We buy good boards! (Improve yield from design to production) Christophe LOTZ ASTER Technologies IEEE 8 th International.

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Presentation transcript:

We buy good boards! (Improve yield from design to production) Christophe LOTZ ASTER Technologies IEEE 8 th International Board Test Workshop

2 Content Introduction Yield improvements Defect prevention vs. Defect detection Test Coverage vs. Test Efficiency Production model Technologies convergence Coverage Analysis + Traceability & Quality tools = Test Innovation Conclusion

3 The world changes Electronic design and production changes:  Functional complexity of electronic boards.  Staggering board density.  Outsourcing of board production. Block 1 Block 2 Block 3 Non-functional channels We buy good boards SMD, fine pitch, BGA, buried via

4 Yield improvements Defect Prevention Defect Detection For a lot of people, Quality is costly. However, Non-Quality can be fatal. When it is impossible to reduce the task, it is always possible to reuse the results for other purpose: i.e. Test for Designability, Production line optimization, Repair Cycle, Product life… Combine Design Re-Use with Test Re-Use…

5 Defect prevention Design Flow Electrical DfT rules checking from schematic. Probe optimization from schematic. Probe placement – Mechanical DfT rules. DfM – Design for Manufacturing. Coverage estimation –Inspection: AOI, AXI –Structural test: ICT,FPT,MDA,BST –Functional test: In-System test, Emulation… Lack of automation/understanding between design and production center (The WALL)!

6 Manufacturing flow Assembly machine –Feeder control/supply chain management, –Passive measurement during placement. Traceability tools –Work In Process, –Box Building. Repair station –CAD data, –Fault ticket, –Diagnosis. –Defect occurrence/re-occurrence Defect Prevention Quality System must be able to report the amount of defects by partnumber

7 Defect Detection Insufficient Excess Cold Solder Marginal Joints Voids Polarity (PCAP) Missing Gross Shorts Lifted Leads Bent Leads Extra Part Bridging Tombstone Misaligned Polarity Shorts Open Inverted Wrong Part Dead Part Bad Part In-System Programming Functionally Bad Short/Open on PCB    AOI In-Circuit  X-Ray Solder Material Placement At-speed memory tests At-speed interconnect Fault Insertion Gate level diagnosis JTAG (unpowered)

8 Defect Detection MPSPPVSPCOLA/SOQPCOLA/SOQ/FAIM MaterialValueCorrect Live PlacementPresenceCorrect Live PolarityOrientation Solder Short Open Quality Function Feature At-Speed In Parallel Measurements

9 One coin/two sides: Defect  Coverage Drill-down on flows for more defect categories Defect Detection FunctionManufactureDesign Soldering Place components Buy Materials (Supply chain) OrientationPresence MPS, PTC, PPVS, PCOLA/SOQ PCOLA/SOQ/FAIM…

10 Demonstration using an absurd example Board - 4 components: 3 resistors, 1 BGA. The 3 resistors are measured with very high accuracy. No test on the BGA. Is the board test score really 75%? 3 resistors / 4 components We need something to weight the coverage… It must be credible, easy to update to reflect growing electronics complexity. Test Coverage

11 Test Efficiency For each category (MPS) of defects (D), we associate the corresponding coverage (C). The test efficiency is based on a coverage balanced by the defects opportunities. DfDf CfCf  D M +  D P +  D S  D M  C M +  D P  C P +  D S  C S We need a better coverage where there are more defect opportunities! Effectiveness =

12 Coverage Material=0%, Placement=100%, Solder=100% Massive production: Material=2PPM, Placement=10PPM, Solder=10PPM Test efficiency=90.9% High mix: Material=15PPM, Placement=10PPM, Solder=15PPM Test efficiency=60.5% Test Efficiency Everything is relative.

13 DPMO Escape rate IPC How to know your defect universe? Average number: It is better than nothing as it make possible to differentiate a resistor from an IC. – – DPMO collected from the real production line –Placement defects and soldering defects by package. –Material defects by partnumber. Defect universe

14 Production model Summarize the coverage in a limited set of numbers that will guide the test strategy choice. The “Escape” is an effective way to measure the manufacturing quality. Test First Pass Yield Fall-Off Rate Pass Fail Good Bad Good Bad Escape False reject Products shipped Products repaired Yield

15 Design re-use is widely accepted throughout the electronics industry. Design | test specification | test development | quality management are isolated in separated silos. Limited data exchange between silos. It is time for test-reuse and technologies convergence. It increases the test value. It decreases the test cost. Technologies convergence

16 Functional coverage could be managed as described in BTW06 paper. By Declaration Functional test Schematic and layout viewers used to simplify coverage declaration.

17 By Inheritance Functional test Recognition of pre-analyzed modules with corresponding coverage Derivation and accumulation for the new design.

18 For a complex board, it represents 3 to 5 days work to analyze the functional coverage if nothing has been prepared from design flow. Benefits: Get the overall coverage (inspection + structural + functional), Identify overlapping (potential optimization), Identify lack of coverage (Failure Mode and Effects Analysis). Functional test Tested?

19 Functional test Functional Test coverage tool used as functional test specification tool. –Define test strategy early in the design flow. –Identify unique test contribution. –Avoid un-required overlapping. Functional Blocks recognition make possible to develop an Automatic Functional Test Generator. –Automate test development and coverage analysis in high-hierarchical design flow. –Integrate Designer knowledge for repair purpose. Test Innovation

20 Test line Test coverage results re-used in functional test repair station. –The Pass tests tell us which defects are not on the board. –The Fail tests tell us which defects could be on the board. Combined with historical data in order to guide diagnosis to the most probable source of defect. Test Innovation Coverage Database

21 Dynamic test program optimization driven by Quality management tool. When the test is the bottleneck of the production: The Quality Management system is collecting DMPO in real time. Defect profile is used to tune the assembly line. According to the defect profile, the test program is dynamically optimized. Test Innovation No need to maintain test on defect that no longer occurs !

22 Conclusion From design, during production and in a more general way, through the whole product life cycle, coverage estimation permits the test process to be optimized. By deploying various testers in the best order, at the best time, with controlled levels of redundancy, costs can be reduced and quality levels raised. The economic challenges are critical: the tools to meet them are available.