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Unformatted text preview: 1 INSE 6220 -- Week 12 Advanced Statistical Approaches to Quality Acceptance Sampling Final Exam Review Dr. A. Ben Hamza Concordia University 2 Acceptance Sampling Why Acceptance Sampling and not 100% Inspection? Testing is destructive Cost of 100% inspection is high 100% inspection is not feasible (require too much time) If vendor has excellent quality history Advantages and Disadvantages of Sampling Advantages Less expensive Reduced damage Reduces the amount of inspection error Disadvantages Risk of accepting bad lots, rejecting good lots. Less information generated Requires planning and documentation 3 Acceptance Sampling Problem: A lot (shipment) is received. A sample is taken from the lot. Some quality characteristic of the units in the sample is inspected. On the basis of this inspection information, the lot is sentenced accept or reject Type of sampling plans classification is by data type, variables and attributes Based on the number of samples required for a decision: Single-sampling plans Double-sampling plans Multiple-sampling plans Sequential-sampling plans 4 Lot formation Lots should be homogeneous. Larger lots are preferred over smaller ones. Lots should be conformable to materials-handling systems used in both supplier and consumer facilities. Random Sampling Single Sampling plan A lot of size N submitted for inspection. Single sampling plan defines: Sample size, n Acceptance number, c Operating Characteristic (OC) Curve To measure the performance of a sampling plan. The OC curve plots the probability of accepting the lot versus the lot fraction defective . Show the probability of a lot submitted, with certain fraction defective, will be either accepted or rejected. 5 OC Curve Lot size, N large # defective, d , in a random sample of size n will follow a binominal distribution with parameters, n and p . The probability of acceptance is P (d c) ! ( ) 1 , 0, 1, 2, ..., !( )! n k k n P d k p p k n k n k ! (Accept lot) ( ) ( ) 1 !( )! c n k k a k n P P p P d c p p k n k OC Curve plots the probability of accepting the lot P a versus the lot fraction defective p (true proportion nonconforming) . Example: An apple producer has 500 baskets of apples, containing 20 each (10000 apples in the lot). A buyer wants to inspect 10 of the apples before accepting the lot (if 2 or less are bruised). That is n=10, N=10000, c=2. Suppose 20% of the apples are bruised, what is the probability of accepting such a lot?...
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This note was uploaded on 09/07/2011 for the course INSE 6210 taught by Professor Benhamza during the Fall '10 term at Concordia Canada.
- Fall '10