# Anna University Question Papers-B Tech-CE-VI-Sem-Quality Control And Reliability Engineering

ANNA UNIVERSITY, B.E. AUTOMOBILE ENGINEERING, VI SEMESTER,

QUALITY CONTROL AND RELIABILITY ENGINEERING

PART – A                                                                                                                                                                                                                (10 x 2 = 20 Marks)

1. Distinguish between quality assurance and quality control.

2. Name any four quality tools used in statistical quality control.

3. Distinguish between chance and assignable causes.

4. What is process capability index?. Explain its significance.

5. Define the terms AQL and LTPD.

6. What is the effect of sample size on the OC curve?

7. What is OPL listing?

8. Three lamps are connected in parallel to produce light in a hall. The reliabilities are 0.92, 0.95 and 0.96. Find the reliability of the total lamp system. If the systems are connected in series, determine the reliability of the system.

9. What is shape parameters? State its effect on the failure rate.

10. An electronic system has a MTBF of 1000 hours and a MTTR of 40 hours. Determine its availability.

PART – B                        (5 x 16 = 80 Marks)

11. The percent of water absorption is an important characteristic of common building brick. A certain company occasionally measured this characteristic of its product but records were never kept.  It was decided to analyze the process with control chart. Twenty-five samples of four bricks each yielded the results.

Estimate the control limits for X  and R chart. If any point lies out of the control limits, estimate the revised control limits.

12. a) Construct the OC curve for the single sampling plan :

N = 830, n = 62, c = 1 and r = 2. Use at least seven points

( OR )

b) (i)  Given P0.10 = 0.053 and P0.95 = 0.014, Determine the single sampling plan which exactly meets the consumer’s stipulation and comes closer to the producer’s stipulation.

(ii) Determine the acceptance equation for the following double sampling plan.

N = 60000 n1 = 80, c1 = 2, r1 = 4, n2 = 160, c2 = 5, r2  = 6.

Determine also the probability of acceptance for an incoming process quality of 2% (i.e. 100 p’ = 2%)

13. a) (i) Distinguish between a P chart and a C chart. Discuss the situations in which C chart is most appropriate to use.

(ii)   A machine makes bolts in batches of 1024. Twenty consecutive batches were tested and the number of rejectable bolts in each batch is given below.

 Batch No. Number of Rejectable bolts 1 2 2 3 3 7 4 1 5 0 6 4 7 8 8 7 9 1 10 3 11 2 12 1 13 5 14 4 15 3 16 12 17 8 18 1 19 2 20 2

Draw a control chart for the fraction defective with the control limits.IF any point lies out of the control limits, then estimate the revised control limits.

( OR )

b) (i) Explain in detail about the Deming’s fourteen points.

(ii)  Write short notes on the following:

1) Quality circle     2) ISO 9000   3) Kaizen

14. a) (i) Determine the acceptance and rejection limits for a sequential life testing plan where the acceptable mean life (qo) is 50,000 hours and the  unacceptable mean life (q1) is 2000 hours. The desired producer’s and consumer’s risks are 10%.

(ii) Explain the Batch Tub curve in detail.

( OR )

b) Construct an OC curve for the sampling plan specified as n = 24, T = 149 and r = 8. Use at least seven points.

15. a) (i) What is reliability? Explain in detail the different techniques employed in improving the reliability.

(ii) Explain briefly the product life cycle

( OR )

b)    (i)   Determine the time terminated, with replacement mean life sampling plan where the producer’s risk of rejecting lots with mean life of 800 hours is 0.05 and the consumer’s risk of accepting lots with mean life of q1  = 220 hours is 0.10. The sample size is 30.

(ii)   The following table indicates the time a lot of electronic pats operated until failure. The times are presented in the order in which the trials are measured and included 30 measurements made with a constant failure rate of 0.0005 per hour.

Compute the respective estimates of mean life in hours that would have been approximated after 1000, 3000, 5000 and   7713 hours of testing.