Q4. Calculation (10 points in total) A camera manufacturer has a policy of inspe
ID: 335831 • Letter: Q
Question
Q4. Calculation (10 points in total) A camera manufacturer has a policy of inspecting every incoming camera lens to ensure it conforms to specifications (1) Do you agree with this policy? If you want to question the wisdom of the policy, what 5 points) (2) A new manager of the manufacturer uses past inspection data concerning the proportion of the defective camera lens to construct a p chart which turns out to be stable. The average fraction of defective lens was found to be 0.003. I costs $0.60 to inspect an incoming camera lens and it costs $6.0 to repair it before leaving the factory. Use the kp rule to 5 points) information would you need? determine which policy should be used for incoming camera lens.Explanation / Answer
Regarding the policy-
Inspection of every camera lens is a good policy, and should be carried on if possible in the organization. The benefits of inspecting every produce for its quality are-
1. The final product is defect free.
2. The customer satisfaction index rate is high as there are lesser defective products
3. If there are defects in the product, they can be identified at inital stages, and the defect can be cured easily
4. The cost of handling the returns or defective pieces is highly reduced
Although, checking every product can be time consuming, and this policy should be used carefully. The cons for this can be-
1. The quality checking process can be very time consuming and can delay production
2. The overall cost to check the quality can be higher than the cost to handle the pieces returned on average
3. The manpower used to check the quality can be a underutilized resource at times
Mostly, companies use statistics and control charts -X bar, R bar, P charts etc, for quality testing. What they do is, take a random sample out of every production lot, and find the mean errors in that lot, using the statistics rules, and creating a confidence interval, the mean error rate in the entire lot is estimated, and production machines or labour are adjusted accordingly to control the errors. The mean error data go on control charts, which help keeping a regular check on the total errors in different lots, and if the errors go beyond the accepted rate, changes in production method, or whatever be the discrepancy is taken out of the system.
Hence, each product should be tested for quality when -
1. Production lot is very small
2. Customer has sent a customized order
Information needed to see if an alternative is better-
1. Cost of handling a returned defetive piece
2. Total errors per production lot
3. Cost of current method used
Ques 2
Average fraction of defective produce = 0.003
For example, there is a lot of 1000 products
Total cost to check each product will be = .6*1000= $600
Total defects produced if each product is not tested= .003*1000 = 3
Cost of handling a defect rate = 6*3 = $18
Total cost turns out to be =$618 to remove defects out of a production lot
There are no costs associated to alternative choices that can be used in place of this method, but if the cost for using p chart to find mean error in a production lot, and handling the return product costs less than than the current method of inspecting each piece, that method should be used.
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