Statistical Quality Control Questions and Answers – SPC Methods and Philosophy – Statistical Basis of the Control Chart – 2

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This set of Statistical Quality Control Quiz focuses on “SPC Methods and Philosophy – Statistical Basis of the Control Chart – 2”.

1. In the name of the OC curve, OC stands for ________
a) Operation Characteristic
b) Operating Characteristic
c) Operator Characteristic
d) Operated Characteristic
View Answer

Answer: b
Explanation: The OC curve stands for Operating Characteristic curve which is used to develop an understanding of probability variation of the Type II error in the quality control.
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2. The general theory of Control charts was first developed by ________
a) Walter A. Shewhart
b) Deming
c) ISO
d) ASQC
View Answer

Answer: a
Explanation: W.A. Shewhart was the first person to develop an applicable theory for quality control for the processes used in manufacturing a product. This was known as the general theory of Control Charts.

3. Control charts are the part of _______ step of DMAIC process.
a) Define
b) Measure
c) Act
d) Control
View Answer

Answer: d
Explanation: The control charts use the data from the measure step to analyze the process situation and then apply the steps to control the quality of the process. So they are used in the control step, analyze step of DMAIC process.

4. The size of sample is 5 for a process. If the process standard deviation is 0.15 micron, and the mean of process is 1.5 micron, the standard deviation of the sample average will be _______
a) 0.0500
b) 0.1000
c) 0.6710
d) 0.0671
View Answer

Answer: d
Explanation: The standard deviation of the sample average is calculated by,
σx=σ/√n
Putting σ=0.15, n=5, we get, σx=0.0671.

5. For a process, sample size=5, process standard deviation=0.15, mean=1.5, and the std. deviation of mean is 0.0671. What will be the value of 3σ upper control limit for the construction of control chart?
a) 1.70
b) 1.29
c) 1.92
d) 0.170
View Answer

Answer: a
Explanation: As we know, UCL=;n=5; σ=0.15, \(\overline{x}\) = 1.5; σx=0.0671{from question}
So, UCL=1.5+3(0.0671)=1.7013.

6. The correct expression for UCL for construction of a control chart is given by _____
a) UCL = \(\overline{x} + Z_{\frac{\alpha}{2}} (\sigma_x)\)
b) UCL = \(\overline{x} – Z_{\frac{\alpha}{2}} (\sigma)\)
c) UCL = \(\overline{x} – Z_{\frac{\alpha}{2}} (\sigma_x)\)
d) UCL = \(\overline{x} + Z_{\frac{\alpha}{2}} (\sigma)\)
View Answer

Answer: a
Explanation: The UCL is defined as the upper control limit for the control chart and it is evaluated as,
UCL = \(\overline{x} + Z_{\frac{\alpha}{2}} (\sigma_x)\); where \(\overline{x}\) is the mean of process, σx is the std. deviation of mean and \(Z_{\frac{\alpha}{2}}\) is a arbitrary constant.
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7. The general model for the lower control limit for a value of quality characteristic “w” will be _____
a) LCL = μw + Lσw
b) LCL = μw – Lσ
c) LCL = μw – Lσw
d) LCL = μw + Lσ
View Answer

Answer: c
Explanation: The general expression for LCL of a quality characteristic “w” is given by,
LCL = μw – Lσw;
Where “L” denotes the distance of control limits from the center line.

8. The center line of a control chart will be having a value ______
a) Higher than mean of quality characteristic
b) Lower than mean of quality characteristic
c) Equal to mean of quality characteristic
d) Which is higher than UCL
View Answer

Answer: c
Explanation: The center line of the control chart denotes the value of the process mean of the quality characteristic. It is always the desired value.

9. Which of these is a part of corrective action process associated with a control chart?
a) OCAP
b) DMAIC
c) OC curve
d) LCL
View Answer

Answer: a
Explanation: OCAP (Out-of-control-plan) is an important part of the corrective action process associated with the control charts which uses results of control charts to control the process.

10. Which of these can be used to estimate capability of the process?
a) Control charts
b) Process mean
c) Acceptance Sampling
d) Designed Experiments
View Answer

Answer: a
Explanation: Control charts are also used as estimating device as their results can be used to estimate the process capability of a certain process.

11. Control charts for central tendency and the variability are called _________ control charts.
a) Variables
b) Attributes
c) Acceptance
d) Rejections
View Answer

Answer: a
Explanation: It is convenient to describe the variables with a measure of central tendency and measure of variability. So the control charts for central tendency and variability are called Variable control charts.

12. The control charts formed for judgment of conformities and non-conformities are called ______ control charts.
a) Variables
b) Attributes
c) Acceptance
d) Rejections
View Answer

Answer: b
Explanation: Attributes are increased on the discrete scale and they give results as either conformity or non-conformity. So the charts plotted for non-conformities and conformities are called Attributes control charts.
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13. Control charts with points around mean and in predicted or fixed manner indicate ________
a) Stationary variability
b) Non-stationary variability
c) Auto correlated variability
d) Process out of control
View Answer

Answer: a
Explanation: The control charts which have points around the mean and in a predicted manner indicate that the process has stationary variability. This explains the nature of the process.

14. Auto correlated stationary process data is dependent on each other.
a) True
b) False
View Answer

Answer: a
Explanation: In the auto correlated data, one data observations influence the next point, which means, if one point is above the mean in the control chart, the next one will also be above the mean.

15. Control charts are not effective in defect prevention.
a) True
b) False
View Answer

Answer: b
Explanation: The control charts will help in the “Do it right from the first time” philosophy. This means, it helps to control the quality of the process, which means we get more conforming products than from out-of-control process.

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @ LinkedIn