ÐÏࡱá>þÿ  þÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿfraction defective is .0075 or less; FGOOD = .0075; ! Consumer considers the lot bad if the lot fraction defective is .025 or more; FBAD = .025; ! We accept the lot if sample contains 2 or less; ACCEPTAT = 2; ! The model; ! What is producer risk of rejecting a good lot; ! Using the (exact) hypergeometric distribution; PGOODH = 1 - @PHG( LOTSIZE, LOTSIZE * FGOOD, SAMPSIZE, ACCEPTAT); ! Using binomial approx. to the hypergeometric; PGOODB = 1 - @PBN( FGOOD, SAMPSIZE, ACCEPTAT); ! Using the Poisson approx. to the binomial; PGOODP = 1 - @PPS( FGOOD * SAMPSIZE, ACCEPTAT); ! Using Normal approximation; PGOODN = 1 - @PSN( (ACCEPTAT + .5 - MUG) / SIGMAG); ! where; MUG = SAMPSIZE * FGOOD; SIGMAG = ( MUG * ( 1 - FGOOD)) ^ .5; ! What is the consumer risk of accepting a bad lot; ! Using the hypergeometric; PBADH = @PHG( LOTSIZE, LOTSIZE * FBAD, SAMPSIZE, ACCEPTAT); ! Binomial; PBADB = @PBN( FBAD, SAMPSIZE, ACCEPTAT); ! Poisson; PBADP = @PPS( FBAD * SAMPSIZE, ACCEPTAT); ! Using Normal approximation; PBADN = @PSN( ( ACCEPTAT + .5 - MUB) / SIGMAB); ! where; MUB = SAMPSIZE * FBAD; SIGMAB = ( MUB * ( 1 - FBAD)) ^ .5; END MODEL: ! Acceptance sampling: taking one or more samples at random from a lot, inspecting each of the items in the sample(s), and deciding on the basis of inspection results whether to accept or reject the entire lot. (See Schroeder, Oper. Mgt.) This Acceptance Sampling model illustrates the effect of choice of distribution.; ! From a lot of 400 items; LOTSIZE = 400; ! We take a sample of size 100; SAMPSIZE = 100; ! 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Binomial;\cf2 \par PBADB = \cf1 @PBN\cf2 ( FBAD, SAMPSIZE, ACCEPTAT); \par \cf3 ! Poisson;\cf2 \par PBADP = \cf1 @PPS\cf2 ( FBAD * SAMPSIZE, ACCEPTAT); \par \cf3 ! Using Normal approximation;\cf2 \par PBADN = \cf1 @PSN\cf2 ( ( ACCEPTAT + .5 - MUB) / SIGMAB); \par \cf3 ! where;\cf2 \par MUB = SAMPSIZE * FBAD; \par SIGMAB = ( MUB * ( 1 - FBAD)) ^ .5; \par \par \cf1 END\cf2 \par \par } ì‹{\rtf1\ansi\ansicpg1252\deff0\deflang1033{\fonttbl{\f0\fnil\fcharset0 Courier New;}} {\colortbl ;\red0\green0\blue255;\red0\green0\blue0;\red0\green175\blue0;} \viewkind4\uc1\pard\cf1\f0\fs20 MODEL\cf2 : \par \par \cf3 ! Acceptance sampling: taking one or more samples \par at random from a lot, inspecting each of the \par items in the sample(s), and deciding on the basis \par of inspection results whether to accept or reject \par the entire lot. (See Schroeder, Oper. Mgt.) This \par Acceptance Sampling model illustrates the effect \par of choice of distribution.;\cf2 \par \par \cf3 ! From a lot of 400 items;\cf2 \par LOTSIZE = 400; \par \cf3 ! We take a sample of size 100;\cf2 \par SAMPSIZE = 100; \par \cf3 ! Producer considers the lot good if \par the lot fraction defective is .0075 or less;\cf2 \par FGOOD = .0075; \par \cf3 ! Consumer considers the lot bad if \par the lot fraction defective is .025 or more;\cf2 \par FBAD = .025; \par \cf3 ! We accept the lot if sample contains 2 or less;\cf2 \par ACCEPTAT = 2; \par \par \cf3 ! The model;\cf2 \par \cf3 ! What is producer risk of rejecting a good lot;\cf2 \par \cf3 ! Using the (exact) hypergeometric distribution;\cf2 \par PGOODH = 1 - \cf1 @PHG\cf2 ( LOTSIZE, LOTSIZE * FGOOD, \par SAMPSIZE, ACCEPTAT); \par \cf3 ! Using binomial approx. to the hypergeometric;\cf2 \par PGOODB = 1 - \cf1 @PBN\cf2 ( FGOOD, SAMPSIZE, ACCEPTAT); \par \cf3 ! Using the Poisson approx. to the binomial;\cf2 \par PGOODP = 1 - \cf1 @PPS\cf2 ( FGOOD * SAMPSIZE, ACCEPTAT); \par \cf3 ! Using Normal approximation;\cf2 \par PGOODN = \par 1 - \cf1 @PSN\cf2 ( (ACCEPTAT + .5 - MUG) / SIGMAG); \par \cf3 ! where;\cf2 \par MUG = SAMPSIZE * FGOOD; \par SIGMAG = ( MUG * ( 1 - FGOOD)) ^ .5; \par \par \cf3 ! What is the consumer risk of accepting a bad lot;\cf2 \par \cf3 ! Using the hypergeometric;\cf2 \par PBADH = \cf1 @PHG\cf2 ( LOTSIZE, LOTSIZE * FBAD,