Hw4_new - IEOR 130 Methods of Manufacturing Improvement Spring 2009 Prof Leachman HW#4 due Tuesday March 3 1 It has been claimed that all defect

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IEOR 130 Methods of Manufacturing Improvement Spring, 2009. Prof. Leachman. HW #4, due Tuesday March 3. 1. It has been claimed that all defect density models basically predict the same yield if the average number of defects per die is less than one. To test this assertion, compute the die yield using the simple Poisson model, the Murphy model, and the Seeds model for the following data: Die area Defect Density (sq cm) (per sq cm) 0.10 0.5 0.20 0.5 0.50 0.5 0.50 1.0 1.00 0.5 1.00 0.75 1.00 1.0 1.00 1.5 2.00 1.5 2. Determine the underlying defect density using the Poisson model and using the Murphy model for the following data. (The Murphy model requires iterative trial and error calculations.) Die area Die yield (sq cm) (percent) 0.25 92.0 0.50 85.0 0.50 92.0 1.00 65.0 1.00 85.0 3. A wafer fab is considering the purchase of a new type of metal sputtering machine. In order to decide whether or not to purchase the new machines, management would like to determine the increased revenue per week that would be generated by the factory if the
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This note was uploaded on 03/16/2010 for the course ORMS 130 taught by Professor Leachman during the Spring '10 term at University of California, Berkeley.

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Hw4_new - IEOR 130 Methods of Manufacturing Improvement Spring 2009 Prof Leachman HW#4 due Tuesday March 3 1 It has been claimed that all defect

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