Computerized Repairable Inventory Management with. Reliability Growth and System Installations Increase

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1 Because Technology Never Sops 1 Compuerized Repairable Invenory Managemen wih Reliabiliy Growh and Sysem Insallaions Increase Jin Tongdan, Ph.D. Teradyne, Inc., Boson When: May 8, 2006 Where: Texas A&M Inernaional Universiy (Noe: Dr. Jin curren is a faculy in TAMIU from 9/1/2006)

2 Wha are Repairable Sysems/Producs 2 1. Sysem can be fixed during is lifeime 2. Capial inensive and long lifeime 3. Diagnosic ools, mainenance and uilizaion 4. PM and reliabiliy growh merics

3 Challenge Yourself, Drive Produc Growh 3 GROWING The receip for success in semiconducor indusry

4 4 Oulines ATE and Semiconducor Indusry Overview ATE Reliabiliy Growh Model Defecive Module Repair Time Esimae Repairable Invenory Service Conroller Conclusions Noe: ATE= Auomaic Tes Equipmen

5 Worldwide ATE Marke Trend 5 World populaion=6 billion You conribue= 38 US$ (or 304 RMB/year) Source:

6 Who are he Players in ATE 6 YEW 12% NPTes 10% Oher 5.6% LTX 7% Credence 6% Teradyne 30% 2004 Prime Research Group Reproducion prohibied Preliminary Agilen 19% Advanes 11%

7 Who Need ATE Sysems? 7 Lowering he cos of capaciy

8 Semiconducor Manufacuring Process 8 ATE Source: From Young Soon Song e. al. Semiconducor elecronics design projec.

9 Semiconducor Manufacuring Process 9 Fundamenal Processing Seps 1.Silicon Manufacuring a) Czochralski mehod. b) Wafer Manufacuring c) Crysal srucure 2.Phoolihography a) Phooresiss b) Phoomask and Reicles c) Paerning Source: From Young Soon Song e. al. Semiconducor elecronics design projec.

10 Semiconducor Manufacuring Process (cn d) 10 3.Oxide Growh & Removal a) Oxide Growh & Deposiion b) Oxide Removal c) Oher effecs d) Local Oxidaion 4. Diffusion & Ion Implanaion a) Diffusion b) Oher effecs c) Ion Implanaion Source: From Young Soon Song e. al. Semiconducor elecronics design projec.

11 ATE Semies Marke Segmens 11 Mass Sorage Daacom Compuing Microprocessor Chipses Graphics Nework Processors HSM Disk Drive Read Channels Disk Drive SOC SERDES/SONET 10/100/1000BaseT Infiniband Wireless / RF Mobile/Cordless Phone WLAN, Blueooh Pagers/PDA Rx/TX GPS Sysems Digial Saellie Rx Cable Tuners Broadband Consumer Baseband processors Cable Modem xdsl Se-op box Converers DVD R/W CODECs Microconrollers Prinhead drivers Baery managemen Servo/moor drivers Auomoive conrol Smar Power Smar cards Source: ASE Inegraion Meeing, July 15, 2004, San Jose, CA

12 Auomaic Tes Equipmen 12 Mainframe Teshaed DIB Cover Dock Crl ATE Cos: 1~3 million US$ PCB Module: 30,00 ~ 100,000 US$ Useful Lifeime: 5 o 10 years Sysem MTBF: 1,500 o 3,000 hours Module MTBF: 40,000-60,00 hours PCB Module Insrumenaions: High-speed digial Analog DC Memory

13 ATE Operaion Principle 13 Square waves or arbirary analog wave Square waves or arbirary analog wave Source:

14 Two Facors for Repairable Invenory 14 1.Sysem and insrumen reliabiliy growh - failure inensiy rae reduced per sysem 2. Expansion of he sysem insallaions - oal failure quaniy may increase

15 Bahub Failure Rae Curve 15 fauls per uni ime Source: hp://

16 MTBF and Insallaions Impac Field Reurns Failures Per Week Failure Reurns Per Week wih Differen Syem Insallaion Rae and MTBF Insall 10 sys/wk, MTBF=1500 Failures=58 Insall 10 sys/wk, MTBF=2500 Insall 5 sys/wk, MTBF=1500 Failures=39 Failures=25 Week No.

17 Benefi of High MTBF o Invenory High MTBF means cusomer saisfacion 2. More han 31 million$ holding cos (1500 vs 2500 hrs) 3. Less repair faciliy and logisic coss 4. Lower backorders and quick response

18 Exising Research Work Zamperini, M., Freimer, M. A Simulaion Analysis of he Vari- Merics Repairable Invenory Opimizaion Procedure for he U.S. Coasal Guard, Proceedings of 2005 Winer Simulaion Conference. 2. Guide, V., Srivasava, R., Invied review for repairable invenory heory: models and applicaions, European Journal of Operaions Research, vol. 102, Kim, J. e. al., Opimal algorihm o deermine he spare invenory level for a repairable-iem invenory sysem, Compuers Operaions Research, vol. 23, Jung, W., Recoverable invenory sysems wih ime-varying demand, Producion and Invenory Managemen Journal, vol. 34, Wasserman, G., Lamberson, L., Spares Provisioning Under Reliabiliy Growh, Logisics Specrum Winer, 1992

19 Road Map o Manage ATE Repairable Invenory 19 Reliabiliy growh es and esimae sysem/produc Shipmen Failure inensiy µ() Sysem insalled N() or E[N()] & Var(N()) Failures δ (T) or E[ δ (T)] & Var(δ (T)) Rae of reurn φ (T)=δ (T)/T Tune m Service Index Pr{γ m φ (T)} R Defecive module Transiion ime Defecive module Repair ime Transiion ime ~Normal FM Pareo & repair ime r or E[ r ] & Var( r ) Defecive ime d = + r or E[ d ] & Var( d ) Repair rae γ m =m/ d

20 Reliabiliy Growh vs. Degradaion 20 Sysem 1 Sysem 2 Sysem 3 X X X X X X X X X X

21 Crown Reliabiliy Growh Esimae 21 Fauls Per Uni Time Failure Inensiy Rae wih various Bea bea=1 bea=1.5 bea=0.5 alpha=1 for all lines u( ) β Time () = αβ

22 Reliabiliy Growh Tes and Esimae 22 Tes Name Crow/AMSSA Laplace Tes Pairwise Comparison Non-parameric Tes (PCNT) Lewis-Robinson Tes (LRT) Tes for Wha NHPP v. HPP NHPP v. HPP Renew vs. Non-Renew Renew vs. Non-Renew Tes Saisics Chi-square Normal Normal Normal HPP= Homogeneous Poisson Process NHPP= Non-homogenous Poisson Process Renew= Renewal Process References: 1). P. Wang, T. Jin, D. Coi, Repairable Sysem Reliabiliy: Planning and Assessmen Tools, Qualiy and Reliabiliy Engineering Cener Repor, QRE repor number 99-2, Ocober 1999, Rugers Universiy, New Jersey, USA 2). T. Jin, H. Liao, Z. Xiong, Compuerized Reparable Invenory Managemen wih Reliabiliy Growh and Increased Produc Populaion, submied o CASE 2006, Oc 8-9, Shanghai, China

23 Tes Reliabiliy Growh Trend Tes Flow Char 23 Crow/AMSSA Laplace Tes Daa Inpu Sar PCNT LR Tes Trend Tes No Goodness-fi-Tes Yes Yes NHPP HPP No Renew Process

24 Renewal Process vs. HPP 24 Renewal processes: The renewal processes are used o model independen idenically disribued occurrences. Definiion 3.7 Le Y1,Y2,Y3,... be i.i.d. and posiive sochasic variables, defining a new random variable n J n = Y i i= 1 And he renewal inerval is [J n, J n+1 ]. Then he random X given by X = max{ n : J n } HPP processes: if each Y1,Y2,Y3,... is i.i.d. and exponenially disribued. Then i is HPP

25 Crow Model Parameers Esimaion Tool 25 Trend Tes Parameer Esimaion

26 26 Single Sysem Failure Reurn Model β α τ τ ) ( ) ( ) ( 0 T d u T m T + = = + + β β α τ αβτ τ τ d d u m = = = ) ( ) ( 1. Failure Inensiy (fauls per uni ime) a ime 2. Cumulaive Failures a ime 3. Cumulaive Failures a ime +T 4. Cumulaive Failures beween [, +T] 1 ) ( = β αβ u [ ] β β α T m T m + = + ) ( ) ( ) (

27 Muliple Sysems - Deerminisic 27 For N muliple sysems, he oal cumulaive Failures beween [, +T] δ ( ; T ) = N = αn ( m( + T ) m( ) ) [ ] β β ( + T ) This means ha given N sysems in he field, he expeced fauls occurred Beween and +T is δ(). The key facor is N is a random variable, no deerminisic

28 Road Map o Manage ATE Repairable Invenory 28 Reliabiliy growh es and esimae sysem/produc Shipmen Failure inensiy µ() Sysem insalled N() or E[N()] & Var(N()) Failures δ (T) or E[ δ (T)] & Var(δ (T)) Rae of reurn φ (T)=δ (T)/T Tune m Service Index Pr{γ m φ (T)} R Defecive module ransi ime Defecive module Repair ime Transi ime ~Normal FM Pareo & repair ime r or E[ r ] & Var( r ) Defecive ime d = + r or E[ d ] & Var( d ) Repair rae γ m =m/ d

29 Failures Considering Insall Base Expansion Demand of A Type of High Speed Digial Tesing Module Monhly Ship Qy Cumulaive Insall Bases Cum Ship Qy Monhly Shipmen Qy Time (Monh)

30 Sysem Insallaion modeling 30 Pr{ N ( ) = n} = ( λ) e n! n λ for n=0, 1, 3,. E[ N ( )] = λ Var ( N ( )) = λ Where: λ= sysem insall rae (e.g. quaniy per uni ime) n = number of sysems insalled by ime

31 31 Muliple Sysems - Sochasic For N() muliple sysems, he oal cumulaive Failures beween [, +T] ( ) [ ] β β α δ T N m T m N T + = + = ) ( ) ( ) ( ) ( ) ( ) ; ( This means ha given N() sysems in he field by ime, he expeced fauls occurred Beween and +T is E[δ(;T)]. ( ) 1 ) ( )] ; ( [ + + = β β αλ δ T T E ( ) 2 2 ) ( )) ; ( ( β β λ α δ T T Var + =

32 Road Map o Manage ATE Repairable Invenory 32 Reliabiliy growh es and esimae sysem/produc Shipmen Failure inensiy µ() Sysem insalled N() or E[N()] & Var(N()) Failures δ (T) or E[ δ (T)] & Var(δ (T)) Rae of reurn φ (T)=δ (T)/T Tune m Service Index Pr{γ m φ (T)} R Defecive module ransi ime Defecive module Repair ime r Transi ime ~Normal FM Pareo & repair ime r or E[ r ] & Var( r ) Defecive ime d = + r or E[ d ] & Var( d ) Repair rae γ m =m/ d

33 Repair and Sock Ceners 33 Memphis Boson Philippines Cosa Rica

34 Repairable Module Cycle Time 34 ATE Sysem in Field Worldwide = Good Par received Defecive Par reurned 1 Good Sock Invenory GCS Inspecion/defecive Invenory 3 Par Tesed/Repaired a Repair Cener (repair ime r ) 2

35 Defecive Module Transiion Time Based on hisorical daa, ransiion ime from differen cusomer sies o he repair cener can generally modeled by normal disribuion. 2. If follows oher ypes of disribuions, i is also applicable. Defecive Module Transiion Time pdf µ σ Time

36 Defecive Module Repair Time r Repair ime r depends on he failure mode. 2. Using weighed average o esimae r µ σ r 2 r = E[ ] = τ E[ w ] r n i= 1 i 2 = Var( ) = τ Var( w r n i= 1 i i i ) Qy PCBA Failure Mode and Repair Time Qy Repair Time Repair ime (minues) 0 Cold Solder Defecive ASICS Bad Relays Corruped EEPROM 0

37 Toal Time in Defecive Saus 37 The oal ime he module in defecive saus include: 1). ransiion ime; and 2) repair imes. Tha is = + d r µ = E [ ] = E[ ] + E[ ] = µ + µ d d r r σ 2 d = Var 2 2 ( d ) = Var( ) + Var( r ) = σ + σ r

38 Road Map o Manage ATE Repairable Invenory 38 Reliabiliy growh es and esimae sysem/produc Shipmen Failure inensiy µ() Sysem insalled N() or E[N()] & Var(N()) Failures δ (T) or E[ δ (T)] & Var(δ (T)) Rae of reurn φ (T)=δ (T)/T Tune m Service Index Pr{γ m φ (T)} R Defecive module ransi ime Defecive module Repair ime Transi ime ~Normal FM Pareo & repair ime r or E[ r ] & Var( r ) Defecive ime d = + r or E[ d ] & Var( d ) Repair rae γ m =m/ d

39 Robus Invenory Service Qualiy Monior 39 Pr m d δ( ) T { γ φ } = Pr = Pr{ δ( ) mt} R m d Where γ m φ = = m d δ ( ; T ) T repair rae under m repair channels failure rae a ime m = number of repair channels R = cusomer saisfacion level (95% or 99% ec)

40 Illusraive Example Repair Channels wih 95% Confidence Level Defecive reurn rae (mean) = 20 /day Var( δ ( ; T )) Var ) ( d m 0 1 Mean of repair 2 ime E[ d 3]=10 days 4 E[ d ]=5 5 days

41 Conclusions A robus invenory conrol model is developed o address reliabiliy growh and he expansion of sysems. 2. A weighed esimae is proposed o compue he repair ime of he defecive module 3. The explici link beween he repair channel and he service index are esablished, based upon which managemen eam can une he service qualiy using he repair resources. 4. Fuure research work can incorporae defecive scrap, muliple repair ceners, and cos analysis ec.

42 42 Thanks Quesions and Commens