ECE 510 Lecture 15 Manufacturing Test Methods. Glenn Shirley Scott Johnson



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Transcription:

ECE 510 Lecture 15 Manufacturing Test Methods Glenn Shirley Scott Johnson

Manufacturing Test Flow Outline The Ramp. Initial Flow. High-Volume Manufacturing (HVM) Flow. Purpose of Various Test Modules. Monitors: Containing Risk in High-Volume Manufacturing What s Inside a Test Module. Mutual Coverage of Tests and Patterns. Stop-on-Fail (SOF) Figures of Merit from Coverage Metrics Measuring Mutual Coverage with Continue-on-Fail (COF) Data Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 2

Fab: Wafer Fabrication Fab and Assembly/Test Silicon wafers are processed through many steps. The entire process is referred to as wafer fabrication. The factories in which this is done are called Fabs. At the end of fabrication, wafers are tested by e-test which provides the Fab with feedback at the transistor level. The first product-specific test after fabrication is Sort. Sort is done at the wafer level. The primary measure of success of the Fab is the yield at Sort. Assembly/Test Wafers are sent to Assembly factories where they are singulated into individual dies, put into packages and tested. The primary focus of the Test Methodology lectures of the course is on the Test aspects of the Assembly/Test factory. Test Wafer Fabric n Sort (Cold) Assembly Raw Class Burn In Hot Class Cold Class Platform Validation OEM Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 3

HVM Methods Several methods are needed to convert the initial manufacturing process to a high-volume process (HVM) while containing the risks: RCE. Raw Class Elimination. CSE. Cold Socket Elimination. BITR. Burn In Time Reduction. TTR. Test Time Reduction. PVSE. Platform Validation Screen Elimination. These all depend on using data acquired during the early stages of the product ramp. Discovery Technology Target Spec Development Technology Certification Lead Product Qualification Factory Qualification Pilot Manufacturing 1+Mu s 100Ku s 10Ku s 1Ku s 100 s Volume Pre-Silicon Discovery Risk Assessment TV s Data Auto Req ts And plan for Post-Si Test Vehicles Post-Silicon Mfg Validation of Test Process Technology, Xfer, & HVM.» Defect Sensitivity Charact n» Process Sensitivity Charact n» Debug ~ 1-2 Quarters Winter 2013 ECE 510 C. G.Shirley, S. C. Johnson 4

Integrated Circuit Manufacturing Test Initial manufacturing process Low volumes, data-intensive. Wafer Fabric n Sort (Cold) Assembly Raw Class Burn In Hot Class Cold Class Platform Validation OEM High-volume manufacturing process Test steps and test content moved to monitors. TTR Monitor: Some units get full test content applied. Wafer Fabric n Sort (Cold) Assembly Burn In OEM Hot Class Extra content ported from Cold Class Raw Class BI Model Validation Reduced test content. Cold Class CSE Monitor Platform Validation PVSE Monitor Winter 2013 ECE 510 C. G.Shirley, S. C. Johnson 5

Outline Manufacturing Test Flow Purpose of Various Test Modules. Sort, Class, Burn In, Platform Validation. Monitors: Containing Risk in High-Volume Manufacturing What s Inside a Test Module. Mutual Coverage of Tests and Patterns. Stop-on-Fail (SOF) Figures of Merit from Coverage Metrics Measuring Mutual Coverage with Continue-on-Fail (COF) Data Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 6

Done at wafer level. Sort Signal and power environment non-optimal. So timings are loose, etc. Test times are several seconds. Gives feedback to Fab on process health. Screens for gross manufacturing defects. Screens and classifies dies for downstream manufacturing. Screen: Greatly reduces number of defective dies packaged. Classify: eg. Low Isb dies get mobile packages. High Isb dies have different burn in settings. The only cold temperature test socket remaining in the HVM test flow. Cold Class removal is enabled by making Sort more effective at screening cold defects. Wafer Fabric n Sort (Cold) Assembly Raw Class Burn In Hot Class Cold Class Platform Validation OEM Winter 2013 ECE 510 C. G.Shirley, S. C. Johnson 7

Hot Class and Raw Class Guarantees product timing, voltage & thermal specifications at hot corner. Dies passing at worst corner (hot, low Vcc) pass at all lower temperatures and higher voltages except for some specific kinds of cold defects. Test times are several seconds. Classifies units by speed (speed binning). Screens defects including: assembly, hot temperature sensitive, latent reliability defects activated by B/I. Gives feedback to Assembly on Assembly Factory process health. Pre-Burn-In Class separates Assembly and Fab latent reliability defects. Raw Class Elimination (RCE) occurs when product has been validated to match burn in models. Thereafter, defect density measured at Sort suffices. ATE testers used for Raw Class are released to serve as Hot Class testers. Wafer Fabric n Sort (Cold) Assembly Raw Class Burn In Hot Class Cold Class Platform Validation OEM Winter 2013 ECE 510 C. G.Shirley, S. C. Johnson 8

Burn In Operates units at high voltage and temperature so that latent reliability defects may be activated and so screened by subsequent Class tests. Burn in times range from about an hour to several hours. Many (100 s) of units are stressed in parallel in burn in ovens. Load/unload times are key factors in the efficiency of the process. Validation of the stress is important for example ensuring that the voltage is really being applied. Burn-In time reduction (BITR) is driven by Fab process killer defect density reduction, which also reduces LRD density. Carefully(!) putting brief high voltage stresses into Sort and Class. Test-during-burn-in (TDBI) is a perennial idea that never works. Wafer Fabric n Sort (Cold) Assembly Raw Class Burn In Hot Class Cold Class Platform Validation OEM Winter 2013 ECE 510 C. G.Shirley, S. C. Johnson 9

Cold Class Guarantees product timing, voltage & thermal specs at cold corner. Some Fab defects fail at the cold corner, rather than at the hot corner. Caused by specific kinds of defects ( salicide ). Uses expensive ATE equipment. Test times are several seconds. Provides two kinds of feedback: Isolates cold defects for Fab, so that Fab can can eliminate them. Identifies tests that can be moved to Sort to screen cold defects there. Cold Socket Elimination (CSE) must occur before the ramp reaches half the planned volume so testers used for Cold Class can be used for Hot Class. Wafer Fabric n Sort (Cold) Assembly Raw Class Burn In Hot Class Cold Class Platform Validation OEM Winter 2013 ECE 510 C. G.Shirley, S. C. Johnson 10

Platform Validation Closely matches end-use conditions. It is an end-use platform (eg. PC) with user-like software running. Heavily engineered to work in a factory. Robot handling, make/break contact sockets, etc. Test times are 10 s of minutes. An in-factory measure of expected customer production-line failure rates. Finds failing patterns missing in upstream test programs. Provides an initial use-like screen, but test times are long (10 s of minutes) so must be quickly moved to monitor status. Wafer Fabric n Sort (Cold) Assembly Raw Class Burn In Hot Class Cold Class Platform Validation OEM Winter 2013 ECE 510 C. G.Shirley, S. C. Johnson 11

Outline Manufacturing Test Flow Purpose of Various Test Modules. Monitors: Containing Risk in High-Volume Manufacturing Statistical Design of Monitors. What s Inside a Test Module. Mutual Coverage of Tests and Patterns. Stop-on-Fail (SOF) Figures of Merit from Coverage Metrics Measuring Mutual Coverage with Continue-on-Fail (COF) Data Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 12

Monitors The HVM process requires monitors which sample the volume. Benefit: Greatly increased efficiency. Risk: Whenever a screen is replaced by a monitor there are producer and customer risks. Sampling plans for monitors must be designed to meet specific producer and customer risk parameters. Example: What is the escape risk for a sudden increase in proportion defective? TTR Monitor: Some units get full test content applied. Wafer Fabric n Sort (Cold) Assembly Burn In OEM Hot Class Extra content ported from Cold Class Raw Class BI Model Validation Reduced test content. Cold Class CSE Monitor Platform Validation PVSE Monitor Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 13

PV Monitor to CLF Correlation The PV monitor provides an in-factory indicator of customer-perceived failure rates; customer line fallout (CLF). The signal is seen about 1 week before the customer sees it. 2000 1500 Customer Line Fallout DPM 1000 500 PV Monitor 0 7 11 15 19 23 27 31 35 Workweek Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 14

Producer Example Fraction defective: p Sample Plan: Sample size N Customer Pass Policy: Criteria p Goal Pass p > Goal Fail Test Valid failures Analysis FI/FA Data: Failure Count f Use Rule Reject Decide Action Accept No Action Producer Oriented Process Fix Customer Oriented Containment, Notification Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 15

Risk Matrix For a specific hypothetical value of p (percent defective). Decision by Rule Accept Reject The Truth (Known only to God) p Goal Correct Probability = (1 ) Producer Risk Alpha Risk Type I Error Probability = p > Goal Customer Risk Beta Risk Type II Error Probability = Correct Probability = (1- ) Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 16

Operating Characteristic (OC) Every rule with an Accept or Reject result has an operating characteristic (OC) curve. The OC curve is the probability of an Accept result as a function of the fraction of the population, p, that is defective. No matter how complicated the rule is, an OC curve exists. The OC curves for simple rules can be calculated analytically. More complicated rules may require Monte-Carlo simulation. Calculation is simplified because the OC curve is only needed at two particular values of p (AQL and RQL, see below.) Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 17

Example Rules 1 Minimum and Nearly Minimum Sample Size Rules A sample of size N is taken. Assumptions Sample is small compared to total population sampled. Population defect density is uniform. Rule 1a: Accept on 0, Reject on 1 or more. Probability of the Accept decision is the probability of no defects Paccept (1 p) N Rule 1b: Accept on 0 or 1, Reject on 2 or more Probability of the Accept decision is the probability of 0 or 1 defects Paccept (1 p) N p (1 p) Probability of "Accept" P N N 1 0.1 0 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 Accept on 0 OC Curves Accept on 0 or 1 0 0.005 0.01 0.015 0.02 0.025 0.03 Hypothetical Fraction Defective, p N = 200 Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 18

Rule for any sample size. A sample of size N is taken. Assumptions Rule Example Rule 2 Sample is small compared to total population sampled. Population defect density is uniform. For 0, 1, 2,..,f failures in the sample, the decision is Accept. For f + 1or more failures in the sample, the decision is Reject. Probability of no failures in the sample, that is, of the Accept decision is f N! Paccept 1 p p f!( n f )! n 0 N f f BINOMIAL( f, N, p,true) Notes: This rule generalizes Rules 1. The OC Picker Tool tab on the Rel Calculator Excel tool may be used to implement this rule. f = 0, N = 100 f = 1, N = 100 f= 10, N = 1000 f = 100, N = 10000 f =1000, N = 100000... Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 19

Sequential Sampling Example Rule 3 Benefit: Sample size adapts to defectivity. Risk: Can lead to 100% sampling. Assumptions (for this example) Rule f, number of defective units Sample is small compared to total population. See diagram and equations. Usually truncate when sample reaches 3x non-sequential plan. h 2 h 1 Reject Continue Sampling n, number of units sampled x h sn Accept Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 20 r a 2 x h sn 1 1- Probability of "Accept" P 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 p 0 1 0.01 0.02 p 2 0.03 0.04 0.05 Hypothetical Fraction Defective, p k ln h h s 1 2 p2(1 p1) p (1 p ) 1 2 1 ln 1 ln 1 p 1 ln 1 p 2 k k k

Producer and Customer Risks Risk Probability of "Accept" P 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Keep out for acceptable producer risk. Keep out, for acceptable customer risk. 0 0.01 0.02 0.03 0.04 0.05 Risk AQL Hypothetical Fraction Defective, p RQL Corporate Quality Goal Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 21

Producer and Customer Risks Producer requires.. Low risk of rejecting a lot with less than some percent defective, called AQL (Acceptable Quality Level). OC curve outside the green zone meets producer requirements. Customer requires.. Low risk of accepting a lot with more than some percent defective, RQL (Rejectable Quality Level). Notes OC curve outside in the red zone meets customer requirements. AQL < RQL, unless everything is tested. Lot Tolerance Percent Defective (LTPD) is RQL when = 0.1 Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 22

Recipe Determine Customer Risk Policy owned by Q&R and Marketing. Assign RQL = Corporate Quality Goal Choose Beta risk = Standard value, 10%. Determine Producer Risk Policy owned by Manufacturing. Assign AQL (< RQL) = Some fraction, < 1, of RQL. Choose Alpha risk = Standard value, 5%. Choose sampling plan that will Avoid green and red zones in the OC Picker tool, but... Minimizes cost by just grazing the red/green zones. Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 23

Example Only if everything is screened, can AQL=RQL. OC curve becomes a step function as N. AQL 0.009 Alpha 5% RQL 0.011 Beta 10% 1 0.9 0.8 0.7 Probability of "Accept" P 0.6 0.5 0.4 0.3 0.2 0.1 0 0 0.005 0.01 0.015 0.02 Hypothetical Fraction Defective, p 10 100 1000 Accept, f (Reject on f + 1). 1000 10000 100000 SS Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 24

Homework 15.1 Use the OC Picker Tool tab on the Rel Calculator Excel tool. Find the sample size for RQL = 1% and Beta risk of 10% when the producer risk is don t care. This will be the minimum sample size. Find a sampling plan which meets RCL/Beta = 1%/10% and AQL/Alpha = 0.5%/5% requirements. What is the probability of a Reject decision if the population is 1.5% defective and the rule is: Sample 7000 units, accept on 95, reject on 96. Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 25

Outline Manufacturing Test Flow Purpose of Various Test Modules. Monitors: Containing Risk in High-Volume Manufacturing What s Inside a Test Module. Modules Tests Patterns Mutual Coverage of Tests and Patterns. Stop-on-Fail (SOF) Figures of Merit from Coverage Metrics Measuring Mutual Coverage with Continue-on-Fail (COF) Data Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 26

Contents of a Test Module Each manufacturing test module (Sort, Class, PV) contains a sequence of tests of different kinds. The initial tests check for basic electrical continuity and leakage before tests that exercise logic are applied. Logical tests are executed by patterns which are sequences of vectors. Patterns exercise the logic so that faults can be found by unexpected outputs. The Sematech data describes only vectors. There are several kinds of logical tests Stuck-At, Functional, Delay, Iddq A failure occurs at a specific vector. Scan is a Design-for-Test feature for Stuck-At, Delay, and Iddq tests. The IBM ASIC in the Sematech study has a scan DFT feature. Logical tests are done at several environmental conditions Voltage: Nominal/Low/High (Sematech does all 3). What s inside these? Hot Sort Temperature: Cold/Room/Hot (Sematech does hot Sort, RT Class). T0 Class Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 27

Sequence of Modules Wafer Fabric n Hot Sort Assembly T0 Class Burn In (6h) T1Class Test Hierarchy Sequence of Tests inside a Module Power-Up Tests Stuck-At Scan Test Functional Tests Delay Scan Tests Iddq Tests Scan Flush Logical Sequence inside a Test Pattern 1 Vector 1 Vector 2.. Pattern 2 Vector 1 Vector 2.. Pattern 3 Vector 1 Vector 2.. Winter 2013 ECE 510 C. G. Shirley, S. C. Johnson 28