(The Criteria Used to Make Decisions on the Amount of Inventory) * ! " * #$%%& * * !"#$%%"& 1061 '& ()+ % ,! (&-10600 '"+ & (% . ' /( &234#5# 7%(/ " ( (4$ %+ /&23# / " ( (3%# $!((( 89: #& #(% . ;#"$!"+%4# / " ( (4$ %+ /&!</ )/ ( " ( (4$ %+ // %4/$ %, # ((( # 23 %8 (4 #(";#7", ABC analysis !=54$ %+ /!<(, ! " ( ((<< (Class) #<A (Class A) <B(Class B) 7",4##! ./ " ( ( 4$ %+ /&%/ @$ "###7"D9E 80/20 /$ 57# 7%7"/$ !!$(replenishment)<C(Class C) /3,=&23%#$!(make to stock: MTS)/$ = 43(@2. (make to order: MTO)@83 ((/!/ ( #7<A B &!<'# / " ( (4$ %+ /(;#""33.86 ,, -:%# " ( (/ !!!@ Abstract This research the purpose to set criteria for decision making in the quantity of inventory stock. To reduce the amount of inventory of the storage plant a case study of plastic molding, This research by collecting data from a given quantity of finished product inventory. Found that the problem isthe volumes of finished inventories are much more than necessary. Due to the forecast of a factory method with dislocation. Then define the analysis method using ABC Analysis with all finished product and how to control the inventory of each group (Class) group A (Class A) and Group B (Class B), Use the determination level of the oµª´Ã¨ª·¥µ«µ­¦r¸ $GYDQFHG6FLHQFH amount of finished product inventory in stock and shortage goods. Using the 80/20 theory as a basis for the decision and used as Replenishment system (replenishment), Group C (Class C) change the method manufacturing to store (make to stock: MTS), Is based on a purchase order (make to order: MTO), After updating Forecasts in Group A and B found that. Can reduce the amount of inventory in stock 33.86 percent. Keywords: Inventory management/ ABC analysis "(< (" %#$!7+ /( "4$ %+ / @83 (((/. '"#& 3<4 %&!/ )/ " ( ( @83 (< (= 7"" $!9 " ( (+ (8. ((<(. /$ ((: #& /# #4 , %!!= &23%#$! !! &ISO 2001:2008 GMP # =5. ( # 71 #!<(/$ / #!% (/^ (#!% # 5 # #4.=;" -- #/ %%! 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" /!#4 , %!! = &23 %# $ ! /$ !!= ;< ! oµª´Ã¨ª·¥µ«µ­¦r¸ $GYDQFHG6FLHQFH & (&7" 7 " "&23 %#< (7" @83 (/$ =%& # /! % =+"! /$ =+ " 4 # (Delphi technique) 1.2 (((# "+ " ( (4$ %+ /%# $! / %%! 4 7" "4$ %+ /!(# " (+<7 ( " @83 ( < ( =7"7 "&.2 3 7 ( "# /</ 2. "+37"7#4 2.1 "+# #3(= ( =5. ( # 71 "(.(<#2 2554 '8( ( 2557 %438 "+ 2.2 "+ 4 73 ( @2. ' #! "+ 4 73 ( = ( =5 3. ! " + 3.1 !"+#( = 5" ( .(<#2 2554 '8 ( ( 2557 4 # , ABC Analysis 4#57< Class % (# 3.2 4#, ! " ( (7< Class 3.2.1 =57Class A Class B 7", ! " ( (# &%" "#2 3.2.2 =57Class C /3,%= &23%#$! (make to stock) /$ = 43 (@2. (make to order) &23 # / " ( (4$ %+ / #./ #" 1. &23"(537"7.(/ " ( (4$ %+ /(((<( 2. &23#/ " ( (4$ %+ /3 %#$!( " 20 0&'0#" 1. "(537"7.(/ " ( (4$ %+ /Class A, Class B 2. 37"7 % .( <#2 E '8( 2557 3. ,&7", ( /1" 2 '% 1. ;#"537"7.(/ " ( (4$ %+ /Class A, Class B 2. #/ " ( ( 4 $ % + /3 %#$!(" 33.86 3. &23/$ (37"7.(/ " ( ('#!(((( #,#" % ./$ 4#537"7 .( / " ( ( 4$ %+ / &23#/ " ( ( 7/ =/ ! ! / " ( ( 4 $ % + / < ( /!/ ( 1. 89&/%%! ((( 1.1 8 9&3 ;/(/ ) / )3 &!7(( 2 / " ( ( 4$ %+ /%4 47"&.23 7%#$!;< oµª´Ã¨ª·¥µ«µ­¦r¸ $GYDQFHG6FLHQFH <'2 @2. @83 (7<#2 % + " < @2. 3 ((%4 # =+"! /$ =+"& " ( " /# /! # "(7 / !!%/ " ( (32+< %894%"+7 ((% (&!/) 1.1 / " ( (4$ %+ / %4 1.2 &2.3%#$!;<&(& 1.3 # " + " ( ( ( //+7< ( " 1.4 # < # 23(& 3.3 & % 53 7 "7 .( / " ( (4$ %+ /7Class A Class B %" "#2#7"D9EE 80/20 3.4 /=.(/ " ( (4$ %+ /7Class A Class B %" " #2 %E80/20 #& (/ !! 3#"%4/&"3 1. 7'0&-8 ((<(. /$ ((: #& /# #4 , %!!=&23%#$! (make to stock) ""+<7((7"+ " * <47&((( #% <:3(7/ 2556 7% 1 (/ )/ " ( (4$ %+ /%4 oµª´Ã¨ª·¥µ«µ­¦r¸ $GYDQFHG6FLHQFH 2.1.2 Class B /$ =53 #<23 (<( 1- 6 #2 #%!< ( Class B " % 4 =5 13 2.1.3 Class C /$ =53 #;< 6 #2 #% !<( Class C " %4 =5 30 2. ,84##"% 2.1 4 " + #= 5 .( # 71 4 #7" ABC Analysis #(. 2.1.1 Class A /$ =53 #<23 ( ;< 1 #2 # %!<( Class A " %4 =528 ", ",#3 #3 4+ 4+ //%ůĂƐƐ% % ůĂƐƐ ε µÎ ª¦µ¥µ¦ µª ª¦µ ª ¦µ ¦ ¥ ¥ µ¦¦ 400 30 2 20 100 0 Class Cl C las asss A C Cl Class las asss B Cl C Class las asss C 288 133 30 7% 2 %4=5.( #(((<( 2.2 4#, ! " ( (4$ %+ /7Class A Class B 2.2.1 =57Class A 2 =53#<23(;< 1 oµª´Ã¨ª·¥µ«µ­¦r¸ #2 =57Class B #<23( <( 1- 6 #2 #4"+ "(4 #/ !!! ==7<=5 $GYDQFHG6FLHQFH 7% 3 #/ !!!== (=5 xxx (Class A (<#2 +<7.7# /$ "+ '3( <. #/$ " &% " "#2 #7"D9E E 80/20 #&% " ( (4$ %+ / ( (;" 3"80 "#2"20 2.2.2 4 " + # "( <(#2 2554 '8( ( 2557 / #"(%4 42 #2 7", ! " ( (# 4# .(# %4 8 . (. <<! 500 #&%# oµª´Ã¨ª·¥µ«µ­¦r¸ $GYDQFHG6FLHQFH % 1 "7< . &23&%7.(/ " ( (4$ %+ / ( ( =5 xxx &%(0#) #. &"/ &"// &"/ 0<& 0-500 17 40.48 40.48 59.52 501-1000 1 2.38 42.86 57.14 1001-1500 0 0.00 42.86 57.14 1501-2000 7 16.67 59.52 40.48 2001-2500 2 4.76 64.29 35.71 2501-3000 9 21.43 85.71 14.29 3001-3500 3 7.14 92.86 7.14 3501-4000 3 7.14 100.00 0.00 # 42 100 2.2.3 #!D9EE80/20 #7" , & (&23 / ! ! #4 $ ! " + # =5 <( xxx (class A .(<#2 2554 '8(#2 ( 2557 / !! ,&. ( 4 , #(. Moving Average, Single Exponential Smoothing, Double Exponential Smoothing, Winter Method #&%" < # 23 (Mean Absolute Percentage Error : MAPE) 433# %(3 1 &!< = 5 <( xxx (class A .(/ " ( ( 4$ %+ / ( (!<(/$ %4 8 . < .< (%4 500 ## 4/$ /$ "&23&%/ " ( ( #!. #D9EE 80/20 %&!<.( / " ( (33000 #<#2 %" 385.71 "#2" 14.29 oµª´Ã¨ª·¥µ«µ­¦r¸ $GYDQFHG6FLHQFH % 2 / !!,&(.( 4 , !,&((( # Minimum Forecasting Maximum MAPE Moving average Single exponential smoothing 0 554 2,562 5,451 2,590 4,626 77 71 Double exponential smoothing 953 2,938 4,922 65 Winter method 669 1,661 2,653 20 Delphi (( 9,600 "&0"<&""%2557 2,805 "(3 9,600 ##% (7 %(32 23!!,&. ( #2 2557 +< 3 2,805 #23! 4 ,& (#", Winter !.(#!/ " ( (4$ %+ /# Method < MAPE 433# 7#2 7"D9EE80/20 34 #;"3 3,000 #< 2557 "(<( 669 - 2,653 # #2 &!< #7#2 2557 " < # 23 +<3" 20 23 %42,805 # / ! ! ! , & (((( & " (7#2 2557 % 3 / !!,4 ##! " ( (4$ %+ /<(z !##2 2557 #, 8/' ,HJ %<&""%2557 Winter method ,&((( 0# 669-2,653 9,600 4##!/ " ( ( #D9EE 80/20 3,000 "&0"<&""%2557 2,805 oµª´Ã¨ª·¥µ«µ­¦r¸ $GYDQFHG6FLHQFH 7% 4 + < " ( (</" (/!/ ( =5 Class C /3,%=&23 %#$! (make to stock) /$ = 43 (@2. (make to order) #(/ !/ ( '# / " ( ( 4 $ %+ /(;#" < /" 3"33.86 3#" , & # /! (((( < # 23%# % (+< 23 (%((( "#2 (%8(=7/ !< . (3 4 7" " !(3 " /&;/ 23 (%#7"( < (= 7"&.23%# $!;<&(& #(((;< #" $! 9 " 4#, ! @83 ((((& % < & ( <474# "(7 + ( < 23 4 (% ( "(7"7/ ! (((;#" $($ 4 )7.(/ " ( ( #&%" "#27"5 # 7%#7"D9E E80/20 &23#/ " ( ( #4#/ " ( (( =57Class A Class B 7" /$ !! $ (replenishment) 7< oµª´Ã¨ª·¥µ«µ­¦r¸ &&& % &$) (. (2547). ' ' 8#.', 8 '13 "." . & , / )) ! 5 %{( . ,.(%'. (2547). ' /'' ' 8 % L N1 &8 & O%&, / ))!5 %{(. $GYDQFHG6FLHQFH Giri, B. and Chauduri, K.S. (1998). Deterministic Models of Perishable Inventory with stock-dependent rate and nonlinear holding cost. European journal of Operation Research, 105(3), 467-474. Magee, J.F. and Boodman, D.M. (1974). Production Planning and Inventory Control. New York: McGraw-hill. Peterson, R. and Silver, E.A. (1979). Decision Systems for Inventory Management and Production Planning. New York: John Wiley & Sons. William, J.S. (2002). Operations Management. New York: McGraw-hill. &!. (2549). /!/ (!!! " ( ( #7" ABC Analysis. + 11", 185(1), 150-155. , , ( . (2542). 7Q/''. &,/ ))!5 %{(. Ferguson, M., Jayaraman, V. and Souza, G.C. (2007). Application of the EOQ model with nonlinear holding cost to inventory management of perishable. European journal of Operation Research, 180(1), 485-490. oµª´Ã¨ª·¥µ«µ­¦r¸ $GYDQFHG6FLHQFH