旋壓成型可靠度分析之研究

ᅩࣱໞࠣרㄅಙӠኔʠᶇἄ

ᓐڶᢏ¹ʳ ຫةᏺ¹ ᓐ৬ີ²

1ᐚᙤݾ๬ᖂೃ ᖲඳߓ

2ᒮᚐٞᄐڶૻֆ׹

ၪ ⣬

ᑇ൳ඝᚘګݮݾ๬ך։ܓشԱᑇ൳ףՠխ֨ऱᐘࢤΔኙሿٙऱ່ึݮणΕ ګݮ૩ᇾΕඝᚘ᠏ຒΕዞᔚၞ࿯ຒ৫࿛೶ᑇၞ۩ٚრᓳᖞΔױאඝᚘנٺጟլ ٵݮणऱሿٙΔࠠڶףՠய෷೏Ε໎೯Ꮑޣ܅Εྤႊၞ۩֊চףՠ࿛௽រΙڇ ඝᚘመ࿓ΔլٵऱޗᔆࡉݮणΔᏁ๻ࡳլٵऱףՠ೶ᑇΔૉ೶ᑇ๻ࡳլᅝΔ࣐

ທګףՠ؈ඓΰధါα෼ွΖ੡ޏ࿳ඝᚘګী঴ᔆլ᡹෼ွΔء֮ආشضՑֱ

ऄհ঴ᔆՠ࿓๵ቤऄΔ։࣫լٵՠ࿓ڂ՗ኙؾᑑ঴ᔆհᐙ᥼Δլٵඝᚘګݮ፹

࿓೶ᑇऱᔞشᒤ໮Δބנ፹࿓່ࠋ֏հףՠ೶ᑇΔא྇֟։࣫ࢬᏁհᇢᑓழၴ

֗ګء௡၄Ζۖ੡༼೏ข঴ױᔾ৫Ε૾܅፹ທլߜ෷Δء֮։࣫լٵদ৫௽ࢤ ڇඝᚘףՠழױᔾ৫ಯ֏ൣउΙ൶ಘ፹࿓೶ᑇኙլٵদ৫֗࿏৫ףՠᐙ᥼Δ ಾ ኙլٵদ৫ࣨޗ൶ಘլٵ᧢ݮֺඝᚘ؈ய଺ڂΔಖᙕ؈யழၴ֗ඝᚘ୲๺ᒤ

໮Δܓشױᔾ৫։࣫հഗء෻ᓵ֗೶ᑇ۷ૠհֱऄΔޣנ؈ய։܉հ೶ᑇଖΔ ٦א K-S ᔞٽ৫ᛀࡳհֱऄΔܒឰข঴່ᔞհ؈ய։܉Δ៶א൓वඝᚘመ࿓խ լٵ᧢ݮֺհױᔾ৫᧢֏Δא੡፹࿓೶ᑇᓳᖞ֗ඝᚘଅᙠေ۷հࠉᖕΖ

〦⼫⥱Řױᔾ৫ΕඝᚘګীΕضՑֱऄΕ፹࿓೶ᑇΖ

A STUDY OF RELIABILITY ANALYSIS FOR METAL SPIN-FORMING

Yuo-Tern Tsai¹ Yeong-Jern Chen¹ Jian-Zhang Tsai²

1Department of Mechanical Engineering De-Lin Institute of Technology

Taipei, Taiwan, 236, R.O.C.

2Wei-Li Limited Company Taipei, Taiwan 22157, R.O.C.

Key Words : reliability, spin forming, taguchi method and manufacturing parameters.

ABSTRACT

The NC spin-forming machine center possesses excellent manufactur- ing properties such as high mechanical efficiency and low manpower need.

It can quickly form the final shapes of parts and doesn’t need more work to cut the material for the formed parts by adjusting the parameters of shaped trajectory, spinning speed and feeding rate, etc. Different processing parameters are usually needed for different materials and shapes. If the

parameters set improperly, spinning failure would be incurred including break-splitting and wrinkling. In order to avoid spinning failure and obtain good quality, this paper investigates the influence of manufacturing parameters on spinning by using the Taguchi method. The purpose is to find out the optimal manufacturing parameters so as to shorten the time needed for trial and to find out the optimal manufacturing parameters.

Moreover, spin-forming reliability of stainless plate on different thicknesses and lengths was also studied to evaluate the successful probability of products on spin-forming. The storage tank of a plastic shot machine is chosen as the researched object. The manufacturing parameters were set according to the results obtained in the Taguchi analysis. The allowed spun lengths of the storage tank in different thicknesses were collected to evaluate spinning reliability in cooperation with K-S identification. The purpose is to find out the relationship between the allowed spinning deformation and the thicknesses of stainless plate. The studied results can be used as a basis in manufacturing parameter adjustment and risk assessment of spin-forming.

ɺȮℨ ⧄

ඝᚘګݮ (Spinning forming) ݾ๬ਢԫጟࠠڶسขၜ ཚ࿍Εݾ๬૞ޣ೏ऱګݮֱऄΔ౨ڇཏຏᖲݩՂش១໢ऱ ᑓࠠ፹ທݮणᓤᠧऱሿٙΔ౨ᔞٽՊᙓΕᔱΕᎭ࿛լٵऱ ८᥆ޗறΔᆏપ଺ޗறࡉՠࠠ၄شΔᜍ࿍ԱףՠழၴΔኙ

࣍ၦ֟Ε؆ী᧢֏Օࢨࢼᚲ (drawing) ྤऄݙګհ८᥆ࣨ

፹঴Δ௽ܑᔞش࣍ඝᚘףՠΖඝᚘڇཏຏᖲݩՂၞ۩ழᏁ

૞፹ທറ॰ऱᔾᑓᖲዌࠐኔ෼ࠡሎ೯૩ᇾΔᅝข঴Ꮑ૞ᆖ

ൄޓᄅངזழΔൄڂլ౨߰ຒᓳᖞሎ೯૩ᇾࢨ፹࿓೶ᑇ൳

ࠫլᅝΔທګඝᚘழՠٙధါࢨ঴ᔆլߜ࿛ംᠲΙڼழΔ ܓشᑇ൳ඝᚘڇ፹࿓೶ᑇ֗ሎ೯૩ᇾ൳ࠫऱᚌ။௽ࢤΔല ױڶயᇞެႚอඝᚘףՠࢬ૿ᜯऱംᠲΔၞۖ྇֟ඝᚘլ ߜ෷ऱขسΕ༼ࣙข঴঴ᔆΕ૾܅سขګء[1]Ζ

ᑇ൳ඝᚘګݮਢܓشᑇ൳߫চխ֨ࠐኔ෼ඝᚘࢬᏁऱ ٺጟሎ೯૩ᇾΔࠀܓشࠡ૩ᇾ᧢֏ࠐᚌ֏ሿٙᔆၦΔٵழ ዞᚘऱᔾᑓՈױऴ൷ڇᑇ൳ᖲݩՂףՠΔ֠ࠡᔞٽՊᆖൄ

ޓᄅངזऱข঴ࢨՕޅၦسขऱඝᚘګݮףՠΖᇠګݮݾ

๬ך։ܓشԱᑇ൳ඝᚘऱᔞᚨࢤΔኙሿٙऱ່ึݮणΕګ ݮऱ૩ᇾΕඝᚘऱ᠏ຒΕዞᔚऱၞ࿯ຒ৫࿛೶ᑇၞ۩ᓳᖞΔ ࠐൎ֏ሿٙᔆၦΔᛧ൓່ࠋऱඝᚘ঴ᔆΖඝᚘᔾᑓڜᇘڇ ᖲݩ׌ၗՂΔױش S40C ᓳᔆ๠෻Δዞᔚᙰऱዞᔚຏൄش

SCr415 ࢨՠࠠᙓ፹ທΔࠡ।૿ᆖ෧־๠෻Δ؆।ၞ۩ࢹ

٠Ζඝᚘழዞᔚፖᜳࣨհၴ੡ొዞ೯Δࠡ।૿ษᜋ৫ፖඝ ᚘ৵ऱ।૿ᔆၦയ֊ઌᣂΔ੡྇֟ᐰᚴ (ط࣍ඝᚘլ㠩ᙓ

࿛ႿࢤለՕऱޗறழ࿇ᑷለՕ) ඝᚘழᚨףՂᔞᅝऱᑮᄶ ईΔᜳࣨۯ࣍ඝᚘᔾᑓፖڜᇘڇݠਮՂऱືᚘࣨٙհၴΔ ՠ܂ழᜳࣨΕືᚘٙᙟዞᚘ׌ၗԫದ᠏೯Δቹ 1 ੡ࠢীऱ ዞᚘقრቹΖەᐞ࿛ൎ৫Ꮑޣ֗ՕޅၦسขംᠲΔආشԲ ࢨԿዞᔚᣬᚘਢཏሙආشऱֱऄΔڕᔚᘿඝᚘᖲՕڍਢࠟ

ᔚ܉ᆜΔඝᔚၗ֨ᒵፖ᜕ٻ݈ߡګ θ ^=15Ζ܉ᆜΔຍጟݮڤ ऱ܉ᆜࠌඝᔚ׽ࢭ࠹ංԺݮګऱށԺΔޏ࿳Աඝᔚᝅ௕ऱ

࠹ԺणኪΔᝅ௕լ࣐ឰါΖ

ඝᚘழዞᔚኙޗறၞ۩ᚲᚘ೯܂Δԫ౳ઔߒ݁ൕԺᖂ ᨠរΔ൶ಘඝᚘழᚨԺΕᚨ᧢ऱధᡏംᠲΙڕ֮᣸[2]։࣫

լٵඝᚘֱڤޗறऱᚨԺፖᚨ᧢ംᠲΔࠀ༼נຍࠄඝᚘֱ

ڤ ऱ ૻ ࠫ Ι ֮ ᣸ [3] ༼ נ ඝ ᚘ ګ ݮ ऱ ڶ ૻ ց ై (Finite

element) ։࣫ᑓীΖԫ౳ۖߢΔᐙ᥼ඝᚘګݮګפፖܡऱ

ڂైڶΚޗற௽ࢤΔ׌ၗ᠏ຒΕඝᚘګݮֺΔՠ܂ᚘԺΕ ඝᚘၞ࿯ຒ৫ፖඝᚘऴᒵऱႜߡΔࠡխֻᰎޗறऱႿࢤΕ ᑷ๠෻णኪऴ൷ᐙ᥼ࠩሿٙऱ।૿ᔆၦΔԫ౳ᙇشႿࢤለ Օऱޗற׊ڍၞ۩ಯ־๠෻ (ᙓޗ)Δۖඝᚘຒ৫Εၞ࿯

෷ΕګݮֺΕՠ܂ᚘԺΕዞᔚႜߡऱ๻ࡳΔൄਢ៶طኔᎾ ףՠऱᆖ᧭ଖ൓ࠩΔᇠଖൄᙟլٵףՠයٙۖ᧢Δؘႊᔞ ழᓳᖞֱױ྇֟ඝᚘధჾംᠲΖ

ඝᚘழዞᔚऎࢬ૞ޣऱሎ೯૩ᇾດڻലᜳࣨګݮΔૉ

᠏ຒመ܅ΔֻᰎᢰᒴದᒋΔᏺףګݮॴԺΔ੷۟ᖄીՠٙ

ధါΙ᠏ຒመ೏Δঞޗற᧢ᜳᣤૹΖڼ؆Δඝᚘऱၞ࿯ຒ ৫ f ኙඝᚘመ࿓ᐙ᥼ՈৰՕΔ،ਢ׌ၗ᠏೯ԫഎዞᔚऎئ ᒵฝ೯ऱ၏ᠦΔၞ࿯ຒ৫መ೏ΔᄎขسֻᰎದᒋΙၞ࿯ຒ ৫መ܅Δᄎࠌᕻদ྇՛ۖขسధါΔਚ f ᚨٽ෻چ൳ࠫڇ ԫࡳऱᒤ໮հփΖۖඝᚘऴᒵऱႜߡΰऴᒵፖ Z ၗإֱٻ ऱ݈ߡαΔٵᑌᄎᐙ᥼ඝᚘመ࿓Δ݈ߡመՕΔᄎขسஉٻᐺ

ါΙ݈ߡመ՛ঞᄎ࿇س֊ٻధါΖ੡߻ַඝᚘመ࿓࿇سޗ றధါΕದᒋࠀᛧ൓່ࠋףՠய࣠Δؘႊᙇᖗᔞᅝऱ፹࿓

೶ᑇࡉሎ೯૩ᇾΔ֮᣸[4]ܓشಱូ։࣫ቃྒྷլٵ፹࿓೶ᑇ ඝᚘऱ।૿ษທ৫Ζ

੡ބנඝᚘףՠ່ࠋ፹࿓೶ᑇΔء֮شضՑऄၞ۩ኔ

᧭։࣫ΔضՑֱऄ!(Taguchi Method) [5] հ঴ᔆՠ࿓๵ቤ ऄΔਢএᄭ۞࣍ 1923 ڣ૎ഏԳ R. A. Fisher [6]ࢬ໌ࡨऱኔ

᧭๻ૠऄΔᆖطֲءضՑخԫ໑Փףא១֏ࠡอૠݾ؏Δ ܓشऴٌ।!(Orthogonal array)Εॾᇆᠧଃֺ!(S/N)Ε᧢ฆ

θ

α

ዞᔚ ඝᚘٙ

ືጹٙ

ඝᚘᔾᑓ

ߧ1 Ҥࠣ᱿ᅩࣱḻาߧ

ᑇ։࣫!(ANOVA)Εڃᚨ।ࢨڃᚨቹ࿛መ࿓ၞ۩։࣫Ζض Ցֱऄ (Taguchi Method) հ঴ᔆՠ࿓๵ቤऄױאՕၦ១

֏٤ڂైኔ᧭ऱኔ᧭ڻᑇΔؾছ๯ᐖऑچࠌش࣍ՠ࿓๻ૠ ፖ፹࿓່ࠋ֏։࣫ՂΔ壆ڕ֊চףՠය່ٙࠋ֏[7, 8]Εሽ

՗৞ᇘ፹࿓່ࠋ֏[9, 10]Ε࣋ሽףՠ।૿壄৫൳ࠫ[11]࿛Ζ ضՑऄԯאຝٝڂ՗ኔ᧭ऄ൶ಘข঴ऱ່ࠋ๻ૠࢨ፹࿓ऱ ለᔞֽᄷิٽΔڶࠄ፹࿓೶ᑇΰڕᛩቼᄵ৫ᄳ৫Ε፹࿓೶

ᑇ᧢ฆΕޗறګ։ΕၦྒྷۯᆜΕࠌشृڂై࿛αऱ൳ࠫࠀ ॺ࣐ࠃΔ૞ᄷᒔऱሒࠩኔ᧭๵ቤՂऱ೶ᑇଖڶழৰᣄሒ

ࠩΖضՑኔ᧭ऱڂ՗ऱֽᄷ֏إױᇞެڼംᠲΔڼऄൄᚨ ش࣍፹ທΕޗறΕא֗ข঴๻ૠ࿛ઌᣂᏆ഑Δऴٌ।ኔ᧭

ԯאᠦཋ֏ऱڂ՗ֽᄷ๵ቤኔ᧭ڂ՗ิٽΔٺଡ൳ࠫڂ՗

ၴᏁฤٽྤٌյ܂شऱഗء೗๻Δאᝩ܍ڂ੡ڂ՗ٌյ܂

شࢬທګऱኔ᧭։࣫ᎄ஁Δ່࠹৬ᤜऱऴٌ।ኔ᧭੡

L12(2¹¹)ΕL¹⁸(2¹*3⁷)ʳ ࿛Δڂ੡ຍࠄऴٌ।ኔ᧭Δܛࠌٺڂ

՗ၴࠠڶٌյ܂شΔ،ଚऱኔ᧭ᎄ஁բ݁֌ऱ։಻ڇٺิ

ٽխ[12]ΖྥۖΔऴٌ।ऱᙇᖗᏁ௅ᖕڂ՗ᑇΕא֗ٺڂ

՗ऱֽᄷᑇࠐެࡳΔለՕऱऴٌ।ኔ᧭Δࡐྥױ൓ࠩױॾ ৫ለ೏ऱ։࣫࿨࣠Δ܀ਢኔ᧭ګءലઌኙऱ༼ࣙΔ֠ࠡਢ ڇኔ᧭ழၴ९Ε፹࿓ګء೏ऱூࠏΖ

ڇެࡳᔞᅝ፹࿓೶ᑇ৵Δء֮ᚵ։࣫፹࿓ױᔾ৫Δױ ᔾ৫ਐᑑؘႊאข঴ኂࡎᑇᖕࠐ۷ૠข঴ױᔾ৫ٺ೶ᑇ ଖΔאቃ۷ข঴ᙟழၴಯ֏հणउΖࠉᖕױᔾ৫෻ᓵ[13]Δ ԫ౳ข঴ࠉࠡ؈யऱ௽ࢤΔױ։੡ڰ֝ཚ (Early life region)Εؓ᡹ཚ (Constant failure rate region) ֗۔֏ཚ (Wear out region)Δࠡ؈ய෷ࠤᑇܧԫ௮બীڴᒵΔᇠ௮બ

ীڴᒵঞᙟլٵհ؈யᑇᖕۖฆ[14]Δ֮᣸[15]א؈ய෷ࠤ ᑇ੡נ࿇រΔࠉᖕٺ؈யᑇᖕኙ؈ய෷հᐙ᥼ΔԱᇞข঴

௮બڴᒵհ᧢֏௽ࢤΖڇױᔾ৫ಯ֏ᑓڤխΔข঴հኂࡎ

։܉ࠤᑇᙟထլٵհข঴ᣊীۖڶլٵऱणኪΔൄ๯ᚨش հ؈யᖲ෷യ৫ࠤᑇΔڕൄኪ։܉Εኙᑇൄኪ։܉Εଁ܄

։܉ (Weibull Distribution)Εਐᑇ։܉…࿛Δຍࠄױᔾ৫ᑓ ڤࠡ؈ய෷ࠤᑇઃ੡ழၴ(ࢨᖙ܂ڻᑇΕ֘៿ڻᑇΕ၏ᠦ…

࿛)հࠤᑇΔڕ Ahmed [16]ܛאข঴հ֘៿ᖙ܂հ؈யڻᑇ

܂੡ױᔾ৫։࣫հ؈யᑇᖕΙTsai [17]։࣫լٵ壄৫Հױᔾ

৫۷ૠࢬᏁऱᑌءᑇΔא੡๵ቤױᔾ৫ᇢ᧭ऱࠉᖕΖۖ೶

ᑇ۷ૠխא່Օᄗۿऄ֗ᖲ෷ቹ౐ऄΔ੡່ൄ۷ૠٺጟൄ

شհኂࡎ։಻ֱऄፖᚨشΔܓشຍࠄ೶ᑇ۷ૠֱऄऱ࿨

࣠Δ٦ᚨشᔞٽ৫ᛀࡳΔױ൓ข঴ऱ່ᔞ։಻ࠤᑇΔၞԫ ޡԱᇞข঴ױᔾ৫ڴᒵ᧢֏[18]Ζ

ࠉᖕኔ᧭ބנऱ෻უ፹࿓೶ᑇΔຏൄᔞشڇਬԫףՠ ᒤ໮Δૉඝᚘढ঴ऱ९৫။९ࢨऴஉ။՛Δඝᚘழ࿇سధ

ါऱᖲ෷Ո။ՕΙኙৰ९ऱඝᚘढ᧯Δڂףՠ؈ඓऱᖲ෷

መՕΔՠᐗױ౨ආ࠷։੄ඝᚘ٦אԳՠ൷ٽऱֱڤݙګΔ ڕڼլ܀፹ທழၴᏺףΰګءᏺףαΔՠٙ।૿Ոڶ൷ᜓΰ঴

ᔆለ஁αΖڼ؆Δՠᐗڇࢭ൷ૡ໢ऱழଢΔ૿ኙመ९ऱढ঴

ΰլߜ෷ᏺףαΔױ౨א༼೏Ꮭ௑ࠐڂᚨ፹ທଅᙠΔ܀ڕڼ Ծᄎ૾܅ؑ໱ᤁञԺΖڇመװΔ९ՠٙඝᚘ؈ඓംᠲΔࠀ

ྤ֮᣸ڶߓอऱၞ۩൶ಘΔ੡ڼΔء֮࿨ٽױᔾ৫෻ᓵΔ

։࣫լٵ᧢ݮֺՠٙհඝᚘױᔾ৫Ζಾኙլٵদ৫հႽ࿟

ګ঴Δ൶ಘլٵ᧢ݮֺࢬ౨ףՠհ່Օ९৫Δ։࣫ඝᚘ؈

யڂ՗ᐙ᥼Δ۷ጩඝᚘ፹࿓ױᔾ৫Δ൶ಘ९৫ᏺףࢨऴஉ

ᜍ՛ழױᔾ৫᧢֏ൣݮΔၞԫޡ࿨ٽอૠᛀࡳֱऄΔא೶

ᑇ۷ጩऄ։࣫լٵףՠයٙՀױᔾ৫ಯ֏Δ৬مޗறদ৫ ࡉ᧢ݮֺᣂএΔຘመၦ֏ऱ፹ທଅᙠေ۷֗ٽ෻፹࿓๵

ቤΔᒔঅඝᚘףՠऱ᡹ࡳऱፖ঴ᔆΖ

ʷȮᅩࣱ⢌Ễאᄲ᧚ඖӠኔ

ඝᚘګݮመ࿓խທګ؈யࢨګীլߜऱ༓ଡ׌૞ڂై

ڕՀΚ

1. ޗறऱ࢏୶ࢤ֗࿏৫լߜΖ

2. ګীመ࿓խٺႈףՠයٙΰ೶ᑇα๻ࡳլᅝΖ 3. ඝᚘ፹঴ݮण๻ૠլߜΔڕႽ࢑תஉመ՛Ζ

4. ඝᚘᖲᖲᕴפ౨լߩΰڕྤऄ壄ᒔ൳ࠫףՠයٙΔᖲᕴ ࢤ౨ಯ֏ംᠲαΖ

ඝᚘګݮژڇԫଡඝᚘګݮֺᄕૻΔܛֻᰎऴஉ d0ፖ

່৵ګݮऱႽᙗ່՛ऴஉ dminհֺΰβ=d0/d_minαΔڇ๺ڍ໱

ٽՀඝᚘլ౨ԫڻګݮΔ૞ലඝᚘመ࿓։੡ڍଡၸ੄Δޢ ڻݙګԫࡳऱګݮΔאᝩ܍ՠٙ।૿ขسᒋెΔࠡޢڻඝ ᚘګݮֺՈؘႊየߩԫࡳऱයٙΙڼ؆Δᅝ೶ᑇ๻ࡳլإ ᒔழ༉ᄎขسٺጟ؈யΔൄߠऱ؈யڶ֊ٻᐺါΕஉٻᐺ

ါࡉದᒋΰቹ 2αΔࠡ଺ڂڕՀΝ

1. ֊ٻధါΝஉٻࢮᚨԺመՕΕඝᚘګݮֺ β መՕΕޢڻ ඝᚘऱޡၞ९৫መՕΖ

2. உٻᐺါΝ֊ٻᚘᚨԺመՕΔᦛڴᚨԺመՕࢨڇբขس ದᒋൣउΖ

3. ದᒋΝඝᚘګݮֺӪ၌መ᧢ݮᄕૻֺΕၞ༓෷֜ݶΖ ط࣍༼֒᠏ຒױ༼֒سข෷ࡉሿٙ।૿ᔆၦΔਚڇւ

๺ऱൣउՀΔᚨᕣױ౨چᙇᖗለ೏ऱ׌ၗ᠏ຒΖط֘៿ኔ

᧭൓वΔᙓऱ່Օඝᚘຒ৫੡ 800 m/minΙᔱΕᎭ੡ 1200 m/minΙլ㠩ᙓ੡ 300 m/minΔޢڻඝᚘऱګݮֺ݁լ౨၌

(a) ֊ٻధါ (b) உٻᐺါ

(c) ದᒋ

ᒔࡳ঴ᔆ௽ࢤ

ᒔࡳڂ՗ֽᄷ

ऴٌ।๻ᆜ

ኔ᧭ച۩

ኔ᧭࿨࣠։࣫

᧭ᢞኔ᧭

່ࠋิٽᙇ࠷

(a) ऴᒵী (b) Ⴝ࢑-ऴᒵী

(c) Ⴝࡰী (d) ٌཙী

ߧ 2 ᅩࣱ౑⣲ʠᶝࣺ

ߧ 3 Р⤑ُⳖ⃛Ⳍಙ᱿׶᫧ⴆႹ

መࠡګݮᄕૻֺΔܡঞᄎנ෼ధါΖၞ۩ඝᚘףՠழΔױ א௅ᖕቹ 3 ࠐษᙇඝᚘழࢬᏁऱႜߡα ࡉၞ࿯ຒ৫ fΖඝ ᚘլਢԫڻࠩۯΔۖਢ։ګ༓ଡխၴመ࿓Δ௽ܑਢኙ࿏৫

೏ޗறΔૉٵழኙޗறၞ۩ઌᚨऱᑷ๠෻Δലױ༼֒ࠡױ ඝᚘࢤΖ

ᑇ൳ඝᚘױආشٺጟլٵሎ೯૩ᇾऎࢨլऎᔾᑓࠐݙ ګ່ึऱئᒵΔඝᚘழࠀլਢዞᔚԫڻࢤچऎࢬᏁऱئᒵ

ၞ۩ዞᚘΔۖਢ։ڍଡၸ੄ၞ۩Δޢڻႛݙګԫຝ։ګݮΔ

ࠡሎ೯૩ᇾፖئᒵࠀ޲ڶऴ൷ᣂএΔڂڼΔޢၸ੄ױ௅ᖕ լٵऱणउΔࠌشլٵऱሎ೯૩ᇾᛧ൓ለࠋऱඝᚘய࣠ࡉ ඝᚘᔆၦΖٺၸ੄ሎ೯૩ᇾऱץ࿮ᒵዌګԱሿٙऱئᒵΔ ඝᚘऱሎ೯૩ᇾڶऴᒵীΕႽ࢑ীΕႽ࢑-ऴᒵীΕ࢓ᓤႽ

࢑ী 4 ጟ (ڕቹ 4)Ζ

ऴᒵীඝᚘ૩ᇾΝኔ෼ऴᒵሎ೯ለ੡ֱঁΔڇඝᚘழ

ࠡႜߡڇլឰ᧢֏Δאݮګئᒵऱץ࿮ᒵΖ

1. Ⴝ࢑-ऴᒵඝᚘ૩ᇾΝڇޢԫڻא՛੄Ⴝ࢑֊ԵΔྥ৵ڇ אؓ۩ऱऴᒵሎ೯Δࠡႜߡլ᧢Ζຍױࠌ֊Եழޓ٠ᄶΔ

༼֒।૿ᔆၦΖ

2. Ⴝ࢑ඝᚘ૩ᇾΝᖞଡඝᚘመ࿓ለ੡ؓᄶΔඝᚘመ࿓խऱ ڃٗለ՛Δ܀ࠡᒳ࿓ঞለ੡ᓤᠧΔ૞ૠጩנႽ࢑ऱึរΕ խ֨រ݄ᑑΖ

3. ٌཙႽ࢑૩ᇾΝࠡඝᚘய࣠ࡉᔆၦ່ړΔඝᚘመ࿓ؓ

᡹Δ܀ᒳ࿓່੡ᓤᠧΖ

ߧ 4 ʃ׺⳥ՒⰉ⭤᱿ᅩࣱ⭰ല

ߧ 5 ᮪םᅞᘍ૪㊹ᙟỄߧ ɿȮ᮪םᅞᘍʠٴ⫨డỄ⣳Ԭ

ڇᙇᖗޢڻඝᚘ֊Եរழ૞ࣹრፖՂԫଡ֊Եរ૞ᠦ

ၲԫࡳऱ၏ᠦΔא߻ַࠟរመ२ڇॵ२೴഑ขسૹᓤඝ ᚘΔທګڼ๠ᕻᖺ྇ᜳΔ່ึขسᐺါΖ

ضՑऄኔ᧭࿓ݧ๻ૠڇضՑऄ঴ᔆՠ࿓ݾ๬խΔኔ᧭

๻ૠ׌૞ױ೴։੡ԿՕႈؾΔรԫႈؾ੡ኔ᧭๵ቤΕรԲ

ႈؾ੡ኔ᧭۩੡ࡉรԿႈؾ੡ኔ᧭։࣫࿛Δࠡኔ᧭ੌ࿓ڕ ቹ 5Ζ

1. ᮪םᅞᘍ

ضՑֱऄհ঴ᔆՠ࿓๵ቤΔࠡ׌૞ޡᨏ੡ܓشऴٌ।

f=mm/min إൄඝᚘ೴

55 60 65 70

80 1 2 3 4 5

α=deg

75

๵ቤࠡઌᣂՠ࿓ڂ՗ࠐ৬مኔ᧭հႈؾΔലࢬᛧ൓ኔ᧭࿨

࣠٦ຘመࠡॾᇆᠧଃֺ!(S/N)Ε᧢ฆᑇ։࣫!(ANOVA) Ε ڃᚨ।ࢨڃᚨቹ࿛መ࿓ࠐၞ۩։࣫Ζڶᣂء֮፹࿓೶ᑇ່

ࠋ֏հઔߒਮዌՕીڕՀΚ

(ԫ) ๻ࡳګীመ࿓խհ঴ᔆ௽ࢤؾᑑΔ࠷ࠡ௽ࢤ੡ඨՕΕ ඨ՛ࢨඨؾ࿛Ζ

(Բ) ᙇᖗ፹࿓൳ࠫڂ՗

ࠉᖕ፹঴ګীመ࿓խઌᣂڂైΔ։࣫ףՠයٙኙࠡ঴

ᔆհᐙ᥼ࠀ๻ࡳ੡൳ࠫڂ՗Ζ

(Կ) ᙇࡳࠡ൳ࠫڂ՗հֽᄷଖΔܛઌᣂٺႈףՠයٙᒤ໮

հ๻ࡳΖ

൳ࠫڂ՗հֽᄷଖא଺ࡨףՠයٙΕޗޗࢤᔆࢨ፹࿓

೶ᑇ࿛යٙΔࠐ๻ࡳࠡٺႈףՠයٙհᒤ໮Ζ (؄) ৬مऴٌ।Ζ

ല๻ࡳ੡൳ࠫڂ՗հٺႈףՠයٙڕඝᚘຒ৫Εၞ࿯

෷Εሎ೯૩ᇾΕՠ܂ᚘԺΕڶྤᑮᄶ࿛ΔࠉᅃضՑֱ

ऄऴٌ।಻ᆜٺႈףՠයٙհྒྷᇢิٽΖ

(ն) ਊᅃऴٌ।ࢬ༼ࠎٺႈףՠයٙհྒྷᇢิٽΔၞ۩ኔ

᧭ᑇᖕگႃΖ

(ք) ኔ᧭ᑇᖕ᠏֏ګॾᇆᠧଃֺ S/NΔࠀૠጩࠡ᧢ฆᑇ։

࣫Ζ

ࠉᖕضՑֱऄലؾᑑ঴ᔆհኔ᧭ᑇᖕૠጩנࠡॾᇆᠧ

ଃֺ S/NΔ

) . . log(

10 MSD

SN=−

ڼ๠ M.S.D.੡ٺႈྒྷᇢิٽհؾᑑ঴ᔆऱ࿨࣠ᑇᖕհ

ֱ݁ؓೣ஁ଖ!(the mean square deviation)Ζ!

(Ԯ) ࠉᖕॾᇆᠧଃֺ S/N ૠጩࠡ᧢ฆᑇ։࣫Δޣ൓፹࿓հ

່ࠋ֏ףՠ೶ᑇΖ

(Զ) ขس S/N ڃᚨ।ࢨڃᚨቹΔᛀီٺ൳ࠫڂ՗հಥ᣸෷

֗ބנᓳᖞڂ՗Ζ

ٺ൳ࠫڂ՗հಥ᣸෷੡ٺ൳ࠫڂ՗ኙؾᑑ঴ᔆऱᐙ᥼

࿓৫Δױ༼ࠎ๻ૠृᓳᖞለ᧩ထ൳ࠫڂ՗೚੡༼ࣙࠡ

ؾᑑ঴ᔆհ೶ەΔۖ᧢ޓለլ᧩ထ൳ࠫڂ՗೚੡૾܅

ګءհࠉᖕΖ 2. ૪㊹⃌ኞ

ء֮൶ಘኙွ੡Ⴝ࿟ীՠٙΔኔ᧭๻ໂ੡ᑇ൳ඝᚘ ᖲΔء֮אඝᚘ৵Ⴝ࿟փஉፖᔾᑓऴஉऱ஁ฆ੡঴ᔆڂ

՗Δᅝ೶ᑇ๻ࡳߜړΔԲृᎄ஁ऱ᧢ฆৰ՛Δ֘հΔঞ᧢

ฆৰՕΰ঴ᔆլߜαΖඝᚘ፹࿓խૉՠ܂ᚘԺ֜ՕΕၞ༓෷

֜ኬΕᙓࣨ֜ᜳΕޗற࿏৫መ೏࿛Δ݁ᄎທګඝᚘధါࢨ ದᒋ࿛ംᠲΔ׊ᙟထඝᚘՠٙ९৫ᏺףΔՠٙ࿇سՂ૪ം

ᠲΰ؈யαऱᖲᄎ။ՕΙڼ؆ΔዞᔚႜߡΕዞᔚႽ࢑תஉΕ ڶྤᑮᄶᕪΔٍᄎᐙ᥼ඝᚘףՠհ঴ᔆፖ؈யΖࠉᖕ෼໱

ՠ܂ᆖ᧭Δඝᚘףՠऱ׌૞ᐙ᥼ڂ՗੡ඝᚘຒ৫Εၞ࿯෷Ε ՠ܂ᚘԺΕዞᔚႜߡΔࠡהᐙ᥼ለ՛հႈؾڇڼီ੡ᠧಛ ڂ՗Δࠡයٙ๯๻ګԫᑌΖەᐞൄش፹࿓೶ᑇऱิٽΔء

֮ᙇᖗ L9(3⁴) ऴٌ।੡ኔ᧭ᑇᖕၦ࠷հഗ៕Δࠡխڂ՗ۯ

⠧ɺ ᅩࣱໞࠣ૪㊹᱿࿳Ӽߌઈדᖛ᜾⠧

ڂ՗ ᎅࣔ ֽᄷԫ ֽᄷԲ ֽᄷԿ

A _ඝᚘຒ৫ 180 m/min 240 m/min 300 m/min B _ၞ࿯෷ 2 mm 4 mm 6 mm C _ՠ܂ᚘԺ 55 kg/cm² 60 kg/cm² 65 kg/cm²

D _ዞᔚႜߡ 60_̓ 65_{̓ ˊ˃̓}

ᄷհެࡳਢא፹࿓խൄشհ೶ᑇ੡׌Δڶᣂء֮ኔ᧭൳ࠫ

ڂ՗ֽ֗ᄷڕ।ԫࢬقΖ

։ ࣫ ່ ࠋ ፹࿓ ೶ ᑇ ࠌ ش հ ګ ী ᑓ ࠠ੡

φ

φ

փஉࡉᑓࠠऱ֡՚஁ฆ੡ၦྒྷኔ᧭ᑇᖕΔࠡኔ᧭๵ቤ֗ࠡ

ઌᣂհኔ᧭ᑇᖕڕ।ԲࢬقΔଡܑ௽ࢤڂ՗ಛᇆᠧಛֺ

(S/N) ऱ֘ᚨڕ।ԿࢬقΔط।Կ࿨࣠࿇෼Δඝᚘףՠ່

ࠋ঴ᔆ௽ࢤհڂ՗ิٽ੡

{A2, B1, C2, D3}

ݺଚለᣂ֨ऱਢቃྒྷଖ֗ᒔᎁኔ᧭ऱૠጩଖऱॾ֨೴

ၴΔᅝࠟଡॾ֨೴ၴڶٚ۶ૹᦤழΔݺଚױאᒔᎁኔ᧭ऱ

࿨࣠ࡉቃྒྷଖജ൷२Ζ੡ֺለ່ࠋףՠයٙ (A2, B1, C2, D3) հኔ᧭ଖፖቃྒྷଖհ஁ฆΔݺଚگႃ 10 ิ່ࠋ೶ᑇՀ հኔ᧭ᑇᖕΰ।؄αΔطԲृհؓ݁ଖΕᑑᄷ஁ऱ஁ฆ࿇෼Δ ቃྒྷଖፖኔ᧭ଖৰ൷२Δڼ࿨࣠ᎅࣔڼ່ࠋิٽ೶ᑇױᛧ

൓᡹೜ऱףՠ঴ᔆΖ

߈Ȯרㄅಙ᫧⧄

ױᔾ৫ഗءՂਢԫଡאᖲ෷ࠐ༴૪ߓอΕข঴ࢨᇘໂ

঴ᔆֽᄷऱਐᑑΔࠡࡳᆠڕՀΚԫଡߓอࢨข঴ڇਬԫᖙ

܂ᛩቼՀፖࠌشழၴᒤ໮Δ౨ႉܓݙګቃࡳٚ೭ऱᖲ෷

[13]Ζ௅ᖕࡳᆠᎅࣔΔߓอঅ਍إൄऱᖲ෷ױီ੡ழၴࠤ ᑇΔאᖲ෷।قڕՀ

0 )

( )

(t₁≥t =Rt t≥

P (1)

ڼ๠ t¹ז।ߓอሎ܂إൄழၴΖڂڼΔR(t) ܛ੡ԫߓ อڇ t ழၴא৵ױ౨սإൄՠ܂ऱᖲ෷Δঞױᔾ৫ࠤᑇऱ

֘૿ F(t) ܛ੡ਚᎽழၴ։಻ࠤᑇΔױ।ق੡

0 ), ( ) ( 1 )

(t = −R t =Pt₁ ≤t t≥

F ⁽²⁾

ڕ࣠ਚᎽழၴشᙟᖲ᧢ᑇ t ࠐז।Δۖ t ऱᖲ෷യ৫ ࠤᑇ f(t) ፖױᔾ৫ࠤᑇ R(t) հᣂএڕՀ

∫

−

=

−

=

t

d f t

F t R

0

) ( 1 ) ( 1 )

( τ τ ⁽³⁾

⠧ʷ ૪㊹⤺Ԭד૪㊹ᄲჇ!

Exp. A B C D y1 y2 y3 y4 y5 y6 Ave S S/N

1 1 1 1 1 0.50 0.88 1.02 0.61 0.97 1.01 0.83 0.22 1.29 2 1 2 2 2 0.80 0.70 0.65 0.23 0.78 0.38 0.59 0.23 3.97 3 1 3 3 3 1.00 1.28 1.55 1.34 1.66 1.63 1.41 0.25 -3.12 4 2 1 2 3 0.30 0.56 0.52 0.46 0.36 0.60 0.47 0.12 6.34 5 2 2 3 1 1.03 1.30 1.20 0.60 1.27 0.94 1.06 0.26 -0.74 6 2 3 1 2 0.80 1.00 1.40 1.38 1.57 0.93 1.18 0.31 -1.72 7 3 1 3 2 0.90 1.21 1.40 1.18 1.40 1.48 1.26 0.21 -2.14 8 3 2 1 3 0.54 0.72 0.85 0.41 1.48 0.84 0.81 0.37 1.05 9 3 3 2 1 1.60 1.70 1.43 1.68 1.87 1.28 1.59 0.21 -4.11

Ave 0.95 0.25 0.62

⠧ɿ ᅩࣱໞࠣ૪㊹ʑ᧚ඖߌઈଃ S/N ᕗ᱿וະ⠧ד ߧ

A B C D Level 1 0.72 1.83 0.21 -1.19 Level 2 1.30 1.43 2.07 0.04 Level 3 -1.73 -2.98 -2.00 1.42

Effect 3.03 4.82 4.06 2.61

Rank 3 1 2 4

אਬԫழၴរ੡ഗᄷΔەᐞਬԫழၴរऱױᔾ৫հ᧢

֏ֺՂᅝழऱױᔾ৫ጠ੡؈ய෷ࠤᑇ (hazard function)Δڼ

؈ய෷ࠤᑇ༉ਢᛳၴ؈ய෷ΔڂڼΔ؈ய෷ࠤᑇ h(t)ױᐊ ګ

) (

) ( )

(

) ( ) ) (

( Rt

t f t

t R

t t R t t R

h =

∆

∆ +

= − ⁽⁴⁾

طڼױव f(t)ΕR(t) ፖ h(t) ԿृၴऱઌյᣂএΔ׽૞

वሐࠡխԲଡΔܛױޣ൓׼ԫृऱࠤᑇΖۖ؈யᑇᖕگႃ

ڶՀ٨༓ጟΚ

1. ݙ٤ᑇᖕΔᇢ᧭ڇࢬڶᑌ঴݁؈யթೖַΖ

2. ؈யᛀྒྷ (censoring)Δࠉᖕᑇᖕ࠷൓ֱڤױ։੡Κ(1)໢

ԫᛀྒྷ: (a) ྒྷᇢᑌ঴؈யሒਬԫ๻ࡳᑇ৵ܛೖַᇢ

᧭Ι(b) ྒྷᇢழၴሒਬԫ๻ࡳଖ৵ܛೖַᇢ᧭Ζ(2)ڍૹ

⠧߈ ሱ̈́אᄲʠ૪㊹ϊ⎞ㅷᛵϊʠదᯌ

Y (_ኔ᧭ᑇᖕ)

Optimal 0.68 0.52 0.61 0.97 0.25 0.43 0.58 0.81 0.72 0.48 Ave S S/N

ኔ᧭ଖ 0.61 0.20 3.89

ቃྒྷଖ 0.68 0.11 4.76

ᛀྒྷΔྒྷᇢᑌ঴ऱྒྷᇢழၴլٵΰڕྒྷᇢխآਚᎽܛ๯

ฝၲαΖ

ࠉᖕگႃऱ؈யᑇᖕΔױᔾ৫։ֱ࣫ऄ׌૞ڶԲጟΚ ॺ೶ᑇ֏۷ૠፖ೶ᑇ֏۷ૠΖॺ೶ᑇ֏۷ૠܛآ೗ࡳኂࡎ

։಻հױᔾ৫։࣫Δ،ਢऴ൷ࠉᖕ؈யᑇᖕࠐ۷ጩױᔾ ৫Δૉ؈யᑇᖕ੡ᠦཋীழΔঞױᔾ৫ױطՀڤ۷ጩΖ

n t t n

R ^s()

)

( = ⁽⁵⁾

؈யᖲ෷യ৫ࠤᑇ(PDF)ױ।قڕՀΚ!

t n

t t n t n t

t t R t t R

f ^{s s}

∆

∆ +

= −

∆

∆ +

= ()− ( ) () ( ) )

( ⁽⁶⁾

ঞ؈ய෷ࠤᑇױ।قڕՀΚ!

t t n

t t n t n t R

t t f h

s s s

∆

∆ +

= −

= ()

) ( ) ( ) (

) ) (

( ⁽⁷⁾

ࠡխΚ n ז।᜔ᇢ᧭ᑌءᑇؾΔns ז।ڇழၴរ t ழऱژ੒ᑇΔӔt ז।ழၴၴሶΖ

೶ᑇ֏۷ૠ੡೗ࡳኂࡎ։಻հױᔾ৫։࣫Δൄشऱኂ ࡎ։܉ڶൄኪ։܉Εਐᑇ։܉ΕLognormal ։܉Εଁ܄։

܉࿛Ζڇ೗ࡳኂࡎ։಻խΔଁ܄։܉੡ױᔾ৫ՠ࿓խ່ൄ

ࠌشհቃ۷։಻Δط࣍ଁ܄։܉լٵऱ೶ᑇิٽऱױᔾ৫ ࠤᑇࠠڶڍ᧢֏ऱ௽ࢤΔኙ࣍լٵऱข঴ኂࡎᇷறΔ༓׏

6 4 2 0 -2 -4

A1 A3 B2 C1 C3 D2

ຟڶᔞᅝऱ೶ᑇิٽ౨ജᔞ֊چ༴૪Ιଁ܄։܉ऱᖲ෷യ ৫ࠤᑇቹݮࠠڶڍ᧢ࢤΔۖ׊ઃ౨ജᔞش࣍༴૪ข঴Ꭰᏺ ࢨᎠ྇ऱ؈ய෷Δࢬאڇױᔾ৫Ꮖ഑ऱኂࡎ։࣫Ղ๯ᚨش چઌᅝᐖऑΖᅝଁ܄։܉ݮण೶ᑇӪ࿛࣍ 1 ழΔ؈ய෷ࠤ ᑇګ੡ԫൄᑇΔՈ༉ਢൄߠऱਐᑇ։಻Δ᥆࣍᡹ࡳཚ؈யΙ ଣૉݮण೶ᑇӪଖտ࣍ 0 ፖ 1 հၴΔ।قข঴ऱ؈ய෷੡

ԫᎠ྇ࠤᑇΔຏൄຍጟൣݮਢ࿇سڇข঴ઔ࿇ࠩګᑵཚ

ၴΔ᥆࣍ڰ֝ཚ؈யΙڕ࣠ݮण೶ᑇǫଖՕ࣍ 1 ழΔঞ।

قข঴ऱ؈ய෷੡ᎠᏺࠤᑇΔຏൄ࿇سڇข঴ᗣჾᣤૹ ΰwear-outαऱᗣ౛ཚΔ᥆࣍ᗣ౛ཚ؈ய”Ιᅝݮण೶ᑇӪ ଖપ੡ 3.6~3.8 ழΔࠡ௽ᐛല൷२࣍ൄኪ։܉Ζ

ၞ۩೶ᑇ֏۷ૠழΔᏁ٣೗๻؈யᑇᖕ։܉Δ٦ၞ۩

؈ய։܉೶ᑇ۷ૠΔൄشऱ۷ૠֱऄਢ່Օઌۿ۷ૠ (Maximum Likelihood Estimation)Ζᅝ೗ࡳ։಻ၞ۩ױᔾ৫ ᑇᖕᇞ࣫ழΔൄᅸࠩऱംᠲਢ೗ࡳऱኂࡎ։಻ਢܡإᒔΔ ڂڼຘመᔞٽ৫ᛀࡳࠐܒឰ೗๻ऱإᒔࢤਢؘ૞ऱΔԫ౳

ൄࠌشऱᛀࡳऄڶ׬ֱ (Ӿ²) ᛀࡳא֗ Kolmogorov-Smirnov ΰ១ጠ K-Sαᛀࡳ18]Ζ

ʽȮᅩࣱרㄅಙӠኔ

੡։࣫ඝᚘ୲๺ףՠ९৫Εေ۷፹࿓ଅᙠΔء֮ಾኙ լٵࣨদլ㠩ᙓࣨၞ۩ඝᚘױᔾ৫։࣫Δ։࣫ޡᨏڕՀΚ 1. दᄓ⎞רㄅಙહ∑

ඝᚘ؈ய׌૞ڶԿጟΚΰஉٻᐺါΕၗٻᐺါፖದ ᒋαΔױᔾ৫ਢ։࣫ࣨޗ୲๺ඝᚘ९৫֗լٵ᧢ݮֺՀ ඝᚘױᔾ৫Ζ

2. ૪㊹⣳Ԭ⎞⥑હ

ء֮ಾኙদ৫ 1.0, 1.5, 2.0, 2.5 mm ऱլ㠩ᙓࣨၞ۩

ඝᚘᇢ᧭Δඝᚘ፹࿓೶ᑇࠌشছᆏضՑֱऄ։࣫հ࿨

࣠Δඝᚘᑓࠠ੡

φ

3. ᄲჇᄇゝ⎞Ӡኔ

گႃऱᇷறլૻ࣍؈யᇷறΔۖᚨץܶ᧩෼؈யհ ࢬڶข঴ྒྷᇢ௽ࢤᔆᇷறΔܛ؈யፖآ؈யข঴൷ᚨࠠ

ໂᇠྒྷᇢ௽ࢤᔆઌᣂᇷறΙၞԫޡܓشፋᣊ։࣫ࢨࠡ،

อૠ։࣫֫੄Δଵೈॺቃཚڂైࢬທګհ؈யᑇᖕΙە ᐞඝᚘధါ֗᧢ݮ௽ࢤΔء֮אڍૹᛀྒྷֱڤگႃ؈ய ᑇᖕΔڶᣂءઔߒհኔ᧭ᑇᖕڕ।նࢬقΖ

4. Ӡ̡אᄲ̒⤺

ಾኙگႃհᑇᖕၞ۩։܉೗๻֗೶ᑇ۷ૠΔء֮א

່Օઌۿऄ (Maximum-likelihood method) ۷ጩਐᑇΕൄ

ኪΕଁ܄࿛Կጟ։܉೶ᑇΖء֮ܓش K-S (Kolmogorov-

⠧ʽ ʃ׺ኈׂᅩࣱदᄓᄲჇ

t (mm) 1.0 1.5 2.0 2.5

x1 44 145 200 262 x2 43 106 227 308 x3 40 120 202 326 x4 48 104 167 254 x5 65 132 215 273 x6 50 115 200 246

ߧ6 ᅩࣱԽడ⳧Ễ

Smirnov) ᛀࡳհֱऄΔ։ܑૠጩנࠡᨠྒྷଖ֗ཚඨଖ

ΰ඿ࣚൕհኂࡎ։಻ऱ F(t) ଖαઌ྇৵ऱ࿪ኙ஁ฆଖΔ ᨠኘ۶ጟ։܉ऱ஁ฆ່՛Δࠐܒܑ؈யᑇᖕᔞٽ࣍ୌጟ

։܉Ιಾኙ।նհ؈யᑇᖕΔٺ೗๻։܉հ۷ૠ೶ᑇ֗

ᛀࡳ࿨࣠ڕ।քࢬق Ζ 5. רㄅಙ̒⤺

ࠉᖕ।ք࿨࣠Δඝᚘ؈யאൄኪ։܉༴૪່৾ᅝΔ ط।քհ(µ, σ)Δࠡ፹࿓ױᔾ৫ױطՀڤ۷ጩΔ



 



 − Φ

= σ µ

R x ⁽⁸⁾

ڶᣂլ㠩ᙓլٵࣨদऱඝᚘױᔾ৫ڕቹ 7 ࢬقΖ

๻ࡳඝᚘ९৫ፖऴஉֺଖ੡ޗறհ᧢ݮֺ YΔࠉᖕ।

նᑇᖕΔױၞԫޡ۷ጩլٵࣨদඝᚘ᧢ݮֺհؓ݁ଖΕᑑ ᄷ஁ΰµY, σYαΔڕ।ԮࢬقΔല࿨࣠൅Եڤ(8)Δױጩנ᧢

ݮֺࡉױᔾ৫ᣂএΔቹ 8 ᧩قլٵױᔾ৫հޗறদ৫ࡉ᧢

ݮֺᣂএΖطቹ 8 ױ઎נඝᚘ᧢ݮֺࡉޗறদ৫ګإֺᣂ এΔຍਢڂ੡ለদऱޗறڶለՕऱൎ৫ΰࣂݼದᒋα֗୲

๺ለڍऱႿࢤ᧢ݮΖࠉᖕቹ 8 ࿨࣠Δၞԫޡ࿨ٽڃូ։࣫

ݾ؏Δലױංᖄנޗறদ৫ࡉףՠ᧢ݮֺᣂএΖאױᔾ৫ R = 0.95੡ࠏΔޗறদ৫ࡉ᧢ݮֺऱᣂএലਢ

0 0.2 0.4 0.6 0.8 1

0 80 160 240 320

Length (mm)

Reliability

t 1.0 t 1.5 t 2.0 t 2.5

0.1 0.3 0.5 0.7 0.9 1.1

1 1.5 2 2.5 3

Thickness

Deformation ratio

R=0.95 R=0.8 R=0.6 R=0.4

⠧Ҟ दᄓᄲჇʠ̒⤺אᄲ⎞ KS ᒑહ Normal Weibull Exponential

t Ӵ Ӻ KS _{ӯ Ӫ} KS _Ӱ KS

1 48.3 8.1 0.252 51.9 5.7 0.280 40.0 0.266 1.5 120.3 14.4 0.175 126.9 8.6 0.208 104.0 0.218 2 201.8 18.3 0.223 209.8 13.6 0.239 167.0 0.445 2.5 278.1 29.1 0.237 291.8 9.9 0.263 246.0 0.287

⠧ɼ ᅩࣱ⩐ഐᕗʠ౹ࠀϊ⎞ᐻ᜾ద

t (mm) 1.0 1.5 2.0 2.5

Ӵˬ 0.179 0.446 0.7469 1.0303 Ӻˬ 0.034 0.057 0.075 0.1183

ߧ 7 ʃ⺩⻘ኈᅩࣱרㄅಙ

!

ߧ 8 ኈׂُ⩐ഐᕗ〦͸

36 . 0 482 .

0 −

= t

Y

ຘመՂڤΔᄐृױࠉᖕࣨদ߰ຒ۷ጩנඝᚘףՠ୲๺

९৫Δᝩ܍ᄅข঴ၲ࿇ழڂቫᇢᙑᎄࢬທګհګء௡၄Δ ٵழ༼ࠎᄐृଅᙠေ۷հࠉᖕΖ

ҞȮ⃌ ⧄

ء֮אႽදীޗற੡։࣫ኙွΔܓشضՑऄބנඝᚘ

່ࠋ፹࿓೶ᑇΔಾኙڇඝᚘףՠழऱధါΕ᧢ݮΕֻᢰፖ ፖ៫ڴംᠲΔ൶ಘᐙ᥼ඝᚘګݮհ൳ࠫڂ՗ፖեឫڂ՗Δ ૡࡳ൳ࠫڂ՗ᔞᅝۯᄷΕ঴ᔆؾᑑ௽ࢤΔᆖطॾᇆᠧଃֺ

S/N ૠጩፖ᧢ฆᑇ։࣫መ࿓Δބנࠡᐙ᥼ംᠲհ׌૞ڂ

ైΕެࡳ່ࠋ፹࿓යٙΔ༼ࣙףՠ঴ᔆፖ૾܅سขګءΙ

ၞԫޡ࿨ٽױᔾ৫෻ᓵΔ։࣫ඝᚘመ࿓ऱ؈யംᠲΕլٵ

ࣨদ୲๺ඝᚘ९৫Ζ

ᐙ᥼ඝᚘףՠ঴ᔆऱڂ՗ڶৰڍΔڇመװඝᚘףՠ፹

࿓೶ᑇऱ๻ࡳΔຏൄਢطףՠृࠉᖕᆖ᧭ࠐࡳΔࠀྤ֮᣸

ኙլٵඝᚘ೶ᑇࢬທګऱᐙ᥼ၞ۩൶ಘΙຘመء֮։࣫࿨

࣠Δലױ྇֟ڂ፹࿓೶ᑇ๻ࡳլᅝࢬທګऱ؈யംᠲፖګ ء௡၄Ζኔ᧭࿨࣠᧩قඝᚘ؈யܧൄኪ։܉Δຘመ؈யᑇ ᖕ։࣫ፖױᔾ৫۷ጩΔױቃ۷ඝᚘ୲๺ףՠ९৫Εլٵࣨ

দඝᚘ୲๺᧢ݮֺΙڼ؆Δء֮࿨ٽڃូ։࣫ݾ؏Δ৬م լ㠩ᙓඝᚘ᧢ݮֺࡉޗறদ৫ᣂএΙઔߒ࿨࣠ല༼ࠎ९ী

ՠٙඝᚘףՠױ۩ࢤေ۷Εඝᚘ፹࿓ଅᙠေ۷հࠉᖕΖ

⦒ ⨀

ء֮ᛧ൓ഏઝᄎૠ྽ᒳᇆ NSC 94-2622-E-237 -007

-CC3 ༼ࠎᆖ၄࠰ܗΔႛڼી᝔Ι܂ृॺൄტ᝔ᐉ਷ࡡ୉

༼ࠎᣪ၆რߠΖ

Ὢ⚦€೧

h M.S.D R S/N Y Ӵ Ӻ

؈ய෷ࠤᑇ

ֱ݁ؓೣ஁ଖ ױᔾ৫ ಛᇆᠧಛֺ

९உֺ

ؓ݁ଖ ᑑᄷ஁

א≙ᄽ᪇Ř

1. Wong, C. C., Dean T. A., and J. Lin, “A Review of Spinning, Shear Forming and Flow Forming Process,”

Internal Journal of Machine Tools and Manufacture, Vol.

43, pp. 1419-1435 (2003).

2. Quigley, E., Monaghan, J., “Metal Forming: An Analysis of Spinning Processes,” Journal of Materials Processing Technology, Vol. 103, pp. 114-119 (2000).

3. Quigley, E., Monaghan, J., “Enhanced Finite Element Models of Metal Spinning,” Journal of Materials Processing Technology, Vol. 121, pp. 43-49 (2002).

4. Chen, M. D., Hsu, R. Q., and Fuh, K. H., “Forecast of Shear Spinning and Surface Roughness of Spun Cones by Employing Regression Analysis,” Internal Journal of Machine Tools and Manufacture, Vol. 41, pp. 1721-1734 (2001).

5. Taguchi, G., Introduction to Quality Engineering, Asian Productivity Organiztion, Tokyo, Japan. (1990).

6. Fisher, R. A., Statistical Methods for Research Workers, Oliver and Boyd, London , UK. (1925).

7. Koa, D. C., Kimb D. H., and Kimc, B.M., “Application of Artificial Neural Network and Taguchi Method to Preform Design in Metal Forming Considering Workability,”

International Journal of Machine Tools and Manufacture 39, pp. 771–785 (1999).

8. Yang W. H., and Tarng, Y. S., “Design Optimization of Cutting Parameters for Turning Operations Based on the Taguchi Mmethod,” Journal of Materials Process Technology Vol. 84, pp. 122-129 (1998).

9. A. Mertol, “Application of the Taguchi Method on the Robust Design of Molded Plastic Ball Grid Array Packages,” IEEE Transaction Components Packaging and Manufacturing Technol,0 Part B, pp. 734-743 (1995).

10. Chen, R. S., Lin H. C., and Kung, C., “Optimal Dimension of PQFP by using Taguchi method,”

Composite Structures Vol. 49, No. 2, pp. 1-8. (2000).

11. Tsai K. M., and Wang, P. J., “Semi-empirical Model of Surface Finish on Electrical Discharge Machining”, International Journal of Machine Tools and Manufacture,

Vol. 41, pp. 1455–1477 (2001).

12. Fowlkes W. Y., and Creveling C. M., Engineering Methods for Robust Design: Using Taguchi Methods in Technology and Product Development, Addison Wesley, Reading, Massachusetts, pp. 308 (1985).

13. Elsayed, A. E., “Reliability Engineering,” Addison Wesley Longman, Inc., pp. 263-279 (1996).

14. Wang Yiqiang , Jia Yazhou , Jiang Weiwei ,“Early Failure Analysis of Machining CentersŘ A Case Study,”

Reliability Engineering and System Safety , Vol. 72 , pp.

91-97 (2001).

15. Wang, K. S., Hsu, F. S., Liu, P. P., “Modeling the Bathtub Shape Hazard Rate Function in Terms of Reliability,”

Reliability Engineering and System Safety, Vol. 75, pp.

397-406 (2002).

16. Al-Garni, Ahmed Z., Sahin A. Z., and!Abdulghani A., Al-Farayedhi, ơ A Reliability Study of Fokker F-27 Airplane Brakes,ƢReliability Engineering and System Safety ,Vol. 56 , pp. 143-150 ( 1997).

17. Tsai, Y. T., and Wang, K. S., “A Study of Sample Size Analysis to Support Reliability Test Programming,”

Journal of Chinese Society of Mechanical Engineers, Vol.

28, No. 3, pp. 315-323, (2007).

18. Nelson, W., “Accelerated Testing: Statistical Models, Test Plans and Data Analyses”, John Wiley and Sons, Inc., NY.

USA, (1990).

2006ڣ 11 ִ 01 ֲ گᒚ 2006ڣ 11 ִ 03 ֲ ॣᐉ 2008ڣ 02 ִ 18 ֲʳ ൷࠹