Industrial Engineering Questions and Answers – OC Curve

This set of Industrial Engineering Multiple Choice Questions & Answers (MCQs) focuses on “OC Curve”.

1. The average percentage of defective items in the finally accepted products after the screening is called average outgoing quality (AOQ).
a) True
b) False
View Answer

Answer a
Explanation: Quality of the rejected lots will be improved by subjecting them to 100% inspection and defectives are replaced by good items. The average quality of the products of accepted lots in sampling and rectified lots together is called the average outgoing quality (AOQ).

2. What is the formula for the average outgoing quality (AOQ) when the sample size (n) is much less compared to the lot size (N)?
a) AOQ = Pa × P
b) AOQ = Pa + P
c) AOQ = Pa – P
d) AOQ = Pa × P × N – nN
View Answer

Answer a
Explanation: The general formula for average outgoing quality (AOQ) is given by AOQ = Pa × P × N – nN. But, when sample size (n) is much less compared to the lot size (N) then it is given as AOQ = Pa × P.

3. The maximum value of average outgoing quality (AOQ) is called Average outgoing quality limit (AOQL).
a) True
b) False
View Answer

Answer a
Explanation: The maximum value of average outgoing quality (AOQ) is called Average outgoing quality limit (AOQL). AOQL is the maximum possible value of the average percentage defectives in the outgoing products after inspection and rectification.
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4. What does the ordinate of OC curve represent?
a) Proportion of lots accepted
b) Proportion of lots rejected
c) Acceptance number
d) Fraction defectives
View Answer

Answer a
Explanation: OC curve is a graph of fraction defective in a lot against the probability of acceptance. Its ordinate represents the proportion of lots accepted and the abscissa represents fraction defective.

5. What is the abscissa of the OC curve?
a) Proportion of lots accepted
b) Proportion of lots rejected
c) Acceptance number
d) Fraction defectives
View Answer

Answer d
Explanation: OC curve is a graph of fraction defective in a lot against the probability of acceptance. Its ordinate represents the proportion of lots accepted and the abscissa represents fraction defective.

6. In the OC curve, if the defectives in the lot are zero, then what is the probability of acceptance?
a) 0.5
b) 0.6
c) 0.99
d) 1
View Answer

Answer d
Explanation: When there is no defective in the lot submitted for the inspection, then the lot can be accepted without any rejection. Hence the probability of acceptance for such type of lots is one.

7. An ideal OC curve can perfectly discriminate between good and bad lots which cannot be possible by any of the sampling plans.
a) True
b) False
View Answer

Answer a
Explanation: An ideal OC curve can perfectly discriminate between good and bad lots. No sampling plan can have an ideal OC curve. Ideal OC curve can only be possible through 100% inspection.
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8. What is the region between the acceptable quality region and objectionable quality region in an OC curve?
a) Non-defective quality region
b) Rejection quality region
c) Defective quality region
d) In-different quality region
View Answer

Answer d
Explanation: The OC is divided into three regions. They are
Acceptable quality region
In-different quality region
Objectionable quality region
The in-different quality region is located between the acceptable quality region and objectionable quality region. The acceptable quality region is on the left side to the in-different quality region while the objectionable quality region is on the right to it.

9. What is the good lots in the acceptable quality region that are rejected because of a bad sample which otherwise has to be accepted termed as?
a) Consumer’s risk
b) Producer’s risk
c) Retailer’s risk
d) Distributor’s risk
View Answer

Answer b
Explanation: The good lots in the acceptable quality region that are rejected because of bad sample for inspection which otherwise has to be accepted is termed as producer’s risk. This is the producer’s risk because even though the lot is good in its quality, it is rejected because of the bad sample drawn for inspection. It leads to a loss to the producer and hence this is the producer’s risk.
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10. A lot in the _______ region is worse than AQL and better than RQL.
a) Acceptable quality region
b) Objectionable quality region
c) In-different quality region
d) Rejection quality region
View Answer

Answer c
Explanation: A lot in the in-different quality region is worse than AQL and better than RQL. Submitted lot consists of fraction defectives more than AQL.

11. In _______, no decision can be taken regarding the acceptance or rejection of lot.
a) Acceptable quality region
b) Objectionable quality region
c) In-different quality region
d) Rejection quality region
View Answer

Answer c
Explanation: In the in-different quality region, no decision can be made regarding the acceptance or rejection of lot. 100% inspection is needed to overcome this indecision.

12. ___________ is the probability of defective lots being accepted which otherwise would have been rejected.
a) Producer’s risk
b) Consumer’s risk
c) Retailer’s risk
d) Distributor’s risk
View Answer

Answer b
Explanation: Consumer’s risk is the probability of defective lots being accepted which otherwise would have been rejected. When a bad lot is accepted because of a few good items that present in the sample chosen for inspection, then it is termed as the consumer’s risk.

Sanfoundry Global Education & Learning Series – Industrial Engineering.

To practice all areas of Industrial Engineering, here is complete set of 1000+ Multiple Choice Questions and Answers.

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

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