ϣ˾ຫεבᇴڱٺބЅ̬ڇચ̝ᑕϡࡁտ
லރှ
ᓑЪ̂ጯ఼ᙊିֈ͕̚
ၡ! ࢋ
ϣ˾ຫεבᇴͽـజᇃھᑕϡдᄦౄຽ۞யݡݡኳෞҤ˯Ăܕֽ̏ᑕ ϡᅳાᕖ̂ҌܧϠயᄦౄ۞Җຽ̚ĄּтĈෞҤֻᑕથĂͽࢋՐֻᑕથ೩ய ݡݡኳٕڇચݡኳćٗгயЅ̬ڇચĂͽ೩ۏІᄃᜪމಫЪ۞јΑதĄώኢ
͛ᑕϡдބЅ̬̝ڇચ˯Ăͽഇބಫ̬۰ٚፉܫయЇĂ֭೩ֻމ
͗Ր࡚႕ބ۞ڇચĄ͛̚ͽ૱జշ̃ᗕ͞҂ᇋ̝˛γдЯ৵Ĉѐ᛬म
ă̍үᗓăጯ።৺मளă၆͞ќˢă֗ăវࢦ̈́ࣧϠछलˠᇴĂ࿅
ϣ˾ݡኳຫεבᇴ۞ᖼೱΐͽณ̼Ă֭ણ੩ᗕ͞၆Я৵̝ࢦࢋޘࢋՐĂຉᓁ јಏ˘ຫεࣃүࠎՙඉតᇴĂഇֹބЅ̬۰੫၆շ̃ᗕ͞ፄઊ୧І۞ݵЪ ޘĂЕָ̝ˠᏴĂͽ၆މ͗೩ֻྵщБض۞ܲᅪĂԼචᄃމ̝͗ม
۞ᙯܼĂ೩چڇચ۞ݡኳĄ
ᙯᔣෟĈϣ˾ຫεבᇴăބЅ̬ăՙඉតᇴă೩چڇચݡኳĄ
IMPROVING MARRIAGE BROKER CUSTOMER SERVICE USING TAGUCHI LOSS FUNCTIONS
Wei-Ning Pi
Center of General Education National United University Miao-Li, Taiwan 360, R.O.C.
Key Words: Taguchi Loss Functions, marriage broker, decision variables, promote service quality.
ABSTRACT
Taguchi loss functions (TLFs) are usually used for measurements of product quality. Now they have been applied to many related non-manufacturing fields. The purpose of this research is to introduce the application of TLFs to a study of marriage brokers. Seven different attributes are considered: age, location of work place, education states, income, height, weight and size of nuclear family. The Taguchi loss function quantifies these attributes in terms of quality loss. These quality losses are combined into one global decision variable to rank the candidates whose attributes most closely match the client’s. Under the assumption that similarities between bride and groom promote successful marriage, this approach should increase the level of satisfaction among clients. An example application of the model is also presented to demonstrate its working.
˘ă݈! ֏
Ϥϣ˾ϛ˘(Genichi Taguchi)ٙ೩̝ݡኳ̍۞நه
͞ڱĂЯд̍ຽࠧᒔ։р̝јड़Ă߇ᇃצࢦෛĄϣ˾
၆Ķݡኳķ۞ؠཌྷߏĈĶயݡྻਖ਼זᜪމ͘̚ޢĂ၆ۤົٙ
ౄј̝ຫεķĄೱήྖᄲĂݡኳຫεߏݡኳপّϏਕЪϫ ᇾࣃٙౄј̝ϡ̈́ྤ̝Ąϣ˾дݡኳ̝ؠཌྷ̚ΐ ˢ˞ܛ۞ໄهĂֹݡኳຫεјࠎݡኳԼච࿅̝̚В Тᄬ֏[1]Ąϫ݈ϣ˾ຫεבᇴ۞ᑕϡĂ̏ྯ௲็۞༺ҍĂ
҃ᅳાᕖणҌܧᄦౄຽĄKethley ඈˠ[2]ᑕϡдٗ
гயЅ̬ຽ۞ڇચ˯Ăͽ೩ۏІᄃᜪމ̝ಫЪјΑ፟
தĂѩдЅ̬ڇચຽ˯۞ᑕϡߏ˘࣎ᅲᆊࣃ۞ࡁտĂЯ
ਕۏІֶ̙Т̝ᅮՐপ̶ّҾᄃϫᇾࣃઇͧྵĂ֭ޙ ϲ˘इෞҤրĂͽֻᜪމүࠎᏴፄ̝ણ҂Ăซ҃೩ಫ ЪјΑதĂ֭೩ڇચݡኳĄ
༊̫ĂބЅ̬̳ΦЯᑕۤົᅮՐĂтܥޢߋඎਠг ڒϲĄᄏބ̝ࢦࢋĂΟѣځĂ̠̚ĈĶӖ̝̄Ăౄ
ბͼ͈Ă̈́Ҍ˵Ă၅ͼ͇гĄķ[3] ٽԔנ็̠ĈĶѣ
͇гޢѣ༱ۏĂѣ༱ۏޢѣշ̃Ăѣշ̃ޢѣ͈Ă ѣ͈ޢѣͭ̄Ăѣͭ̄ޢѣӖҊĂѣӖҊޢѣ˯
˭Ăѣ˯˭ޢᖃ̝ѣٙĄ͈̝Ă̙Ξͽ̙˳˵Ąķ [4] ٽ็̠ĈĶ͇г༱ۏ̝ώĂ͈ˠ̝ࣖؕĄķ[5] Ϥѩ ΞۢĂշ̃ଐԸຍЪĂඕࠎ͈ĂјछलĂˠࣖჹბͼ ѩĂۤົಧૄٺѩĄ҃ᖃѣڃ݄Ăྐࢵᙯ༢ĂддӮពϯ ԧ઼ҋΟӈপҾࢦෛބᄃछलĄ
҃ᐌॡ۞ซՎĂனˠϠ߿ѓ༨ăᑅ˧ᆧΐĂ
ͻᄃளّ̢જ۞፟ົĄშྮϹ̓ĂᔵܮӀĂᑢ͵
ࠧĂ·႕ౝ֪ĂЫᓪ˯༊ĂॡѣٙჷĄણΐෛ̓༼ϫĂ дБ઼៍ிќෛ̝˭Ă࠹̢੨၆Ăᑌԉ̙щĂ૱΄ˠݒՎĄ Гΐ˯ᇾၳĶ߿ҋԧķ۞៍هҖĂՐĶϠ߿ݡኳķ
۞ຍᙊٶᐝĂĶှ̻ᑿķ۞ӵ́ĂຏଐϠ߿ళͻĂዋ
᛬҃Ϗ۰ѣດֽດк۞ᔌ๕ĄտјЯĂ֭ܧ̙ຐඕ
ĂΪߏۢࢰᙱడĂڱԱזዋЪ۞ҡܴĄ੫၆ѩன෪Ă
ބЅ̬ຽаᕩ็۞࠹Ꮠ͞ёĂ֭ͷࡎ็Ķಫˠķ
֎Ғ۞༺ҍĂ҃ు႙ᔙШĶҖຽགྷᒉķ۞ؠҜĄڇચ̰
टੵ˞೩ֻ̬̓ڇચγĂإΒ߁Ᏹந̓ᓑኖ߿જă
ّјܜኝăބᏙྙă͕நםኘඈڇચĄ
ބְᙯ࣎ˠ˘Ϡ۞ضĂਬְវ̂Ă̙Ξ̙ຕĄЯ ѩĂބಫ̬̝యˠĂᑕۧĶ͕͕ͧķăĶ̙̎ٙ୬Ă
̻߉ٺˠķ۞͕ၗĂన֗гࠎމ͗ຐĂ̬Ъዋ۞၆ ෪ֻމ͗ણ҂Ă̙҃ᑕ˘̷ͽĶຽચķଭޔĂۭᜪҖຽԛ ෪ٕڇચݡኳĂෛĶಫЪјΑதķ౼ٺĶڇચϫ۞ķĄּтĂ ѣ۞͕̓̚ĂΪߏΡ๒ົࣶĂќפົĂГᏱᏱᓑኖ߿
જܮϹम˞ְĂ҃ڱࣘᜪົࣶߏӎਕԱזৌϒЪዋ۞၆ ෪Ąҭѣ۞͕̓̚ଳϡĶଵࡗёķڇચĂӈ੫၆շ̃
ᗕ͞ፄઊ୧І۞ݵЪޘĂགྷಫ̬ˠࣶᄃމ͗எˢ఼֭ү Ԇፋ۞ͧྵޥ҂ޢĂГщଵշ̃ϒё֍ࢬĂѩүڱјΑ தྵĂ၆މ͗˵೩ֻྵщБ۞ܲᅪĄЯѩĂ̓ಫ̬۰
ٚፉމ͗۞ܫĂநᑕ੫၆ބᅮՐԱזৌϒዋЪ۞၆ ෪Ăͽܳј࡚႕ض۞ބቡĄߏ߇Ăдኜкބ੨၆୧І
̚ĂтңඕЪ֭үዋ༊҂ณĂಶјࠎ྿ѩϫᇾ۞̙˟
ڱܝĄ
ώࡁտࢵАଣϣ˾ຫεבᇴ̝পّᑕϡĂତଂ
͛ᚥ̚Ăᕩৼշ̃ᗕ͞ፄઊ̝γд୧ІĂ֭ྖణય
͕̓̚యˠΐͽОᙋĄГͽϣ˾ݡኳຫεבᇴүࠎ̍
âਠፄઊٙᙯ̷̝γд୧Іᖼೱјຫεͷΐͽณ
̼ĂޢГॲፂЧ୧І̝ᝋࢦΐᓁјಏ˘ෞณ̶ᇴ-ຫε ࣃĂ೩ֻ˘इፄઊෞҤᏴፄրĂഇਕ੫၆շ̃ᗕ͞ፄઊ ୧І۞ݵЪޘĂЕָˠᏴĂͽ༼࠷ಫЪॡมĂᆧΐ੨ ၆፟தĂ೩ڇચݡኳĄ
˟ă͛ᚥଣ
͛ᚥొ̶ࢵА੫၆ϣ˾ݡኳຫεבᇴ۞ؠཌྷ̈́ᑕϡ ଐԛү˘ଣĂѨГಶ̓୧Іኢ۞ϲኢૄᖂ̰̈́உ
ྎΐᛚĈ
1. ϣ˾ݡኳຫεבᇴ
็˯Ă̂ొ̶۞Ϡய۰ͽயݡณീࣃߏӎఢॾ
ࠧቢֽઇࠎᏊณயݡݡኳߏӎЪॾ۞ᇾĂ˲дఢॾࠧቢ
̝̰۰Ăౌෛࠎ˘ᇹ۞рĂдఢॾࠧቢ̝γ۰Ăౌෛࠎ˘
ᇹ۞ᗼĄࠎ˞႕֖ᜪމ۞ᅮՐĂឰயݡݡኳ̬ٺఢॾࠧቢ
̝̰ĂಶјࠎϠய۰Ӆ˧۞ࢦᕇĂ҃၆ٺఢॾࠧቢ̰யݡ ݡኳ̝मள̙֭҂ᇋĄҭಶְ၁҃֏Ăயݡݡኳপّດ ତܕϫᇾࣃĂّਕດрĂດઐᗓϫᇾࣃĂّਕດमĄ ߇ಶݡኳ۞გந҃֏Ăтѣ˘ྵр۞ࢍณ͞ڱֽೡ༊ய ݡপّઐᗓϫᇾࣃॡĂᜪމٙዎצז۞ຫεĂݡგड़ਕ
ՀჟĄ
Ϥ˯ΞۢĂ̙Ъఢॾ۞யݡົౄјຫεĂ
Ъఢॾ۞யݡ˵ΞਕົౄјຫεĂιᇆᜩயݡ۞થ
ዚณĂ߇၆ٺݡኳຫεྵр۞ೡ͞ڱᑕྍߏтң̚
ٕ၆ϫᇾࣃ[6]Ą
ϣ˾౾̀дݡኳ̝ؠཌྷ̚ΐˢܛ۞៍هĂֹݡኳຫ εјࠎݡኳԼච࿅̝̚В఼ᄬ֏Ąϣ˾౾̀၆ݡኳ۞࠻
ڱࠎĈĶݡኳܼயݡᇄޢٙගۤົ۞ຫεĄķݡኳຫ εߏݡኳপّϏਕЪϫᇾࣃٙౄј̝ϡྤ̝
[6]Ą
ϣ˾ݡኳຫεבᇴ۞៍هĂЯࠎΐˢۤົјώ۞៍
ᕇĂͷૻአᜪމጱШ۞៍هĂ่̙ݡኳณ̼Ă҃ͷ˵
Ъۤົགྷᑻ۞൴णሀёĂдጯఙ˯˵͟ৈצזጯ۰۞ࢦෛ
ᄃኢ҃జᇃھᑕϡĄтڒᚊ[7]ᑕϡдεड़፟טࠎ
ᇴ̶੨ॡ̝πӮࣃგטဦགྷᑻనࢍćࢉߋ[8]ᑕϡ д ε ड़ ፟ ט ࠎ ࢮ ͩ ̶ ੨ ॡ ̝ π Ӯ ࣃ გ ט ဦ གྷ ᑻ న ࢍ ć Quigley McNamara [9]ᑕϡдݡኳ̝ෞҤͽүࠎֻ
ᑕથᏴፄ۞ણ҂ćMargavio ඈ[10]ᑕϡдயݡݡኳԼซ ड़ৈ۞ෞҤĂͽՙؠߏӎᑕྍซҖѩีݡኳԼซ̝Ըྤć
ཀശآ[11]ᑕϡдָྤய੨ཉ̝ՙඉሀёĂͽԼච ԸྤЪćKethley ඈˠ[2]ᑕϡдٗгயЅ̬ຽ۞ڇચ
˯Ă೩ۏІᄃᜪމ̝ಫЪјΑ፟தĂͽ೩ᜪމ̝႕ຍ ޘĄLi[12]ᑕϡд Kano ݡኳሀё̝ଣĂͽ೩چᇄ થڇચݡኳĄ
2. ̓୧Іኢ
ᔵᄲ͌շଐᘃᓁߏ༓Ă͌̃ଐᘃᓁߏྐĂҭдன၁Ϡ
߿ዎĂ̙֭टٽჷזႝ৷ო۞ຑଐĄୖ̋ұᄃৡࡻ
έё۞৷৷̝ຑĂٙͽຏˠ۱ඩĂᔇˠሤஊĂࠎˠߺߺሄ
۰ĂϒЯࠎιޝං͌ĂΪ૱֍ٺᑚᆐ۞ᄅέ˯Ăݒցх ٺன၁۞Ϡ߿̚ĄೱήྖᄲĂĶд˘ਠܸ͵ଐቡ྆Ăᓁߏᙱ
௲ன၁۞ॾԊĄķĶӈֹߏѣබͪ࠹ె۞ൺᇶଐቡĂ˵Ϊᛳ Ϡ̚Ξຑம࡚۞̈೧ѡĂ̙ົតјன၁Ϡ߿۞ޠĄ
̝ޢĂаᕩזϒ૱۞ĂᚶᜈԷႊ˘࣎̚ఢ̚۞
͵ܸ֎ҒĄķ[13] ңͽтѩĉΞଂ˭Еೀ࣎ᆸࢬଣĈ (˘) ಶϔ̼͛҃֏
࣫Ӗላ[14]ᄮࠎ઼̝̚ބຑଐ៍ه̙ТٺҘ͞۰Ăӈ Ҙ̝͞շ͈̃ࢦຑ҃Ă઼̚Οˠࢦຑ҃ະĄຑ
҃Ăღ࠹ֶĂٽјռᇒ̝࠹ેĄຑ҃ѣະĂ
ຑ̝ဩࠧ˜ᐌ̝ฟ٤Ą߇͈̝ᙯܼ͇г̼ăछ
̼ăۤົ̼҃உᛷˠ၆ۤົцأ۞ຍᙊĄߏ߇Ăᖙฟ
઼̚ຑଐΫĂ̙ᙱ൴ன઼̚ˠ۞ຑଐĂϖᅈజᔑд Ķன၁ķغ˭Ăᓁߏྫྷࣖநᇇăᖃܸ௫ၚăछܝ ௐĂͽ̈́۞ۤົఢ˘னĂ҃ͷ۬ᜇ̙
ЃĄೱήྖᄲĂ઼̚ё۞ຑଐҁߏజΒᄤдބ۞ϫ
۞غ˭Ă҃ބ˫ᓁߏజࣖ૱ăछăۤົఢٙ
ᔑ[13]ĄٕᏜĂॡតዏ֝ిĂ็۞ፄઊ୧Іߏӎ̪
хдٺ̫͟ĂᅲࣃથၻĂҭϒт࢚ąयႬ౾̀
ٙᄲ۞ĈĶΟҁ۞ᆊࣃ៍ᄃၗޘĂ఼૱ͧࣇٙങॲ۞
ۤົඕၹѪՀၙĄҰᔵ߿д˟˩͵ࡔ۞னĂፄ ઊඉரΞਕ̪ᖞྫྷࣧؕয়؟˘ᇹĄķ[13]ĄϤѩΞۢĂ
็۞ፄઊඉரĂ̪၆ޢ͵̝ˠᇆᜩஎᅈĄ (˟) ಶބώኳ҃֏
кᇴ۞ބᙯܼĂౌᐌॡม۞ঐీ҃តҽ୶Ă૱
дĶࢴ̝קĂୢ̝Ξଓķ۞͕ဩ˭ĂͽࢂؼĄࠎ
˞ԼචѩଐԛĂഇਕބਕϖᜈ࡚႕Ă͕நጯछૺߋ Ꮈ[15]ޙᛉଂೀ࣎ࢦࢋᆸࢬ࠻ބĈ˘ࠎϠۏ۞៍ᕇů
ّ۞࠹ӛăّᅮՐ۞႕֖ăޢ۞ؼᜈĂߏၹј
ބ۞ࣧؕ୧ІĄੵѩ̝γĂՀچරזវᄻ۞ӛ͔Ă֗
វ۞ઉඈĄ˟ࠎགྷᑻጯ۞៍ᕇůѩӈ˘ਠˠٙᏜ۞
གྷᑻૄᖂĂߏֹބăछलܜ˳Ϡх۞ૄώ҂ณĂࠤ Ҍ؍̄ߏӎᅮಶຽፉछࢍඈĂ˵д҂ᇋ̝ЕĄˬࠎ
ۤົጯ۞៍ᕇůдބϠ߿̚Ă˵ᅮࢋۤົّ႕֖Ă ͽჯछल۞ۤົгҜă࣎ˠᗞࢬҋĄѩᆸࢬӈ
࿅Νۤົ̚ࢋՐ۞ܝ༊͗၆ĂனۤົٙᏜ۞छलࡦ
ഀăିֈޘăᖚຽќˢඈĄαࠎ͕நጯ۞៍ᕇůك ѩ࠹ຑΞਕߏЯԠ࠹Ըăၗޘ࠹ॆăّॾ࠹ܕٕ୧
І̢ྃĂͽ̈́͟˳ϠଐඈኜкЯ৵ౄјĂֱౌߏˠ
ˠ͕ந۞ତᛈࢬĂ˵ߏၹјބض̚ޝࢦࢋ۞˘
࣎ᆸࢬĄ̣ࠎࣰጯ۞៍ᕇůߏˠ۞ˠϠࣰጯ̷
ඕЪᄃჟৠ۞ݵЪĄ˯̝ۤົ៍གྷᑻ៍Ăߏᚶ
ّม۞ௐ˘࣎Ϡநତᛈࢬ̝ޢ۞࣎ۤົాࢬĂ
࣎ᆸࢬĂࢋߏצγдᒖဩᇆᜩĂᛳٺΑӀЯ৵Ą Яѩ៍̝Ăಶބώኳ҃֏Ăι೩ֻ˞ˠᙷϠۏăགྷ ᑻăۤົă͕நăჟৠ͞ࢬ۞ᅮՐĂ֭ѣΑӀड़ਕĄ ॡ˭ႝཌྷ۞Ϗշ̃Ăкૣإຑ۞͕நЯ৵Ă
҃ෛΑӀЯ৵ࠎܸĂซˢछलϠ߿Ăତᛈބ۞
Ķன၁ķࢬޢĂݒ૱Яᗕ͞ڱזۤົăགྷᑻඈ͞
ࢬ۞႕֖Ă҃ͅϫෘĂঅࠎጹĄ (ˬ) ބன၁୧І̰உ
ބߊߏѣ୧І۞ᏴፄĂ୧І̶ࠎγд̰д୧ІĄ γд୧ІĂ˫ΞჍࠎĶன၁୧ІķĄఄࡌᇊ[13]ͽࠎ၆ னշ̃҃֏ĂĶன၁ķ۞ࠧؠߏኑᗔ۞Ą̰टΞΒ ߁гҜăќˢăጯ።ăѐ᛬ă֗ăछ͵ඈĄ༊၆͞
ٯᛈ˞ۤົᇾγдෞᆊĂּтĈ၆͉͞ࡡă͉ሴă
͉ă͉༣ă͉ᔟăጯ።͉Ҳăѐ᛬̙၆ăќˢ͉Ҳ ඈĂߊֹᗕ͕͞ី˩̶ݵЪĂΞߏγдۤົၚٺ၆ˠ
ᕇᕇĂ̪ޝᙱԯ၆͞זҋ̎۞Ϡ߿ˠᅫ
྆ĄѦԏሁ[16]˘ีέ៉гડބአዋࡁտពϯĈ
͈؍ିֈޘ࠹ඈ۰Ăބض̶Ă҃јࠎ ѣӀٺބአዋ̝ځពЯ৵Ąᜪ༉Ӗ([17]ͽࠎշ̃ᗕ
͞۞ିֈޘăछलࡦഀ̙ਕ͉࿅ᚙঅĂͽҺكѩ៍
ه̙ਕ఼ĂЯѩጯ።मߏᇆᜩ៍ه఼۞ࢦࢋЯ
৵Ą͕நጯछเၷՅ[18]ͽࠎބ̙Ϊߏ࣎ˠ۞ְĂ
҃ߏ࣎छल۞ְĄٙͽĂᗕ͞۞छलࡦഀ˵ߏ̙Ξ نෛ۞୧ІĄۤົጯछೆᘃৌ[19]ͽࠎĶटٽၨ໑͈
؍எଐ۞Ă̙ߏᗕ͞நຐ۞ᅌᅈķĂ҃ߏன၁Ϡ߿۞ᑅ
˧Ą͈؍ࣧѣ۞छलᙯܼтڍ̙ਕррщଵĂಶົј ࠎՕࢦ۞Βෙक़Զ۞ֽĄڒ઼ࢶ[20]ᄮࠎ͈؍ᗓள
̙˘ؠߏˠ̝ม۞યᗟĂѣֱ̃Яᙱͽԡצछ
ሣ҃ှΞٸୢބĄтڍԓ୕ጾѣ˘࣎႕۞
ބĂд݈ಶ̙Ξنரஎˢ˞ྋ੨ઊ۞छलĄۤົጯ छჅऔ[21]ᄮࠎބ۞ј̶̚Ă၁ણૻধ۞Ķۤ
ົϹೱķຍקĄੵѩ̝γĂᜪ༉Ӗ[17]ͽࠎॲፂ઼ˠ۞
˘ีአߤඕڍĂ࠹̝ˠЯॡ۩ܡ̶͘۞Ăا̶͘
ࣧЯ۞ௐαҜĂҫ 10.8%Ăຑଐߏޝ၁ᅫ۞ຏᛇĂ૱૱
གྷ̙ॡ۩۞҂រĄЯࠎᅈͪା̙˞ܕͫĂ౦อـܔ ᓁᙱ੨Ъଐჰ˼ត༱̼۞ॡड़ّĄ
Ϥ˯ኢΞۢĂބ۞ன၁୧І̰உĂΒӣ၆͞
ѐ᛬ăќˢă֗ăវࢦă۰̍үᗓăጯ።৺
मளăछ͵ඈĄώኢ͛ӈͽѩඈкีγдЯ৵ࠎ
҂ᇋЯ̄Ăᑕϡϣ˾ݡኳຫεבᇴᖼೱјЧี
Я̝̄ຫεࣃĂ֭ΐ˯ᝋࢦޢຉᓁјࠎಏ˘̝ՙඉ តᇴĂޢΐͽଵԔĂͽүࠎЅ̬ຽ۰ಫЪշ̃
̝̓ણ҂Ą
100
60
20
LSL TARGET USL
TAGUCHI LOSS
100
60
20
LSL TARGET USL
TAGUCHI LOSS
ဦ 1 ၆Ⴭ୕ϫপّϣ˾ ဦ 2 ̙၆Ⴭ୕ϫপّϣ˾
ຫεבᇴ ຫεבᇴ
TARGET USL
100
60
20
TAGUCHI LOSS
TARGET 100
60
20
TAGUCHI LOSS
LSL
ဦ 3 ୕̈পّϣ˾ຫε ဦ 4 ୕̂পّϣ˾ຫε
בᇴ בᇴ
ˬăϣ˾۞ݡኳຍஉ
ᛂഈᆫ[6]Ĉϣ˾ϛ˘ٙ೩̝ݡኳ̍(quality engineering)۞நه͞ڱĂϫ۞ߏдயݡ၆ᑕ̝ᄦ
̰ޙϲݡኳĄϤٺݡኳ̍۞நهࠎݡኳԼච̝Ӆ˧
ϤϠயล߱Ш݈೩̿זనࢍล߱ĂЯ҃˘ਠჍࠎᗓቢ̝ݡ ኳგט͞ڱ(off-line quality control)Ăϣ˾̝ᗓቢݡგ͞ڱ̙
่Ξͽ೩چயݡݡኳĂ၆ٺࢫҲјώ˵ߏܧ૱ѣड़Ąдϣ
˾۞ݡኳຍஉ̈́ѣᙯ̝ԫఙ͞ڱ˯ౌߏͽݡኳຫε̝៍
هࠎ͕̚ĂֽᏊณயݡݡኳĄд็៍ه̚ĂᄮࠎΪࢋய ݡЪఢॾಶߏрயݡĂдఢॾٙटధ̝ቑಛ̰Ăεड़ јώயϠćТॡĂயݡ̙дఢॾቑಛ̰Ă̙ኢमளк͌Ă εड़ٙயϠ̝јώӮࠎ࠹ТĄְ҃၁֭ܧтѩĂϣ˾౾
̀ᄮࠎЇңயݡ̝ᄦౄĂপّࣃᑕᄃϫᇾࣃ˘ĂΪࢋ
ѣઐᗓĂӈົ၆ۤົౄјຫεĄ
ϣ˾̝ݡኳຫεᄃݡኳপّઐொϫᇾࣃ̝ณ۞π͞
јϒͧĂ҃ݡኳ̝পّΞ̶ࠎˬ[6]Ĉௐ˘ߏ୕ϫপّĂ ຍᏜݡኳপّ̝ീณࣃດତܕϫᇾࣃດрĂּтயݡ̝͎
̇ăࢦณćௐ˟ߏ୕̈পّĂຍᏜݡኳপّ̝ീณࣃດ
̈ດрĂּтຫਈăѳߖĂѩᙷপّࣃࠎܧࣃĂநຐࣃ ࠎćௐˬߏ୕̂পّĂຍᏜݡኳপّ̝ീณࣃດ̂ດ рĂּтૻޘăർޘĂѩᙷপّࣃࠎܧࣃĂநຐࣃࠎ
ࢨ̂Ą
୕ϫপّ̚ĂϫᇾࣃΞͽࠎயݡ˯˭ࠧࢨ̝͕̚ࣃĂ Ⴭࠎ၆Ⴭ୕ϫݡኳপّćϺΞࠎઐொ͕̚ᕇ̝ࣃĂჍࠎ̙
၆Ⴭ୕ϫݡኳপّĄ୕ϫݡኳপّᄃݡኳຫεבᇴ̝ᙯܼ
тဦ 1 ᄃဦ 2 ٙϯĂݡኳຫεבᇴؠཌྷт˭Ĉ
( ) (y k y m)2
L = − (1)
ܑ˘! ՙඉតᇴᄃटధቑಛ
ϫᇾࣃ Ξटధቑಛ टధࠧቢ ѐ᛬म -2 -2 ~ -8 -8
̍үᗓ 0 0 ~ 3 3 ጯ።म 0 0 ~ 2 2 ၆͞ќˢ 50000 0 ~ 20000 30000
֗ 165 0 ~ 10 155 វࢦ 55 0 ~ 10 45
ࣧϠछलˠᇴ 4 0 ~ 3 7
( )
( ) (y k y m) y m L
m y m y k y L
≤
−
=
≥
−
=
if ,
or if , ) (
2 2
2
1 (2)
̚ y ࠎݡኳপّࣃăL( )y ܑϯপّࠎ y ॡ۞ຫεࣃă m ࠎϫᇾࣃăk ٕ k1 ᄃ k2 ܑݡኳຫεܼᇴĄ୕̈পّ̈́୕
̂পّ̝ݡኳপّᄃຫεבᇴ۞ᙯܼтဦ 3 ᄃဦ 4 ٙϯĂ
ݡኳຫεבᇴؠཌྷт̳ё(3)̈́(4)ٙϯĈ
( ) ( )y k y2
L = (3)
( )y k/ y2
L = (4)
̚ y ăL( )y ᄃ k ̝ຍཌྷТ̳ё(1)ٙĄ
ϣ˾ຫεבᇴᔵҋٺᄦౄຽĂҭܕֽ̏జᑕϡдܧ ᄦౄຽ۞Җຽ̚Ăώኢ͛ᑕϡזބЅ̬۞ڇચ˯Ą
αăϣ˾ຫεבᇴд̓Ѕ̬̝ᑕϡ
ώᑕϡּ่ͽշّࠎ၆෪ү˘ᄲځĂనдބ۞ன ၁୧І̰உ̚Ă˭Е˛ีЯ৵ࠎЅ̬ಫЪјΑᄃӎ̝ࢦࢋ
ีϫĄдѐ᛬˯Ăշ͞நຐϫᇾࠎ̃ͧ͞շ̈͞໐Ăҭ
к̙ࢋ࿅ˣ໐ćд̍үᗓ˯Ăᗕ̙͞ࢋ࿅ˬ࣎̈
ॡ̝֘ĂநຐϫᇾࠎдТ˘ഏ̂ሁ̍үćጯ።˯Ă
ԓ୕рࠎТ˘৺ĂтТࠎ̂ጯٕТࠎჇ̀ጯҜĂ̂
म̙ࢋ࿅࣎৺ćќˢ͞ࢬĂշ͞ϫ݈ќˢՏ͡ࠎ 50000 ̮Ăԓ୕၆͞ќˢрਕᄃҋ̎࠹༊ĂҭΞତצ̝म
ࠎՏ͡ 20000 ̮ć֗͞ࢬĂշ͞ϫ݈ 168 ̶̳Ăԓ୕
̃͞நຐޘࠎ 165 ̶̳ĂҭΞତצ֗ቑಛࠎ 155 ̶̳
ͽ˯ćநຐវࢦࠎ 55 ̳͝ĂΞତצ̝វࢦቑಛࠎ 45~55 ̳
͝ć̃ࣧ͞Ϡछलˠᇴϫᇾࣃࠎ 4 ˠĂΞତצቑಛࠎ 4~7 ˠĂܑ˘ၡࢋ˯୧ІࢋՐĄ
˯Чี҂ᇋЯ৵གྷᖼ̼ࠎᄃϫᇾࣃ̝मޢĂᄃϫ ᇾࣃ̝मࠎດ̈ດрĂͽ̳ё(3)ՐЧϣ˾ຫεבᇴݡ ኳܼᇴ k Ă̶ҾࠎĈ27.78, 11.11, 25, 0.00000025, 1, 1 ̈́ 11.11ĄϤٺॡมඈЯ৵ĂಫЪˠࣶЕᓝ˞ 10 ࣎Ξਕّ̝̃
ˠᏴĂ֭Чี҂ᇋЯ৵ᄃϫᇾࣃमЕтܑ˟ٙ
ϯĄѩඈ҂ᇋЯ৵ᄃϫᇾࣃम̈́ݡኳܼᇴ k གྷϤ̳
ё(3)̝ϣ˾ຫεבᇴՐЧϣ˾ຫεࣃĂܑˬពϯ 10 ࣎Ξ ਕˠᏴ̝Чี҂ᇋЯ৵ຫεࣃ̝ࢍზඕڍĄѩॡӍˠΞͽ
ܑ˟! ۏІপّࣃ̈́࠹၆ࣃ
ѐ᛬म ̍үᗓ ጯ።৺म ၆͞ќˢ ֗ វࢦ ࣧϠछलˠᇴ በཱི னѣ
ۏІ
ᄃϫᇾ ࣃम
னѣ ۏІ
ᄃϫᇾ ࣃम
னѣ ۏІ
ᄃϫᇾ ࣃम
னѣ ۏІ
ᄃϫᇾ ࣃम
னѣ ۏІ
ᄃϫᇾ ࣃम
னѣ ۏІ
ᄃϫᇾ ࣃम
னѣ ۏІ
ᄃϫᇾ ࣃम
1 -4 2 2.1 2.1 1 1 36000 14000 160 5 48 7 7 3 2 -7 5 2 2 0 0 45000 5000 163 2 50 5 4 0 3 -8 6 1.1 1.1 1 1 40000 10000 165 0 46 9 5 1 4 -5 3 2.8 2.8 2 2 38000 12000 158 7 49 6 5 1 5 -5 3 0.9 0.9 0 0 48000 2000 155 10 53 2 6 2 6 -6 4 1.9 1.9 0 0 50000 0 159 6 45 10 4 0 7 -7 5 2.9 2.9 1 1 35000 15000 162 3 46 9 5 1 8 -4 2 0.8 0.8 1 1 45000 5000 160 5 45 10 5 1 9 -4 2 1.2 1.2 1 1 30000 20000 161 4 47 8 6 2 10 -5 3 1.8 1.8 2 2 32000 18000 164 1 46 9 4 0
ܑˬ! ЧۏІপّ̝ϣ˾ຫεࣃ
በཱི ѐ᛬म ̍үᗓ ጯ።৺म ၆͞ќˢ ֗ វࢦ ࣧϠछलˠᇴ 1 11.11 49.00 25.00 49.00 25.00 49.00 100.00 2 69.44 44.44 0.00 6.25 4.00 25.00 0.00 3 100.00 13.44 25.00 25.00 0.00 81.00 11.11 4 25.00 87.11 100.00 36.00 49.00 36.00 11.11 5 25.00 9.00 0.00 1.00 100.00 4.00 44.44 6 44.44 40.11 0.00 0.00 36.00 100.00 0.00 7 69.44 93.44 25.00 56.25 9.00 81.00 11.11 8 11.11 7.11 25.00 6.25 25.00 100.00 11.11 9 11.11 16.00 25.00 100.00 16.00 64.00 44.44 10 25.00 36.00 100.00 81.00 1.00 81.00 0.00
ܑα! ЧۏІপّΐᝋޢ̝ϣ˾ຫεࣃ በཱི ѐ᛬म
20%
̍үᗓ 10%
ጯ።৺म 5%
၆͞ќˢ 25%
֗ 20%
វ ࢦ 15%
ࣧϠछलˠᇴ
5% ϣ˾ຫεࣃ ᐹАଵԔ 1 2.22 4.90 1.25 12.25 5.00 7.35 5.00 37.97 5 2 13.89 4.44 0.00 1.56 0.80 3.75 0.00 24.45 1 3 20.00 1.34 1.25 6.25 0.00 12.15 0.56 41.55 6 4 5.00 8.71 5.00 9.00 9.80 5.40 0.56 43.47 7 5 5.00 0.90 0.00 0.25 20.00 0.60 2.22 28.97 3 6 8.89 4.01 0.00 0.00 7.20 15.00 0.00 35.10 4 7 13.89 9.34 1.25 14.06 1.80 12.15 0.56 53.05 10 8 2.22 0.71 1.25 1.56 5.00 15.00 0.56 26.30 2 9 2.22 1.60 1.25 25.00 3.20 9.60 2.22 45.09 8 10 5.00 3.60 5.00 20.25 0.20 12.15 0.00 46.20 9
ΐᓁЧี҂ᇋЯ৵̝ຫεࣃ҃ፋវᓁຫεĂޢᏴפຫ ε̈۰ࠎָˠᏴĄ҃âਠ҃֏Տˠ၆Чี҂ᇋЯ
৵̝ࢦࢋޘࢋՐ̙˘ĂѣֱˠྵࢦෛќˢćѣֱˠΞਕ
ྵࢦෛѐ᛬मĄЯ҃дүՙඉ̝݈ѣυࢋ၆࣎ˠдЧี
҂ᇋЯ৵˯ග̟̙Т̝ᝋࢦĂޢГ̟ͽΐᝋຉᓁĄΐᝋ ޢ̝ຫεͽ̳ё(5)ܑϯĈ
=∑
= n i WiCi
Loss
1
(5)
̚ Loss ࠎፋវຫεࣃĂW ࠎ҂ᇋЯ৵ i ̝ΐᝋࣃĂi C ࠎi
҂ᇋЯ৵ i ̝ϣ˾ຫεࣃĄనྍವడҡܴ̝շ̀၆Чี
҂ᇋЯ৵̝ᝋࢦࢋՐ̶Ҿࠎ 20%Ă10%Ă5%Ă25%Ă20%Ă 15%Ă5%Ă 10 ࣎Ξਕّ̝̃ˠᏴĂགྷΐᝋࢍზޢЧΞ ਕˠᏴ၆ྍշ̝̀ຫεΞ̶ҾՐĂ֭ዋЪଐڶͽᐹ АѨԔଵЕĂྎтܑαٙϯĄ
ૄώ˯ĂಫЪಏҜϺืֶೈ˯ઇڱĂֶፂّ̃̓
̝ࢋՐࢍზຫεࣃĂтڍྍշ̀˵дߙّ̝࣏̃̓Ᏼ Щಏ̚Ăࠎྵָ̝੨၆ĄགྷѩඈϹ˽̶ژޢГщଵᗕ͞
֍ࢬĂΞᆧΐಫЪјΑ̝፟தĄ
̣ăඕ! ኢ
дᚮۋ፬ধ۞னۤົĂᜪމ႕ຍޘڇચݡኳĂ ߏٙѣҖຽјୀ۞ࢦࢋЯ৵ĄMcDaniel Louargand [22]
ͽࠎڇચݡኳ۞ࢦᕇߏࢋ႕֖ٕ۰ঐ۰۞ഇޞĂҭ
̝มயϠ۞རमಶߏঐ۰۞ഇޞֻᑕ۰ٙ೩ֻ۞ڇ ચݡኳڱ˘Ăϣ˾ຫεבᇴ۞ᑕϡĂϒрΞԼචѩય ᗟĄᄏϣ˾ຫεבᇴਕϡᖎٽ̝ڱۏІ̶ඈĂ֭ۏІ পّมүр۞ͧྵĂણ੩މ͗۞ઐр̈́ᏴፄᇾĂͽם ӄމ͗డָᇾ۞֭೩މ͗۞႕ຍޘĄ
ன̫۞ބಫ̬۰Ăᑕםӄމ͗дൺ۞ॡม̰Աז Ъዋ۞၆෪Ąтѩ˘ֽĂಶމ͗҃֏ĂΞᆧΐགྷᑻ)ॡม*
ड़ৈĂడ։ቡćಫ̬۰ΞќזҮܛͷ౹ౄՀк۞થ፟Ă
֭၆ۤົ̝щؠேᚥ˘Њ͕˧Ą!
ϣ˾ݡኳຫεבᇴдބಫ̬˯۞ᑕϡĂপّࠎਕ
̙Т۞҂ᇋЯ৵Ăᖼೱࠎ˘ਠࢍณಏҜĂֹਕ࠹̢ͧ
ྵĂ̯֭ధމ͗ણᄃಫЪ࿅ĂͷΞᏴፄ̶੨҂ᇋЯ৵
۞ͧࢦĂֹᜪމдүᏴፄॡĂਕѣՀк̮۞҂ณĂ֭༼࠷
Ѕ̬ॡมĂᆧΐ੨၆፟ົĂͽഴ͌ሕдࢲᐍĄ
ϤٺՏ࣎ˠ၆̓Ᏼፄ̝҂ᇋЯ৵ٕѣ̙ТĂ҃ώࡁ տ่ಶ˘ਠ͛ᚥ̝ଣĂ֭Оᙋٺ࠹ᙯຽ۰ᕩৼೀᕇࢦ
ࢋีϫĂޢͽᇴࣃּΐͽᄲځĂ߇дᑕϡ˯ĂЧ҂ᇋЯ
৵ѣυࢋ੫၆࣎ˠᅮՐΐͽડă̶ژĄТॡд҂ณЧี
Я৵ᝋࢦॡĂώࡁտ่ͽމ͗ҋ̎៍Я৵೩ֻ̝ᝋࢦࣃ
ֽΐͽଣĂϏֽΞඕЪᆸ৺̶ژڱ(AHP)ٕሀቘநኢд ᄬຍតᇴ˯̝ᑕϡĂͽྵࠎމ៍̝͞ёؠЧี҂ᇋЯ৵
̝ᝋࣃĂүࠎޢᜈࡁտ̝͞ШĄ
ણ҂͛ᚥ
1. ዑߋϠĂݡኳგநĂˬϔ३ԊĂέΔĂௐ 617-618 ࢱ (1995)Ą
2. Kethley, R. B., Waller, B. D., and Festervand, T. A.,
“Improving Customer Service in the Real Estate Industry:
A Property Selection Model Using Taguchi Loss Functions,” Total Quality Management, Vol. 13, No. 6, pp.
739-748 (2002).
3. ౘϲ͈Ăα३రĂ͵ࠧ३ԊĂέΔĂௐ 784 ࢱ(1993)Ą 4. ͳำ̣በĂݑᘃርăष܄लොᛌĂٽ̫ො̫ᛌĂ
έ៉થચО३ᐡĂέΔĂௐ 458 ࢱ(1990)Ą
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