Question
At a call centre, callers have to wait till an operator is ready to take their call. To monitor this process, 5 calls were recorded every hour for the 8-hour working day. The data below shows the waiting time in seconds:
Time | Sample Number | ||||
1 | 2 | 3 | 4 | 5 | |
9 a.m | 8 | 9 | 15 | 4 | 11 |
10 | 7 | 10 | 7 | 6 | 8 |
11 | 11 | 12 | 10 | 9 | 10 |
12 | 12 | 8 | 6 | 9 | 12 |
1 p.m. | 11 | 10 | 6 | 14 | 11 |
2 | 7 | 7 | 10 | 4 | 11 |
3 | 10 | 7 | 4 | 10 | 10 |
4 | 8 | 11 | 11 | 11 | 7 |
(i) Use the data to construct control charts for mean and comments about the
process. If process is out of control, then calculate the revised control limits.
(ii) Construct the CUSUM chart when the process is under control and draw the conclusion about the process.
(iii) If the specification limits as the 8±2, then calculate the process capability index Cpk and impetrate the result.
(iv) Also find the percentage of calls lie outside the specification limits assuming that calls follow the normal distribution.
A system has four components connected in parallel configuration with reliability 0.2, 0.4, 0.5, 0.8. To improve the reliability of the system most, we have to replace the component which reliability is 0.2.
The R- chart is suitable when subgroup size is greater than 10.
In single sampling plan, if we increase acceptance number then the OC curve will be steeper.
If the effect of summer and winter is not constant on the sale of AC then we use the additive model of the time series.
Consider the time series model
Where
(i) Is this a stationary time series?
(ii) What are the mean and variance of the time series?
(iii) Calculate the autocorrelation function.
(iv) Plot the correlogram.
Differentiate between the autoregressive and moving average models of time series.
The failure data for 40 electronic components is shown below:
Operating Time (in hours) | 0-5 | 5-10 | 10-15 | 15-20 | 20-25 | 25-30 |
Number of Failures | 5 | 7 | 6 | 4 | 5 | 4 |
Operating Time (in hours) | 30-35 | 35-40 | 40-45 | 45-50 | ≥50 | |
Number of Failures | 4 | 0 | 2 | 1 | 2 |
Estimate the reliability, cumulative failure distribution, failure density and failure rate functions.
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