Viigaji vya WIA SOOM

Kiwanda cha semikondakta Modeli hai

Unaendesha eneo la lithografia la kiwanda cha wafa za mm 300 — skana nane, chumba safi na mapishi yanayopaswa kubaki ndani ya viwango. Wafa hupanga foleni, zana huharibika, chembe huingia na mavuno hubadilika kwa kila uamuzi.

Utakachojifunza

Kiigaji

Muda 0 h
Upatikanaji wa zana 100% · Kazi inayoendelea 20 · Daraja la ISO la chumba safi 3.4S1⚙S2▶S3▶S4▶S5▶S6▶S7‖S8‖WIP 20▶ 34 wph
  • Uzalishaji
  • Kusubiri
  • Uhandisi
  • Imesimama (matengenezo)
  • Chembe za hewani

Vidhibiti

Wafa zinazoachiliwa kwenye eneo la kazi kwa saa.

Sehemu ya muda wa skana inayotolewa kwa makundi ya majaribio ya wafer yanayofundisha mchakato: uzalishaji kidogo sasa, kasoro chache baadaye.

Kila fundi hukarabati zana moja kwa wakati.

Mabadiliko zaidi ya hewa hupunguza msongamano wa chembe; nguvu ya feni hukua kwa mchemraba wa kasi.

Kila mtu aliyevaa vazi maalum bado hutoa chembe.

Wafa zinazopimwa kwa saa: chati ya SPC iliyo kali zaidi, uwezo mdogo kidogo.

Huchukua saa 3 na huongeza watu 2 chumbani wanapofanya kazi.

Saa 2 kwa nusu uwezo, kisha mchakato unarudi kwenye lengo.

Viashiria

Chipu nzuri zilizotoka
19547/h
Mavuno
89.8%
kawaida
Daraja la ISO la chumba safi
3.4
kawaida
Muda wa mzunguko wa eneo
1.6h
kawaida
Upatikanaji wa zana100 %
Matumizi ya zana71 %
Muda wa uhandisi10 %
Uanzishaji wa wafa ulioachiliwa34 wph
Kazi inayoendelea20 wafers
Msongamano wa kasoro0.110 /cm²
Uwezo wa mchakato Cpk1.25 · tahadhari
Nje ya viwango (sawa na wafa)0.0 wph
Nguvu ya eneo1339 kW

Mwelekeo

Chipu nzuri zilizotoka: — /h250000

Sampuli ya SPC (mkengeuko wa CD)

Sampuli ya SPC (mkengeuko wa CD): 0 ⚑+3σ−3σ

Matukio ya mgogoro

Kiwango 1 · Kupotoka kwa chembe

Zamu ya kawaida kwenye laini ya chipu za simu. Mahali fulani juu ya eneo, kichujio cha dari kinakaribia kushindwa. Weka chumba safi ndani ya daraja, linda mavuno — na usiache feni kwa kasi kamili kwa muda mrefu kuliko inavyohitajika.

  • Daraja la ISO limerudi ≤ 3.6 mwishoni
  • Kamwe zaidi ya daraja 4.55 baada ya saa ya kwanza
  • Wastani wa mavuno ≥ 87 % katika saa za kwanza za tukio
  • Wastani wa nguvu ya eneo ≤ kW 1,380 katika nusu ya pili

Kiwango 2 · Skana kuharibika

Eneo linafanya kazi kwa joto kwa uanzishaji wa wafa 38 kwa saa. Skana tatu zinakaribia kuharibika kwa wakati mmoja. Zuia foleni isilipuke ukizirudisha, na bado utoe chipu nzuri.

  • WIP ≤ wafa 60 mwishoni
  • Muda wa mzunguko hauzidi kamwe saa 3.5 baada ya hitilafu (dirisha la muda wa foleni)
  • Angalau chipu nzuri 900,000 ndani ya saa 48
  • Achilia angalau uanzishaji wa wafa 1,600 ndani ya saa 48 (mpango wa uanzishaji: 34 kwa saa)

Kiwango 3 · Mpotoko wa mapishi

Toleo jipya la mapishi liliwashwa jana usiku. Hakuna anayejua bado kwamba linabadilisha polepole kipimo muhimu. Tazama chati ya SPC: gundua mpotoko na urudishe nyuma kabla wafa hazijatoka nje ya viwango.

  • Upeo wa wafa 12 sawa nje ya viwango kwa jumla
  • Cpk ≥ 1.2 mwishoni
  • Angalau chipu nzuri 620,000

Kiwango 2 · Kupanda kwa bidhaa mpya

Chipu kubwa ya kasi inaingia kwenye uzalishaji na mchakato ambao haujakomaa: msongamano wa kasoro ni mkubwa na chipu ya mm² 600 haina huruma. Laini inapakiwa kwa uanzishaji wa wafa 42 kwa saa. Una siku 14. Sawazisha uzalishaji wa leo na kujifunza kwa kesho.

  • Msongamano wa kasoro ≤ 0.08 /cm² siku ya 14
  • Angalau chipu nzuri 660,000 ndani ya siku 14

Msingi — modeli iliyo nyuma ya namba

Kila uhusiano ambao kiigaji kinatumia, pamoja na chanzo chake. Viwango vilivyowekwa alama kama dhana ni urekebishaji wa mfano.

Hali za vifaa hufuata SEMI E10: uzalishaji, kusubiri, uhandisi, kusimama kulikopangwa na kusikopangwa.
Availability = up tools / 8 · Utilization = productive tool-hours / total[1]
Zana hushindwa kwa nasibu kwa muda wa kushindwa wa kielelezo; matengenezo husubiri fundi aliye huru.
P(fail in Δt) = 1 − e^(−Δt/MTBF), MTBF = 250 h; repair ~ Exp(mean 6 h) once a technician is free[17][1]Dhana: ukubwa (MTBF, viwango vya uzalishaji, k, τ) ni urekebishaji wa mfano, si data kutoka kiwanda halisi.
Sheria ya Little inaunganisha kazi inayoendelea, uzalishaji na muda wa mzunguko.
CT = WIP / TH = T0 + queue / TH, T0 = 1 h[6][5]
Katika mstari thabiti, kiasi kinachotoka ni sawa na kiwango cha kuachilia, kwa hivyo uanzishaji wa wafa usioachiliwa ni wafa ambayo haitatoka kamwe. Wafa zinazosubiri muda mrefu mno kati ya hatua huvunja dirisha la muda wa foleni.
TH = release rate while u < 1 ⇒ wafers out ≈ Σ starts; queue wait = CT − T0 = queue / TH ≤ queue-time window (3.5 h CT in semi-tool-crash)[5][16]Dhana: kikomo cha muda wa mzunguko cha saa 3.5 kinasimama badala ya dirisha la muda wa foleni; madirisha halisi huwekwa hatua kwa hatua na uhandisi wa mchakato, na wafa zinazoyavunja kwa kawaida hutupwa.
Ukadiriaji wa Kingman: muda wa foleni hukua kama u/(1−u) — hulipuka matumizi yanapokaribia 100 %.
CTq ≈ ((ca² + ce²)/2) · (u/(1−u)) · te[5]Imeonyeshwa kwa ajili ya uelewa: foleni ya kiigaji hutokana na kufika kwa nasibu na uwezo wa nasibu badala ya fomula hii.
Kikomo cha daraja la ISO 14644-1 kwa chembe za ukubwa D; kwa 0.1 µm daraja ni logarithmu ya msongamano.
Cn = 10^N · (0.1/D)^2.08 ⇒ N = log10(C≥0.1µm)[2]
Chumba kilichochanganywa vizuri: msongamano = uzalishaji ÷ (mabadiliko ya hewa × ujazo × ufanisi wa kichujio).
C = G / (ACH · V · η)[13][11]Dhana: ukubwa (MTBF, viwango vya uzalishaji, k, τ) ni urekebishaji wa mfano, si data kutoka kiwanda halisi.
Sheria ya ukaribu ya feni: nguvu hupanda kwa mchemraba wa kasi ya feni.
P_fan = P_max · (speed)³[10]
Mavuno ya binomial hasi: kasoro hukusanyika, kwa hivyo mavuno hushuka polepole kuliko modeli ya Poisson inavyotabiri.
Y = (1 + A·D/α)^(−α), α = 2 (α→∞: Y = e^(−A·D))[3][4][15][14]
Kujifunza mavuno: msongamano wa kasoro hupungua kuelekea kiwango kilichokomaa muda wa uhandisi unapotumika.
D(t+Δt) = D∞ + (D − D∞)·e^(−Δt/τ), τ = 120 h · (0.10 / engineering share)[15][18]Dhana: τ imebanwa kwa muda takriban mara 100 ikilinganishwa na viwango vya kujifunza vya sekta vilivyoripotiwa (4–6.5 % kwa mwezi, Leachman) ili tukio la siku 14 lionyeshe athari.
Chembe zinazotua kwenye wafa huongeza kasoro hatari kulingana na msongamano wa hewa.
D_total = D_learn + k · C, k = 4·10⁻⁶ cm⁻² per particle/m³Dhana: kiwango cha mfano — viwanda halisi hurekebisha viwango vya kasoro hatari kutokana na data zao za ukaguzi.
Mavuno ya kigezo: sehemu ya mchakato wa kawaida inayoangukia ndani ya mipaka ya viwango; Cpk hupima nafasi.
Y_param = Φ((USL−μ)/σ) − Φ((LSL−μ)/σ), Cpk = min(USL−μ, μ−LSL)/(3σ)[7][8][19]
SPC: wastani wa sampuli n, ikiwa na mipaka ya udhibiti ya ±3σ/√n na kanuni za kanda.
x̄ ~ N(μ, σ/√n), control limits ±3σ/√n; zone rules (2 of 3 beyond 2σ, 4 of 5 beyond 1σ, 8 on one side)[8][7][12]
Viwango vingine vya uendeshaji vinavyotumiwa na modeli.
8 scanners × 6 wafer-starts/h · metrology −0.5 % capacity per sampled wafer/h · rollback: 2 h at half capacity + 4 wafer-equivalents reworked · drift 0.25 nm/h · crash repair 18 technician-hours · leak crew +2 people for 3 h · tools 150 kW busy / 60 kW idle, fans 150 kW at 100 %Dhana: ukubwa (MTBF, viwango vya uzalishaji, k, τ) ni urekebishaji wa mfano, si data kutoka kiwanda halisi.
Idadi ghafi ya chipu kwa kila wafa ya mm 300 kwa chipu yenye eneo A.
DPW = π·d²/(4A) − π·d/√(2A), d = 300 mm[9]

Nasibu: jenereta ya mulberry32 yenye mbegu; mgawanyo unaotumika — sawa, kielelezo (CDF kinyume), kawaida (Box–Muller), Poisson (Knuth). Mbegu inaonyeshwa na inaweza kushirikiwa.

Vyanzo

  1. SEMI E10 — Specification for Definition and Measurement of Equipment Reliability, Availability, and Maintainability (RAM) and Utilization — SEMI
  2. ISO 14644-1:2015 Cleanrooms and associated controlled environments — Part 1: Classification of air cleanliness by particle concentration — ISO, 2015
  3. C. H. Stapper, F. M. Armstrong, K. Saji — Integrated circuit yield statistics — Proceedings of the IEEE 71(4), 1983
  4. J. A. Cunningham — The use and evaluation of yield models in integrated circuit manufacturing — IEEE Trans. Semiconductor Manufacturing 3(2), 1990
  5. W. J. Hopp, M. L. Spearman — Factory Physics (3rd ed.), ch. 7–8: Little’s law, Kingman (VUT) equation — Waveland Press, 2008
  6. J. D. C. Little — A Proof for the Queuing Formula L = λW — Operations Research 9(3), 1961
  7. D. C. Montgomery — Introduction to Statistical Quality Control (x̄ charts, process capability Cpk) — Wiley, 2019
  8. NIST/SEMATECH e-Handbook of Statistical Methods — 6.3 Univariate and Multivariate Control Charts; 6.1.6 Process capability — NIST
  9. Dies-per-wafer estimate DPW = πd²/(4S) − πd/√(2S) (de Vries, “Investigation of gross die per wafer formulas”, IEEE TSM 18(1)) — IEEE, 2005
  10. Fan affinity laws: flow ∝ speed, pressure ∝ speed², power ∝ speed³ — U.S. DOE — Improving Fan System Performance: A Sourcebook for Industry
  11. EN 1822-1:2019 High efficiency air filters (EPA, HEPA and ULPA) — classification (U15 ≥ 99.9995 % at MPPS) — CEN, 2019
  12. Western Electric Statistical Quality Control Handbook (1956) — zone rules for control charts — Western Electric / NIST e-Handbook 6.3.2
  13. W. Whyte — Cleanroom Technology: Fundamentals of Design, Testing and Operation (2nd ed.), ch. on dispersion of particles from people; well-mixed room dilution equation — Wiley, 2010
  14. Yu. I. Bogdanov, N. A. Bogdanova, V. L. Dshkhunyan — Statistical Yield Modeling for IC Manufacture: Hierarchical Fault Distributions (§2 Compound Poisson distribution, after Eq. (17), p. 4 of the arXiv PDF — large-area clustering negative binomial model: the cluster parameter’s “typical values approximately range from 0.3 to 7”) — arXiv physics/0303039, 2003
  15. R. C. Leachman — Yield Modeling and Analysis (Poisson, Murphy, Seeds, negative-binomial models; §8: SMLY survey with C. N. Berglund for International SEMATECH, 2002–03 — yield loss fitted as YL(t) = YL(0)·e^(−λt), Table 2 averages 4.4 / 4.0 / 6.5 %/month at 350 / 250 / 180 nm) — UC Berkeley, IEOR 130 course notes (unpublished), 2014
  16. A. Klemmt, L. Mönch — Scheduling jobs with time constraints between consecutive process steps in semiconductor manufacturing (time windows set by process engineering against native oxidation and contamination; jobs that violate them are scrapped) — Proceedings of the 2012 Winter Simulation Conference, 2012
  17. NIST/SEMATECH e-Handbook of Statistical Methods — 8.1.6.1 Exponential distribution (constant failure rate) — NIST
  18. C. Weber — Yield learning and the sources of profitability in semiconductor manufacturing and process development — IEEE Trans. Semiconductor Manufacturing 17(4), 2004
  19. M. Abramowitz, I. Stegun — Handbook of Mathematical Functions, 26.2.17 — NBS, 1964

Nani hufanya kazi hii kama taaluma

Modeli ya kielimu — si kwa maamuzi ya uendeshaji. Vituo halisi hurekebisha kila kiwango kulingana na vifaa na data zao.