Fusion of Ultrasound and X-ray Data for Automatic Inspection of Flip Chip and BGA Solder Joints

1. Fusion of Ultrasound and X-ray Data for Automatic Inspection of Flip Chip and BGA Solder Joints Ryan Yang 27/02/2009

2. Presentation Outline • Introduction • Acoustic Micro Imaging • X-ray Imaging • Image Registration • Image Fusion • Conclusion

3. Introduction • Solder joint reliability is a primary concern in the assembly of all Electronic components and products. • The importance of solder joint reliability became more emphasized in recent years as a result of three factors: • 1) The shift from leaded to lead-free solders in semiconductor industry. • 2) Shrinking in die size as well as solder balls dimension. • 3) The emergence of fine-pitched area array packages that employ hundreds of solder joints for electrical connection.

4. Figure 1: Evolution of Packaging Technology (adapted from Japan Jisso Technology) Introduction

5. Introduction Hidden Solder Joints !?

6. Figure 2a: X-ray image of solder joints Figure 2b: Ultrasound C-scan image of solder joints Introduction • Acoustic Micro Imaging and X-ray imaging are principle Non-Destructive Testing techniques. • Both techniques can penetrate through the component to image the hidden solder joints. • X-ray inspection and AMI are complementary, each technology has distinct discriminating features and is good at inspecting certain defects.

7. Introduction • AMI is an effective approach for detecting gap-type defects due to strong reflections of ultrasound at a solid-air interface. • X-ray inspection is able to identify volumetric defects which are hard to detect by AMI.

8. Introduction • Penetration of AMI through several layers of dissimilar materials is a big challenge for AMI, whereas X-ray penetration is good but without the discrimination accuracy. • Inspection of flip chip and BGA solder joints still remains a significant challenge to current testing techniques • FUSION of ultrasound and X-ray data for flip chip and BGA solder joints provides a novel way to interpret and analyse the image of the solder joints and potentially increases the resolution of very small dimensions

9. Introduction • When two complementary techniques are combined, they could be helpful in reinforcing certain evaluations, improving feature measurement resolution, technique can also applied to other fields. • Combining multiple image modalities to provide a single, enhanced picture is offering an added value and more informative data to the processor in order to developing an automated inspection system. (Smith, 2005) • In future, other techniques such as MRI. Infrared and AFM could be added.

10. Acoustic Micro Imaging • Acoustic Micro Imaging (AMI) is makes use of the properties of ultrasonic waves which range from 5MHz to 400MHz. • Ultrasonic waves are generated by a piezoelectric transducer and propagate through an object. • When the wave travels through the object, it may be scattered, reflected and absorbed with respect to the differences between acoustic properties of materials. Figure 3: Reaction of ultrasound wave in an object (Image adapted from Sonoscan Inc)

11. Figure 4b: Through Transmission Mode Figure 4a: Pulse Echo Mode Acoustic Micro Imaging (Images adapted from Sonoscan Inc) Different imaging modes are used for locating certain defects.

12. Acoustic Micro Imaging Figure 5: AMI images of Flip chip solder joints

13. X-Ray Imaging • X-ray microscope imaging uses electromagnetic radiation in the soft X-ray band to produce images of very small objects. • When X-rays pass through a materials, it experience a variety of scattering interaction. These interactions lead to energy attenuation and the energy is detected by a Charge Coupled Devices (CCD). • X-rays imaging is a contrast imaging technique where high density materials lead to higher attenuation and hence produce darker image than those with less density or thickness.

14. X-Ray Imaging Figure 6: X-ray images of Flip chip and BGA solder joints

15. Image Registration • The essential step in the fusion process is to bring the X-ray and C-scan images into spatial alignment, known as registration. • Image Registration is the process of overlaying two or more images of the same scene taken at different times, different viewpoints or different sensors. • The registration geometrically align two images or transform different set of data into one coordinate system.

16. Image Registration • Registration is have been widely used in: • Medicine • Combining CT, NMR or MRI data • Remote Sensing • Multispectral classification • Environmental monitoring • Change detection • Image mosaicing • Weather forecasting • Computer Vision • Target localization, • automatic quality control • Military • Satelite detection • Map updating

17. Image Registration • Open Source Registration tools • ITK-Insight software consortium • AIR- Roger P. Woods, M.D., UCLA School of Medicine • FLIRT – FMRIB centre, University of Oxford • DROP - Technische Universität München (TUM) , Germany • BunwarpJ - Arganda-Carreras , Universidad Autonoma de Madrid • No pre-processing and mainly developed for biomedical images

18. Image Registration Figure 7: Feature Detection Figure 8: Feature Matching (Images adapted from Zitova,2003 )

19. Image Registration Figure 9: Transformation Model Estimation Figure 10: Image Resampling and Transformation (Images adapted from Zitova,2003 )

20. Image Registration Figure 11: Original Images Figure 12: Processed Images

21. Image Registration • Point based methods and Least Square Approximation • The transformation that aligns the corresponding fiducial points will interpolate the mapping from these points to other points in the view. w= weighting factor X= points of reference image Y= points of sensed image R= rotation t= Translation Figure 13: Measurement for Registration Errors

22. Image Registration • Compute the weighted centroid of the fiducial configuration in each space: • Compute the weighted fiducial covariance matrix:

23. Image Registration • Perform singular value decomposition (SVD) of H • Finally,

24. Image Registration Figure 14: LabVIEW Program for Computing Point Based Method

25. Image Fusion • The term Image Fusion generally implies the intelligent combination of multi-modality sensor imagery for the purpose of providing an enhanced single view of a scene with extended information content. (Smith, 2005) • Fundamental Standard of fusion • The fused image should preserve all salient information of source images. • The fusion process should not introduce any artefacts or inconsistencies into the fused image. • Undesirable features (noise) should be suppressed in the fused image.

26. Image Fusion Table 1: Table of Fusion Method

27. Image Fusion Maximum Amplitude and Weighted Pixel Averaging • Common Fusion Algorithm approaches: • Disadvantages • Also suppresses salient features • Low contrast • ‘washed-out’ appearance • Advantages: • Easy implemented • Fast to execute • Suppressing noise

28. Image Fusion • Multi-Resolution Methods • Extract the salient features at several levels of image decomposition from coarse to fine • Pyramidal Schemes • Gaussian Pyramid • Laplacian Pyramid • Wavelet Schemes • Colour Fusion • Advantages • Produce sharp, high-contrast images • Disadvantages • Reserve unwanted features • Further Assessment is required

29. Image Fusion Pyramidal Schemes R=Reduce E=Expand D=Difference F=Fused C=Combined Figure 15: Generic Pyramidal image fusion scheme (Image adopted from Smith,2005)

30. Image Fusion • Reduce operation: • Expand operation:

31. Image Fusion • Wavelet Schemes • Discrete Wavelet Transform Figure 16b: Wavelet representation of Sinusoidal Wave Figure 16a: Sinusoidal Wave

32. Image Fusion • Rescaling is usually done in power of two Figure 17: Generic Wavelet Fusion Scheme (Image adopted from Smith,2005)

33. Conclusion • Increasing the Solder Joints reliability can increase the product life time and increases customer quality. • Reduces potential warranty costs. • Image fusion provide a new method to keep inspection of hidden solder joints in line with the rapid reduction in component size • Improves the ability to inspect smaller dimensions seen in newer packaging. May also improve the inspection of area array parts such as BGA which contain interposer • Image fusion remains a challenging technology and its application in electronic inspection is less mature and required additional research and assessment

34. References ZHANG, G.M., HARVEY, D.M. and BRADEN, D.R. (2006) “”X-ray Inspection and Acoustic Micro Imaging Applied to Quality Testing of BGA Solder Joints – A Comparative Study”, 2nd GERI Annual Research Symposium GARS 2006, Liverpool, UK, 15th June 2006 KAPUR, A. and et al (2002) “Fusion of Digital Mammography with Ultrasound – A phantom Study”, Proc of SPIE – The international Society of Optical Engineering, 4682, p.526-537 SEMMENS, J.E. (2000) “Flip Chis and Acoustic Micro Imaging: An overview of Past Application, Present Status, and Roadmap for the Future”. Proceedings of ESREF conference, Dresden, Germany, October 2000 ZITOVA, B. and FLUSSER, J. (2003) “Image Registration Methods: A Survey”, Image and Vision Computing vol. 21, p977-1000 SMITH, M.I. andHEATHER, J.P. (2005) “A review of image fusion technology in 2005” Thermosense XXVII. Proceedings of the SPIE, Vol. 5782, pp. 29-45

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