of times that an error can be occurred. So it is much accurate.
10. If there are 85 defects in the lot containing 150 units, what is the value of DPU?
Explanation: DPU is calculated by using the following formula,
By calculating the DPU, we get, DPU=0.57.
11. If the DPMO for a sample containing 45 units is 0.237. If the total number of defects is 32, what will be the number of opportunities?
Explanation: DPMO is calculated using the formula,
Putting the values, we get, the number of opportunities= 3.
12. PPM defectives can be a measure of the process capability. Although an equivalent sigma level can also be used.
Explanation: As a particular sigma level shows a particular amount of defectives, e.g. 2700 ppm is equivalent to 3-sigma process; an equivalent sigma level can be used instead of using the ppm defectives as a measure of the process capability.
13. DPU can be evaluated only when, the variable data is available.
Explanation: As DPU suggests the defects found per unit of the product, which is an attribute data, we do not need the variable data to calculate the DPU.
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