灰色田口法應用於蛋黃酥油酥皮生產最佳化研究

ങڷ፱ȃдסྛȈԸՓҤοݲᔖҢܻೖ༁໓ݶ໓Ҫҡ౰ശٹϽϞंـ 549

ԸՓҤοݲᔖҢܻೖ༁໓ݶ໓Ҫҡ౰ശٹϽϞंـ

ങڷ፱! дסྛ

୽ҳࡎݍऋ׬σᏰॵࠢऋᏰف

ᄢ! ौ

ҏंـᔖҢԸᜰᖒϷݙ๖ӫҤοПݲᄇᇧแཬૉȃοڨЅ؅ਟԙҏ้έ໶

Ҭ኿ࠢ፴੫ܒȂ൶ײΙശᎌҡ౰నӇȂᙤо໠ีೖ༁໓ݶ໓ҪՌଢ଼Ͻҡ౰ᇧ แȄᄂᡛ๖ݎᡗҰȂᇧแശᎌޟҡ౰నӇϷտ࣏Ȉଽճ๐ឨ઱Шٽ

1:1

^ȇឨҪ

፪ݶ఺ё໔

34

^{ʦȇᙽᎈಢଽ࡙}

5 mm

^{ȇँᑥ֤໔}

21%

^{ȇݶ໓፪ݶ఺ё໔}

43

^ʦȇ

జ௢ᐠజ௢ᙽᎈഀ

100

ᙽȇజ௢ᐠజᒯଚளᙽഀ

100

^{ᙽȇឨҪёЫ໔}

40

^ʦȇ

ݶҪѓݶ໓Шٽ

1.7:1

Ȅശᎌҡ౰నӇငᡛᜌᄂᡛᡗҰȂڏᐌᡝܒࠢ፴ᓺܻᄂ ᡛᄇྱಢȄ

ᜰᗤຠȈೖ༁໓ȃԸᜰᖒϷݙȃҤοПݲȄ

APPLICATION OF THE GREY-TAGUCHI METHOD TO OPTIMIZE THE MANUFACTURING PROCESS ON THE OIL DOUGHS OF EGG

SHORTENING CAKES

Ho-Hsien Chen! Chi-Yuan Wang

Department of Food Science

National Pingtung University of Science and Technology Pingtung, Taiwan 912, R.O.C.

Key Words:

egg shortening cake, Grey Relational Analysis, Taguchi method.

ABSTRACT

In order to develop an automatic manufacturing process for the oil doughs in egg shortening cakes, Grey Relational Analysis associated with the Taguchi method has been used to find a set of optimal processing pa- rameters from the rate of process waste, sensory evaluation and cost of materials. The results showed that optimal processing parameters were obtained as follows: (1)the ratio of 1:1 between strong flour and soft flour;

(2)34% lard added to dough; (3)the height of the third roller set at 5mm;

(4)21% sugar; (5)43% lard added to shortening cake; (6)100 rpm rolling speed of rollers; (7)100 rpm of conveyor speed; (8)40% water added to dough; (9)and the ratio of 1.7:1 between oil dough and oil shortening cake used for covering. The confirmation experiment also showed that the over- all quality of the products based on the optimal processing parameters was better than control test samples’ quality.

׬೚Ᏸѐ! ಑Ϊϲڢ! ಑Ѳ෈! ҕ୽ΞΪԑ

Journal of Technology, Vol. 16, No. 4, pp. 549-556 (2001)

550 ׬೚Ᏸѐ! ಑Ϊϲڢ! ಑Ѳ෈! ҕ୽ΞΪԑ

Ιȃࠉ! ِ

ӵ༈ಛޟೖ༁໓ᇧհႆแϛȂхཾޱശາΨޟ࢐ݶ໓ Ҫޟజ௢ȃѓᓥᇧհޟ໦ࢲȄଶΟငᡛΰ଩ӫϞѴȂоЙ ώᇧհݶ໓ҪϚծາਢາΨȂՄи౰໔Ԥ३ȄӰԪष૖஠

ݶ໓Ҫޟᇧհ؏᡽ҥՌଢ଼Ͻᐠడ෇фѓᓥȃᔆ۽ȃ௢ଔȃ

׷᠒ޟώհȂయฒᅸ୰ޟ஠џ࿽ࣺࣸ࿋ӻޟΡΨȃਢ໢Ѕ ቨё౰໔Ȅ༈ಛޟ୦ཾ଩Пѫ૖ၼҢӵЙώᐇհΰȂषौ

ၼҢӵᐠడᐇհΰȂ஠ོඪଽᇧࠢཬѶ౥ȄкौনӰ࢐Ӱ

࣏ݶ໓ҪϚӣনਟ଩Пོ౰ҡϚӣޟ۽৤ܒȂ࿋ငႆᐠడ ш༲ȃᔠᔆȃᔆ۽ȃ௢ଔȃᄧ᠒ޟႆแϛȂЎڏौ೽ႆ௢

ᎈȂ௢ଔ១ᆩȂ๖ݎџ૖ོ౰ҡકҪȃݶ໓ೝᔠю้౪ຫȂ ኇ៪ԙࠢޟቹԩ๖ᄺȄष׽ᡐ౰ࠢ଩ПȂо଩ӫᐠడҡ౰Ȃ ࠌܾᏲम੥ฎࡣޟ౰ࠢॳڨЅοཐЅনਟԙҏޟ౴ଢ଼ȂӰ Մ६ճ౰ࠢᝯތΨȄႆўंـෆо൐સҤοПݲᔖҢӵೖ

༁໓ᇧഅശᎌ௡ڙӰυಢӫ௤ଆ

[1]

Ȅծ࢐ӵࡣ៉ंـϛี

౪Ȃӵ౰ࠢޟࠢ፴೩ॎႆแϛȂٮߨ༉ՃኌᇧแཬѶ౥Ι

໶ȄЎڏӵॵࠢ౰ཾϛϚᘞଡؑଽࠢ፴ήȂཱི౰ࠢ໠ีϛ ଶΟौؑᇧแޟശٹϽѴȂᗙ҆໸ӣਢՃ໔ੑາޱοڨޟ

௥ڧܒЅёώԙҏȄӵ೻ٲՃ໔ϞϛȂѓ֤Οӻ१ޟࠢ፴ ੫ܒȂՄӵ೻ٲӻ१ࠢ፴੫ܒϞϛȂี౪ڏࣺᄇᔖޟ೩ॎ

୤ኵ܁܁܄ԪϞ໢࢐ࣺϣҭࣽȂฒݲΙमȂमٺഅԙ໠ี

ཱི౰ࠢਢȂശತёώనӇᒵᐅޟ֨ᜲȄ

ҏंـభ௤ଆ஠ݶ໓ҪҥЙώҡ౰׽࣏ᐠడҡ౰Ȃٮ ցҢԸՓҤοݲ൶ײюശᎌӫೖ༁໓ёώޟ౰ࠢনਟ଩П Ѕ೩രᐇհనӇಢӫȂӣਢঙ៫ڗ౰ࠢޟ௥ڧܒЅԙҏޟ Ճ໔Ȃо෈ႀڗᇧแശٹϽȄ

ΠȃМᝦӱ៫

ҤοԒࠢ፴ώแޟࠢ፴྅܈ڷࠢᆓώแϐೝϴᇯ࣏ଡ

ؑࠢ፴ᛧۡȃ׽๡ࠢ፴ڷ६ճԙҏޟПݲϞΙȂڏኄݿᔖ Ңӵώཾࣨᇧഅȃёώȃ໠ี้Ȃ֯Ԥுڗ࡞ԁޟຟቋȄ ծ࢐ԪݲᔖҢӵॵࠢёώП७ϚӻȂҬࠉᔖҢӵॵࠢऋ׬

ϞࣺᜰंـԤȈ֔

[2]

้ΡᔖҢܻМດ೺ᑥޟᇧഅȂ֖

[3]

้ΡᔖҢܻΙٲӄ໣ॵࠢࠢ፴ඪЀȂങ

[4]

้ΡᔖҢܻ᜼ᓞ

଩ПЅনਟϞኇ៪Ӱυ௤ଆȂങ

[5]

้ΡᔖҢܻц૩ጲ๵ڥ સϽंـȄ

ҤοПݲޟ੫ՓȂ࣏ڏցҢޢҺߒپᙏϽᐌএᄂᡛႆ

แȂҥཬѶڒኵۡဎоॎᆗᄂᡛ๖ݎڷӱᔖ঄Ϟ໢ޟ୑

৯Ȃ໌Ι؏װཬѶڒኵᙽᡐԙ

S/N

ШȞ

signal to noise ratio

ȇ

߬ဴᚕॱଉШȟȄ೽லӵ

S/N

ШശٹϽӱᔖޟႆแޟϷݙ

ॎᆗПݲԤѲএጒᛟȂϷտ࢐ఖω੫ܒȃఖσ੫ܒȃఖҬ ੫ܒᇄଢ଼ᄘ੫ܒȄӵॎᆗᄇؐΙএᄂᡛӱᔖ঄ޟႆแϛȂ

S/N

ШϚᆓႆแӱᔖޟጒ൜ԃդȂശσޟ

S/N

Ш൷࢐ശԁ ޟӱᔖ঄Ȃζ൷࢐ശ౩དЫྥޟᇧแӱᔖȄ

ณՄȂӵᄂᡛႆแϛڏӱᔖ঄ޟശᎌϽᒵᐅȂ೽லϚ

џ૖ѫԤ൐ΙޟӱᔖശᎌϽ٥ቄᙏ൐Ȃ܁܁ӵΙಢᄂᡛϞ ϛȂڎരΟӻᆍޟ੫ܒӱᔖȂӵ೻ٲᇧแӱᔖႆแϞϛȂ Өᆍޟᇧแޟ

S/N

Ш੫ܒ঄ޟӱᔖ܁܁Ϛ૖ΙमȂՄٺӻ १឴ܒޟᇧแӱᔖϛശٹϽޟ

S/N

ШᜲоຟեȄ

࣏ Ο ၌ ؚ ೻ এ ୰ ᚠ Ȃ ႆ ў ޟ ࣺ ᜰ ं ـ ൢ ֙ Ԥ Ȉ

Logothetis

้Ρ

[6]

оҤοПݲ၌ؚӻࠢ፴੫ܒᇧแϞശٹ

ϽПݲ ȂԪПݲ࡚ដӵܻᄂᡛࠉȂሯӑϷݙၥਟޟ੫ܒȂ Ӕ஠ၥਟᙽ඲ԙᚕଉᕼਝಛॎ໔Ȟ

noise performance sta- tistic

Ȃ

NPS

ȟڷҬ኿঄ᕼਝಛॎ໔Ȟ

target performance statistic

Ȃ

TPS

ȟȂശࡣҥጣܒଟᘪПԒȂײюശٹӰυಢӫȄ ࢹ้Ρ

[7]

ᔖҢӵјᏲᡝҡ౰ᇧแȂԪंـ࡚ដ஠ࠢ፴੫ܒ

኿ྥϽȂϷտؑюএտᚔ৯ҁПҁ֯ኵȂٮ๝Ϡᎌ࿋᠌१Ȃ ശࡣёᖂڏҁ֯ኵॎᆗᐌᡝ

S/N

ШȂՄؑுശٹӰυಢ ӫȄങ้Ρ

[8]

ඪюငᡛԒࠢ፴ཬѶڒኵܻӻ१ࠢ፴੫ܒശ ٹϽ୰ᚠȂڏПݲᇯ࣏ҤοԒޟΠԩཬѶڒኵҐ૖ߒႀю

ࠢ፴ޟઍғޟཬѶཎဎȂՄඪюငᡛཬѶڒኵȂоեॎࠢ

፴੫ܒޟཬѶȄд้Ρ

[9]

ᔖҢҤοПݲܻጣѴࠢ፴ӻ१ࠢ

፴੫ܒᇧแശٹϽंـȂԪПݲ࡚ដ஠࢚ԩᄂᡛࠢ፴ཬѶ

঄ଶоӒഋᄂᡛϛശσޟࠢ፴ཬѶ঄ޟПݲȂо኿ྥϽএ տࠢ፴੫ܒޟཬѶȂٮ๝Ϡᎌ࿋᠌१ȂёᖂӨ᜸ࠢ፴੫Ϟ

኿ྥ঄Ȃоؑுӻ१ࠢ፴੫ܒϞᖂཬѶ

;

Ӕᙤ኿ྥϽޟᖂཬ ѶȂॎᆗᐌᡝ

S/N

ШȂٮหӱᔖყȂоؚۡശٹӰυЫྥ

ಢӫȄࢠ้Ρ

[10]

࡚ҳӻ१ࠢ፴੫ܒϞ౰ࠢᛧ࡚೩ॎؚ๊

዁ԒȂԪПݲցҢ዁ጙ໱ӫ౩፣ޟ྅܈Ȃ஠

S/N

Шᙽ඲ԙ

዁ጙᗵ឴ڒኵȂٮҢӻϯଟᘪϷݙؑுӨࠢ፴੫ܒޟଟᘪ ԒȂցҢኵᏰೣგПݲюശᎌӰυЫྥಢӫȄ

ӵоΰޟࣺᜰंـȂငҥᄂᡛᡛᜌᡗҰȂڏࣱԤ੫੆

ޟᎌҢܒՃ໔ȄณՄᄇॵࠢ౰ࠢ໠ีȂҥܻཐۢࠢຟᄂᡛ ኵ঄ޟ዁ጙܒȂ܁܁ငҥӻ१೎౩ϞࡣོԤኵ঄Ѷઍޟ౪

ຫีҡȄ

Lin

้Ρ

[11,12]

ෆඪюցҢԸՓ౩፣ϛޟԸᜰᖒϷ

ݙȂ၌ؚҤοПݲϛӻ१឴ܒޟࠢ፴׽๡୰ᚠȂڏցҢԸ ᜰᖒϷݙپ၌ؚᄂᡛϛषϓӱᔖޟ዁ጙޟፒᚕᜰ߽Ȃٮആ

ႆᄂᡛޟӱᔖپுڗശᎌϽޟ๖ݎȄӰԪҏंـȂоॵࠢ

ೖ༁໓ݶ໓Ҫ࣏ٽȂٷᐃॵࠢёώ੫ܒޟሯؑȂଶΟᇧแ ཬૉᇄԙҏϞ໢ޟࣺᄇܒՃ໔ϞѴȂ؁ቨӖ౰ࠢཐۢࠢຟ

໶ҬȂоಒӫᄂሬॵཱིࠢ౰ࠢ໠ีᇄᇧഅёώȄ

έȃंـПݲ

ԸՓ౩፣Ȟ

Grey Theory

ȟ࢐ҥσച๼ϛ౩ώσᏰՌଢ଼

௡ڙف᎓ᆹᓸఀ௲ܻ

1982

ԑܚඪюȂΝ࢐ବᄇفಛ዁࠮ϛ ၥଉϚ݂ጂЅኵᐃϚׇᐌޟഋӋȂ໌՗Ԥᜰفಛҏ٘Ϟᜰ ᖒϷݙȃ዁࠮࢜ᄺ࡚ҳȂٮᙤҥڏႱกᇄᜰᖒᄇفಛୈ؁

໌Ι؏Ϟ௤ଆȄԸՓ౩፣кौବᄇٱސޟϚጂۡܒȃӻᡐ ໔ᒯΣȃᚔඹኵᐃЅኵᐃޟϚׇᐌܒୈശԤਝϞ೎౩ȄՄ ԸᜰᖒϷݙࠌ࢐ӵԸՓفಛϛȂϷݙفಛᚔඹוӖ໢Ȃࣺ

ᜰแ࡙σωޟก࡙ПݲȄҬޟӵ൶ؑΙᆍ૖ஊᒋ໔ӨᆍӰ શ໢ڏᜰᖒแ࡙Ϟσωޟ໔ϽПݲȂо߯ײюኇ៪فಛี

 !"#"$%&'()*+, 551

k9¶Æ]4´r·’¸A³HOÈl¹°/

0 h-Ȗ"¥í1º»8%¼XŸ'“‡g½

=¾[¿ÀOÁ±&/0%¼[13]

’™šw%ÚۖÚý‡/08žXŸ¬

­?@>j0 ¢€4¥ÉÊ

¦% ÂTÙ[žXŸ S/N %/0"wx VÙ [Úý‡±‚Ia«Çl S/N %Çl°‘Sý

‡±’" S/N %Úý‡±/0È0aQÆa«Çl /0Ã<¹Äþ

1.S/N Шॎᆗ

žŸÇl/0g8Ia«Çl$g S/N % Ù [ S/N %Ý{a«¼T†“6¬­S/N %­ä gþ

(³) 57Çl

1 db log 1

10 1 2









− 

=

∑

= n i yi

η n (1)

(g) 56Çl

db / log 10 1

2 



−

=

∑

= n

i yi n

η (2)

Åg S/N %Çl

y

ig"

n

g"ƒÊ

db

g S/N %/ÆœÇ ‡+è=HÇl È7Å&ÉÈ 7 S/N -ÈV*Çl.Êȼ[14,15]

2.ኵᐃࠉ೎౩

Ia«Çl
! S/N %Çl/0 r:³¦ÊŽË }{+hÌlT+h|Í/Î
ŽÏS@zÊ}

·Ð ÑÒ~2lÓÈÔl`lçÁÕlÃ1´í

@ ¢íɱʑç6ˆ%¼Ê‘&Sý‡ŠÊçý‡

± r!ʎú†@ >7#ý‡±ÁÕÊ$

W 1 Ö&×aØʎ8z$Wg 0 454¥Ù8 Ú 0~1 &S Ð$WʎUiÙG2OPõ³Š

l[16]rʎú†@êägþ

)]

( min[

)]

(

max[ ( ) min[ ( )]

)

(

⁽⁰⁾₍₀₎ ⁽⁰⁾₍₀₎

*

k x k

x

k x k k x

x

i i

i i i

−

= − (3)

r

x

i*(

k

)g‚$Wʎ x⁽_i⁰⁾(k)g‚m³

"¦Ê‘

i

Û1,...,

m

,

k

Û1,...,n

^max [ ]

^{xi( )0}

( )

^{k g‚m³}

"¦Ê‘7 .

^min [ ]

^{xi( )0}

( )

^k ‚m³"¦Ê‘

6

3.Ըᜰᖒ࡙Ϸݙ

Úý‡±/0 rígÜ°‘Sý‡

±
’™šùZ°‘¬íg"gÁÕ@A

 ®
°‘%¼ùZ°‘8"°‘SÌ5ý‡

±Ê}Ã9:<¹‚[17]þ

(³) Quʎú†@°‘

x

i(

k

), i =1,...,

m

,

k

=1,...,

n

'r

x

i(

k

) gʎú†@&ʎ

(g)­°‘!

n k m i k x k

x

i

i 0( ) ( ), 1,... , 1,...

0 = − = =

∆ (4)

r∆_0i^{g°‘!®ÝÈ} x0⁽k⁾g@AÞùZ°

‘&ß

k

 x₁(k)gm³"¦ÊŽ É‚ß

i

¦&

ß

k



(à) Ý{°‘&7!∆_maxT6!∆_min'∆_maxT∆_min /4í<¹‚þ

) ( ) 0( minmax

min= _{i k} x k −x_i k

∆ _{∀ ∀} (5)

) ( ) 0( maxmax

max= _{i k} x k −x_i k

∆ _{∀ ∀} (6)

(1) ¬íáâŠÊã&“S]-

(ä) ¸{Úý‡ŠÊ&þ

( )

n k m

i x k x k k

i i

,..., 1 , ,..., 1

) ) (

( ),

( 0 max

max 0 min

=

=

∆ +

∆

∆ +

= ∆

ζ γ ζ

(7)

rγ(x₀(k),x_i(k))gý‡ŠÊ ∆_maxg7! ∆_min g6! ∆_0i(k)gùZ8"&°‘!

(å) ¸Úý‡±þ

)) ( ), ( 1 ( ) ,

( 0 1 x0 k x k x n

x ⁿ _i

i k

∑

= =

Γ γ (8)

rΓ(x₀,x_i)gÚý‡± n g°‘¦Ê (æ) ;Γ ¹{Úý‡°_0i Γ₀₁≥Γ₀₂≥Γ₀₃≥...

rΓ 7&ý‡± Á¹°g₀₁ Γ ₀₂ Γ … 03

Ѳȃ೩രᇄ؅ਟ

’  " & e ] ¬ Þ ­ 2 < =   ? & RHEON- KN300-L  ?&ûç KL-301-èé&SVEBA DAHLEN AB DC-33-
0a êi(`•ëìí&

³ìí-&jî-ï&ðgÍÇï-ñ òó³ôõö÷0aj0<s 1 ‚

Ϥȃ๖ݎᇄଆ፣

’"g§¨ €4¥ `•ëìí%

Œ11$t`±ï$tø­

ùúøìB18%û£¤4¥ È0a

bfi’j0Ydüý±þ

552 ׬೚Ᏸѐ! ಑Ϊϲڢ! ಑Ѳ෈! ҕ୽ΞΪԑ

ყ 1! ೖ༁໓Ռଢ଼Ͻҡ౰ࢺแ

±«ӴॷŽ'ᢎΪ´a«Çl€ ®

Žú‚êä ÜÝ¢£¤4¥V*Éʦ%

"Ù[Ú۞ŸQÆa«Çl/0"

ù‚þ

1.௡ڙӰυȃޢҺߒޟᒵᐅ[15]

5"2û£¤4¥ :£¤4¥&BC <

³‚ r

e

gᇲ!4¥ IGӈ="BC


‡Ô[L₂₇(3¹³) 4¥$ညwx<g‚

"௴ᓍ?" rEdg:ƒ

300

ᗻàÆ

᙭&bò ‘…aö"´ù ‡g

24

ÇÂଋጛ&a öষ (û/Ÿaö଄/

2.Ҭ኿੫ܒޟ೩ۡᇄॎᆗ

ùZa«Çl­2bTêi

’à´
b­2Edj0ødg´


‡20aüý±þ±«ӴॷŽ' ᢎ|æ´Tj0’ 45ӓ2Ϊ´a«ÇlE dg
?@ aђE/Iyb

Ի/dgEdj0ødg:6-?7j0&

Ê
Çl#(‘…aö

9

/ŸaöXä ­ È0aüý±þ±«ӴॷŽ'ᢎ æ´Çl/0j0’­Xäg:

1000

êi

’V#bcÊ&bcÊL(y)=ky²'k

=

:

1000



êi’÷ᓀ'

y=

bcd&్؜b--

3.ӰυϷݙ

(

³

)S/N

%­

žŸÇl/0g8a«Çl$g

S/N

% Ù[

ߒΙ! ௡ڙӰυᇄЫྥ

B) £¤4¥ BC

1

BC

2

BC

3 A

`•ëìí%Œ

1:1 1.5:1 2:1

B

^1

% 32 34 36

C

$t¦`±

mm 3 5 7

D

ï

% 15 18 21

E

1

% 43 45 47

F

^$tø

RPM 80 90 100

G

­ùúø

RPM 80 90 100

H

ìB1

% 40 38 36

I

8%

1.5:1 1.7:1 2:1

e - - - -

ߒΠ! L27Ȟ3¹³ȟޢҺߒЅڏӰυ଩ည

£¤4¥¦4

A B C D E F e e G H I e e 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 2 2 2 2 2 2 2 2 3 1 1 1 1 3 3 3 3 3 3 3 3 3 4 1 2 2 2 1 1 1 2 2 2 3 3 3 5 1 2 2 2 2 2 2 3 3 3 1 1 1 6 1 2 2 2 3 3 3 1 1 1 2 2 2 7 1 3 3 3 1 1 1 3 3 3 2 2 2 8 1 3 3 3 2 2 2 1 1 1 3 3 3 9 1 3 3 3 3 3 3 2 2 2 1 1 1 10 2 1 2 3 1 2 3 1 2 3 1 2 3 11 2 1 2 3 2 3 1 2 1 2 2 3 1 12 2 1 2 3 3 1 1 3 2 1 3 2 1 13 2 2 3 1 1 2 3 2 3 1 3 1 2 14 2 2 3 1 2 3 1 3 1 2 1 2 3 15 2 2 3 1 3 1 2 1 2 3 2 3 1 16 2 3 1 2 1 2 3 3 1 2 2 3 1 17 2 3 1 2 2 3 1 1 2 3 3 1 2 18 2 3 1 2 3 1 2 2 3 1 1 2 3 19 3 1 3 2 1 3 2 1 3 2 1 3 2 20 3 1 3 2 2 1 3 2 1 3 2 1 3 21 3 1 3 2 3 2 1 3 2 1 3 2 1 22 3 2 1 3 1 3 2 2 1 3 3 2 1 23 3 2 1 3 2 1 3 3 2 1 1 3 2 24 3 2 1 3 3 2 1 1 3 2 2 1 3 25 3 3 2 1 1 3 2 3 2 1 2 1 3 26 3 3 2 1 2 1 3 1 3 2 3 2 1 27 3 3 2 1 3 2 1 2 1 3 1 3 2

S/N

%Ý{a«¼T†“6¬­’™š

S/N

^%

57ÇlgEdj0Ydüý±þ±

«ӴॷŽ'ᢎ 56Çlgj0’

"8a«/0wx<à‚ a«Çl&

S/N

^%<

1‚

(

^g

)

^Úý‡±/0

Úý‡±/0g"¦°È@A°‘%¼

,

^ʎ

ú†@é8

S/N

^%Çl†@

1

^ʂ

0

ୢS°‘ <

䝂.
r

1

B๿gÁÕ@A 45
5

 

f i

f i

ᡁ ܝ { ë ᡁ ܝ ౅ %

< =   ?

< = ਛ  ?

 

è Œ

վ ࠓ

 a

-./0123456789:;<=>?@ABC 553

D 300 EAFG!HIJKLM

 " w x

a«Çl¦4 êi’|/1000  j0ød/hr Ed ü  ý± þ± «
  Ž  '  1 2356 510 0.96 7.1 7.1 7.6 8.0 6.9 7.8 7.2 2 2353 519 0.98 6.4 6.2 6.5 6.9 5.8 6.9 5.8 3 2352 528 1.00 6.2 6.2 6.3 6.6 5.6 7.1 6.2 4 2354 519 0.97 6.2 6.3 6.2 6.7 6.2 7.5 6.6 5 2386 528 0.88 6.7 7.5 6.5 7.3 6.3 7.7 6.4 6 2352 510 1.00 6.4 7.4 6.9 8.0 7.0 7.9 7.1 7 2398 528 0.86 6.5 8.6 8.0 8.6 6.7 8.4 8.4 8 4475 510 0.05 6.4 7.3 7.8 7.9 6.4 7.8 7.8 9 2360 519 0.94 6.2 6.9 7.0 7.2 5.5 7.1 6.9 10 4173 519 0.12 6.8 8.1 8.5 7.9 6.9 7.9 8.7 11 2437 528 0.81 6.5 7.4 7.6 8.0 7.1 8.1 7.8 12 3711 519 0.24 6.4 7.9 8.2 7.9 6.3 7.7 7.9 13 2360 528 0.94 6.7 7.1 6.7 7.4 6.5 7.2 6.9 14 2828 510 0.55 6.6 8.0 7.8 8.2 6.5 7.2 7.8 15 3747 519 0.23 6.7 7.9 7.6 7.1 6.7 7.4 7.7 16 3315 510 0.36 6.3 7.0 7.2 7.6 6.3 7.5 7.4 17 2499 519 0.75 6.4 7.2 7.2 7.0 6.2 7.2 6.9 18 4657 528 0.01 6.8 6.7 7.2 7.4 6.3 7.8 7.1 19 4657 528 0.01 6.6 7.1 6.4 7.2 5.7 7.0 6.4 20 4173 510 0.12 6.7 7.3 7.5 8.0 6.1 7.3 7.3 21 2367 519 0.92 6.5 6.4 5.7 6.3 5.9 6.9 5.9 22 2807 510 0.56 6.9 7.3 7.0 7.4 6.4 7.6 7.0 23 2710 519 0.61 6.4 6.8 6.5 7.2 6.1 7.1 6.1 24 2353 528 0.98 6.1 6.8 6.3 7.1 5.7 7.2 6.6 25 2371 519 0.91 6.8 6.7 7.2 7.4 6.3 7.8 7.1 26 2499 528 0.75 6.6 7.1 6.4 7.2 5.7 7.0 6.4 27 3675 510 0.25 6.7 7.5 6.5 7.3 6.3 7.7 6.4

 NOHIPQA S/N R S/N %

a«Çl¦4 êi’|/1000 j0ød/hr Ed ü ý± þ± «
 Ž '

1 -67.44 54.15 -0.35 17.03 17.03 17.62 18.06 16.78 17.84 17.15 2 -67.43 54.30 -0.18 16.12 15.85 16.26 16.78 15.27 16.78 15.27 3 -67.43 54.45 0.00 15.85 15.85 15.99 16.39 14.96 17.03 15.85 4 -67.44 54.30 -0.26 15.85 15.99 15.85 16.52 15.85 17.50 16.39 5 -67.55 54.45 -1.11 16.52 17.50 16.26 17.27 15.99 17.73 16.12 6 -67.43 54.15 0.00 16.12 17.38 16.78 18.06 16.90 17.95 17.03 7 -67.60 54.45 -1.31 16.26 18.69 18.06 18.69 16.52 18.49 18.49 8 -73.02 54.15 -26.02 16.12 17.27 17.84 17.95 16.12 17.84 17.84 9 -67.46 54.30 -0.54 15.85 16.78 16.90 17.15 14.81 17.03 16.78 10 -72.41 54.30 -18.42 16.65 18.17 18.59 17.95 16.78 17.95 18.79 11 -67.74 54.45 -1.83 16.26 17.38 17.62 18.06 17.03 18.17 17.84 12 -71.39 54.30 -12.40 16.12 17.95 18.28 17.95 15.99 17.73 17.95 13 -67.46 54.45 -0.54 16.52 17.03 16.52 17.38 16.26 17.15 16.78 14 -69.03 54.15 -5.19 16.39 18.06 17.84 18.28 16.26 17.15 17.84 15 -71.47 54.30 -12.77 16.52 17.95 17.62 17.03 16.52 17.38 17.73 16 -70.41 54.15 -8.87 15.99 16.90 17.15 17.62 15.99 17.50 17.38 17 -67.96 54.30 -2.50 16.12 17.15 17.15 16.90 15.85 17.15 16.78 18 -73.36 54.45 -40.00 16.65 16.52 17.15 17.38 15.99 17.84 17.03 19 -73.36 54.45 -40.00 16.39 17.03 16.12 17.15 15.12 16.90 16.12 20 -72.41 54.15 -18.42 16.52 17.27 17.50 18.06 15.71 17.27 17.27 21 -67.48 54.30 -0.72 16.26 16.12 15.12 15.99 15.42 16.78 15.42 22 -68.96 54.15 -5.04 16.78 17.27 16.90 17.38 16.12 17.62 16.90 23 -68.66 54.30 -4.29 16.12 16.65 16.26 17.15 15.71 17.03 15.71 24 -67.43 54.45 -0.18 15.71 16.65 15.99 17.03 15.12 17.15 16.39 25 -67.50 54.30 -0.82 16.65 16.52 17.15 17.38 15.99 17.84 17.03 26 -67.96 54.45 -2.50 16.39 17.03 16.12 17.15 15.12 16.90 16.12 27 -71.31 54.15 -12.04 16.52 17.50 16.26 17.27 15.99 17.73 16.12

554
     

A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 E1 E2 E3 F1 F2 F3 G1 G2 G3H1 H2 H3 I1 I2 I3 T

0.50 0.52 0.54 0.56 0.58 0.60 0.62 0.64 0.66 0.68

=0.62

 2 =>STUV:

W NOHIPQAXYZ[\

Ê Ž ú † @

a« Çl

¦4 êi’

j0ød

/hr

 E d

ü



 ý

±

 þ

±

«





Ž



؆ ᨠ 1 1.00 0.00 0.99 1.00 0.42 0.70 0.77 0.89 0.62 0.53 2 1.00 0.50 1.00 0.31 0.00 0.32 0.29 0.21 0.00 0.00 3 1.00 1.00 1.00 0.11 0.00 0.24 0.15 0.07 0.15 0.16 4 1.00 0.50 0.99 0.11 0.05 0.20 0.20 0.47 0.42 0.32 5 0.98 1.00 0.97 0.61 0.58 0.32 0.47 0.53 0.56 0.24 6 1.00 0.00 1.00 0.31 0.54 0.46 0.77 0.94 0.68 0.50 7 0.97 1.00 0.97 0.42 1.00 0.82 1.00 0.77 1.00 0.91 8 0.06 0.00 0.35 0.31 0.50 0.76 0.73 0.59 0.62 0.73 9 1.00 0.50 0.99 0.11 0.33 0.50 0.43 0.00 0.15 0.43 10 0.16 0.50 0.54 0.71 0.82 1.00 0.73 0.89 0.68 1.00 11 0.95 1.00 0.95 0.42 0.54 0.70 0.77 1.00 0.81 0.73 12 0.33 0.50 0.69 0.31 0.74 0.89 0.73 0.53 0.56 0.76 13 1.00 1.00 0.99 0.61 0.42 0.39 0.51 0.65 0.22 0.43 14 0.73 0.00 0.87 0.52 0.78 0.76 0.85 0.65 0.22 0.73 15 0.32 0.50 0.68 0.61 0.74 0.70 0.39 0.77 0.35 0.70 16 0.50 0.00 0.78 0.21 0.37 0.57 0.60 0.53 0.42 0.60 17 0.91 0.50 0.94 0.31 0.46 0.57 0.34 0.47 0.22 0.43 18 0.00 1.00 0.00 0.71 0.24 0.57 0.51 0.53 0.62 0.50 19 0.00 1.00 0.00 0.52 0.42 0.28 0.43 0.14 0.07 0.24 20 0.16 0.00 0.54 0.61 0.50 0.67 0.77 0.41 0.29 0.57 21 0.99 0.50 0.98 0.42 0.10 0.00 0.00 0.27 0.00 0.04 22 0.74 0.00 0.87 0.81 0.50 0.50 0.51 0.59 0.49 0.46 23 0.79 0.50 0.89 0.31 0.28 0.32 0.43 0.41 0.15 0.13 24 1.00 1.00 1.00 0.00 0.28 0.24 0.39 0.14 0.22 0.32 25 0.99 0.50 0.98 0.71 0.24 0.57 0.51 0.53 0.62 0.50 26 0.91 1.00 0.94 0.52 0.42 0.28 0.43 0.14 0.07 0.24 27 0.35 0.00 0.70 0.61 0.58 0.32 0.47 0.53 0.56 0.24

Úý‡/0 8 1 ¬íg@A, @A°‘ƒg 1

Ve’
’™š8êi’j0ødTE d8üý±þ±«
ŽT'!

gO|Æ] rVe/4Ig 1/6 T 1/14 r<å

‚
å"¦Úý‡±ÁÕ@A°‘g ß 7 ¦ ý‡±g 0.89 r"I¦È@A°‘OÕ±

°g 11 ¦>13 ¦>5 ¦>1 ¦>24 ¦>3 ¦Û6 ¦>25 ¦=26 ¦

>4 ¦=9 ¦Û10 ¦>2 ¦>14 ¦=17 ¦>21 ¦>22 ¦>12 ¦>23

 =>!\]^_AST`X!5STU

¦>15 ¦>18 ¦>16 ¦>19 ¦>27 ¦>8 ¦Û20 ¦

4.

(³)¢4¥¦%

8åý‡±  T s <æs 2

ý ‡ ±

a« Çl êi

’

j0ød

/hr

 E d

ü



 ý

±

 þ

±

«





Ž



؆ ᨠ

Ú ý

¹

V 1 1 1 1 1 1 1 1 1 1 e 6 6 6 14 14 14 14 14 14 14 ‡

@A°‘ 1 1 1 1 1 1 1 1 1 1 ± ° 1 0.995 0.33 0.97 1.00 0.46 0.63 0.68 0.82 0.57 0.52 0.72 5 2 0.999 0.50 0.99 0.42 0.33 0.42 0.41 0.39 0.33 0.33 0.61 10 3 1.000 1.00 1.00 0.36 0.33 0.40 0.37 0.35 0.37 0.37 0.68 7 4 0.998 0.50 0.98 0.36 0.34 0.39 0.38 0.48 0.46 0.42 0.62 9 5 0.960 1.00 0.92 0.56 0.54 0.42 0.49 0.52 0.53 0.40 0.73 4 6 1.000 0.33 1.00 0.42 0.52 0.48 0.68 0.90 0.61 0.50 0.68 7 7 0.947 1.00 0.91 0.46 1.00 0.74 1.00 0.69 1.00 0.85 0.89 1 8 0.347 0.33 0.33 0.42 0.50 0.68 0.65 0.55 0.57 0.65 0.47 20 9 0.991 0.50 0.96 0.36 0.43 0.50 0.47 0.33 0.37 0.47 0.62 9 10 0.373 0.50 0.41 0.63 0.73 1.00 0.65 0.82 0.61 1.00 0.62 9 11 0.906 1.00 0.88 0.46 0.52 0.63 0.68 1.00 0.73 0.65 0.80 2 12 0.428 0.50 0.51 0.42 0.66 0.81 0.65 0.52 0.53 0.68 0.56 14 13 0.991 1.00 0.96 0.56 0.46 0.45 0.51 0.59 0.39 0.47 0.74 3 14 0.650 0.33 0.71 0.51 0.69 0.68 0.77 0.59 0.39 0.65 0.60 11 15 0.423 0.50 0.50 0.56 0.66 0.63 0.45 0.69 0.44 0.62 0.54 16 16 0.499 0.33 0.59 0.39 0.44 0.54 0.56 0.52 0.46 0.56 0.50 17 17 0.849 0.50 0.84 0.42 0.48 0.54 0.43 0.48 0.39 0.47 0.60 11 18 0.333 1.00 0.25 0.63 0.40 0.54 0.51 0.52 0.57 0.50 0.54 16 19 0.333 1.00 0.25 0.51 0.46 0.41 0.47 0.37 0.35 0.40 0.49 18 20 0.373 0.33 0.41 0.56 0.50 0.60 0.68 0.46 0.41 0.54 0.47 20 21 0.982 0.50 0.95 0.46 0.36 0.33 0.33 0.41 0.33 0.34 0.59 12 22 0.659 0.33 0.72 0.73 0.50 0.50 0.51 0.55 0.50 0.48 0.57 13 23 0.707 0.50 0.75 0.42 0.41 0.42 0.47 0.46 0.37 0.36 0.55 15 24 0.999 1.00 0.99 0.33 0.41 0.40 0.45 0.37 0.39 0.42 0.70 6 25 0.977 0.50 0.94 0.63 0.40 0.54 0.51 0.52 0.57 0.50 0.67 8 26 0.849 1.00 0.84 0.51 0.46 0.41 0.47 0.37 0.35 0.40 0.67 8 27 0.433 0.33 0.52 0.56 0.54 0.42 0.49 0.52 0.53 0.40 0.48 19

-./0123456789:;<=>?@ABC 555

a =>STUV:

Ú ý ±    

A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 0.67 0.61 0.58 0.62 0.64 0.60 0.61 0.65 0.60 0.63 0.58 0.64

E1 E2 E3 F1 F2 F3 G1 G2 G3 H1 H2 H3 0.65 0.61 0.60 0.62 0.60 0.63 0.56 0.60 0.69 0.64 0.60 0.62

I1 I2 I3

0.59 0.65 0.61 T =0.62

b => ANOVA ANOVA

†# SS <;± MS F P- $ñ

A 0.039 2 0.020 1.93 0.17 3.4 B 0.005 2 0.002 0.21 0.81 3.4 C 0.011 2 0.006 0.51 0.61 3.4 D 0.021 2 0.010 0.95 0.40 3.4 E 0.011 2 0.006 0.49 0.62 3.4 F 0.004 2 0.002 0.18 0.84 3.4 G 0.082 2 0.041 4.96 0.02 3.4 H 0.008 2 0.004 0.37 0.69 3.4 I 0.015 2 0.008 0.69 0.51 3.4

 =>AGcFG

£¤4¥  " w x

¦4 A B C D E F G H I

êi’ j0ø± Ed ü ý± þ± «
 Ž ' `l Á±

ß%¦ 1 1 1 1 1 1 1 1 1 2356 510 0.96 7.1 7.1 7.6 8.0 6.9 7.8 7.2 7.4

¼BC¦ 1 2 2 3 1 3 3 1 2 2352 528 0.99 7.5 6.7 8.4 8.7 8.4 8.6 8.4 8.3

 =>GcFG S/N RARd

S/N % a«Çl

¦4 êi’ j0ø± Ed ü ý± þ± «
 Ž '

ß 1 ¦ -67.44 54.15 -0.35 17.03 17.03 17.62 18.06 16.78 17.84 17.15

¼BC¦ -67.42 54.45 -0.09 17.5 16.52 18.49 18.79 18.49 18.69 18.49 S/N %! -0.02 -0.3 -0.26 -0.47 0.51 -0.87 -0.73 -1.71 -0.85 -1.34

‚ý‡±&7 Ba«&õ 0aa«&ÁÕ@

A 45LÝ{ A1B2C2D3E1F3G3H1I2 Úý‡± 

 Ég¢4¥¦%

(g)Úý‡±

†“Ê/0&analysis of variance; ANOVA-Úý‡±

†“Ê/0ù
(­XŸ
QÆa«Çl'

%löK& Ý{È–G2±4¥ r wx<(‚r4¥g G&­ùú$ø-;

(I¦ F T P-L) 4¥ G  F  4.96 7

0.05 BC$ñ 3.40 (*í4¥ G 4¥rÈ

QÆa«Çl2€+


5.

 27 ¦" ß³¦"4¥gf,ɱ4

¥
"€" ß 1 ¦ g¢4¥¦%ÈÈ~

<û‚;L) a«Çl S/N %…î1gþê i’UV 0.02db j0ødUV 0.30db EdUV 0.26db üUV 0.47db ý±-. 0.51db þ±

UV 0.87db «
UV 0.73db UV 1.71db

ŽUV 0.85db 'UV 1.34db

;µa‘…aö"Ê gR‘…Áȵ

¬ªOÈl%¼ö/ qr
Oh0a& Å2`

±wxl 45%¼×[¢íÊ¡}Ì5!

×+

’"‘…aöo¤ /Dý±2¹”

0¶ ,
r"´ù_0¶Ù%ý±` Ð ó0a+Âáý±€ Ö.Ð`lÁÂ

±óá _&<û‚-
êi’Xø:j0 1000

LMNêi 4 |j0ød:6-UV 3.5%

01T0aEd_ 3% ;5Ló)0aa«

1ó…î

ϲȃ๖! ፣

;µa0a…î!.lS]h-±1ᐏT

g]´ ./ËËÌ523’"<xœ

A_401TEd ôœ
YS88

%_4 3:1 0aEdL(ãá 100% j0ø±

?L_48Õ 50% D.А75¹”W678 µaj0®+9³Æ]±1 #·¸?ô Æ]

’™š Ù[Ú۞Ÿ(³:>Xä…îµa

 LÁ;bdTêi’ Ý{¢

556 ׬೚Ᏸѐ! ಑Ϊϲڢ! ಑Ѳ෈! ҕ୽ΞΪԑ

fi$XTj0ÒÓ'Ðó?T? Lz[

BR* T* (MN71-STR

’™š!"€"‚ 0a`la«¢1ó… î 45Ú۞ŸL;ïáñ gµa…î 8º0a»ªXŸÉ±



1.

ç<=>?@AçlB# C [ža«*

…"&™šD ðEF>}8µ aû} ß

38

^{G ß}

3

^{â ß}

214-222

^H&

2000

^-

2.

nI
´JKLçMNO Cžäa«*

µaV*# [

-

¡D PB0J Q ß

493

^{â ß}

29-40

^H&

1994

^-

3.

RSTTUVWçXYZ C"­


µaa«_™š8 [D

NSC85-2121-M006- 023

85

œ±Pû^[N™š­rxOP ð\

&

1996

^-

4.

]^_`abcdçef C€ìíx>Ç l&Æ]4´/0®§¨r8aS&ýŠD

NSC85-

2121-M006-022

85

œ±Pû^[N™š­rxO

P ð\&

1996

^-

5.

ghijklmnçop Cf&

8>™šD ™

84-0942

µa*™šOP º o ðE&

1995

^-

6. Logothetis, N., and Haigh, A., “Characterizing and Opti- mizing Multi-Response Process by the Taguchi Method,”

Quality and Reliabitity Engineering International , Vol. 4, No. 2, pp.159-169 (1988).

7.

^mq CQ€ a[_‰`j0¡&a«è¤D Pus7}**™šrsz ºo ðE

&

1990

^-

8.

tu C!"äbcÊQHa«Çl¼>KN

& [™šD Pus7}**™šrsz

 ºo ðE&

1993

^-

9.

lvç CžXŸ['aèQÆa«Çl¼

>& [™šD Pus7}*™šrsz

ºo ðE&

1993

^-

10.

twx CQÆa«Çl&0aìQ¬­MvwäD Pu7}*è@™š´sz ðy ðE

&

1995

^-

11. Lin, J. L., Wang, K. S. and Yan, B. H., “A Study of Grey- Based and Fuzzy-Based Taguchi Methods for Optimizing the Multi-Response Process,” The Journal of Grey System , Vol. 11, No. 3, pp.257-277 (1999).

12.

z{™|}~çM€ C [Úý‡/0‚V

*ÉÊ¢>&™šD

1998

^œÚۖ@z8 

[™¨^ ƒ> ß

159-164

^H&

1998

^-

13.

„…—˜™çX†‡ ÚÛ/0®ˆ `us‰2 3êŠ ð\&

1996

^-

14.

‹Œ žäa«*åz •ŽPa«è¤

^ ð\õ&

1992

^-

15. Peace, P. G., Taguchi Methods , Addison-Wesley, New York (1993).

16.

‘<
„… Úý‡/0&[lʎú†@§¨

1998

œÚۖ@z8 [™¨^ `… ß

47-53

^H

&

1998

^-

17.

ç<=>çi’Ž C [Úý‡/0“”e

¤/0•"–a«&™šD Úۖ}Q ßàG ß³â ß

25-35

^H&

2000

^-

89 œ 11 J 20 — ˜™

89 œ 12 J 30 — š›

90 œ 02 J 23 — ‰›

90 œ 04 J 28 — ÁÂ