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A novel approach for flip chip solder joint inspection based on pulsed phase thermography
NDT&E International 44 (2011) 484–489
Contents lists available at ScienceDirect
NDT&E International journal homepage: www.elsevier.com/locate/ndteint
A novel approach for flip chip solder joint inspection based on pulsed phase thermography Xiangning Lu a, Guanglan Liao a,n, Zheyu Zha a, Qi Xia a, Tielin Shi b a b
State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei 430074, PR China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 27 September 2010 Received in revised form 19 April 2011 Accepted 4 May 2011 Available online 11 May 2011
Surface mount components have been extensively used in microelectronic packaging. However, it brings great challenge for defect inspection with the development of solder bumps towards ultra-fine pitch and high density. Traditional nondestructive detection methods are insufficient for solder joint assessment due to their own disadvantages. Therefore, it is necessary to explore new methods for solder joint inspection. A novel approach based on the pulsed phase thermography was investigated for identifying the defects of solder joints. In this approach, the test chip was stimulated by a thermal pulse, and the consequent transient response was captured by a commercial thermal imager. The spacial and temporal filtering techniques were adopted to improve the signal to noise ratio. The recorded thermograms were input to an improved median filter with a 5 5 mask, and the temperature evolution of each pixel was extracted and smoothed by the moving average operation. Then the temperature–time curve was fitted with an exponential function. To eliminate emissivity variations and heating non-uniformity, we converted the fitted temperature values in time domain to the phase information in frequency domain using the fast Fourier transform. In low frequency range, the phase– frequency curve of the defect area was differentiated from that of the sound area. The results demonstrate that this approach is effective for identification of the missing bumps, and can be used in the solder joint inspection in high density packaging. & 2011 Elsevier Ltd. All rights reserved.
Keywords: Flip chip Solder joints Inspection Pulsed phase thermography
1. Introduction The miniaturization of electronic devices has driven the extensive use of surface mount components, such as flip chips (FC), ball grid array (BGA) and chip scale packages (CSPs). These components use solder bumps to realize interconnection between chips and substrates or printed wiring board (PWB). The solder bump technology provides decreased package size, greater I/O density and larger speed of signal propagation. It plays an increasingly important role in the electronic packaging process [1,2]. However there exist common manufacturing defects, including open, cracked, missing and misaligned solder bumps, which are hidden between the chip and the substrate. With the trend of solder bumps towards ultra-fine pitch and high density, the inspection of these defects becomes more difficult. Traditional nondestructive detection methods are insufficient for solder joint assessment due to their own disadvantages. For example, electrical testing cannot trace the specific location of the defects [3]. It would pass the partial cracks and cold joints,
n
Corresponding author. Tel.: þ86 27 87793103; fax: þ86 27 87792413. E-mail address: [email protected] (G. Liao).
0963-8695/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.ndteint.2011.05.003
because such defects provide partial or intermittent electrical connections between chip and substrate. Additionally it is operated in a contact way, which may damage the specimen. As the hidden solder joints deny the access of light beams, visual inspection becomes almost infeasible [4]. A novel visual method has been proposed that employs a microscope assisted with a 901 prism, but only the peripheral solder joints can be viewed. It is also subjected to human visual errors. X-ray radiography applies transmission of X-rays through the package. The obtained changes in the amplitude of transmitted energy indicate changes in the material between the transmitter and the receiver. However fine crack and open bump with small air gap, which does not attenuate X- rays, is not detected by this method. X-ray laminography circumvents this problem by focusing the X-ray beam on one plane at a time and slicing the board horizontally [5,6]. It is extremely effective and can detect almost all solder joint defects but the equipment and operation cost is unaffordable. X-ray is also harmful to the human body. Scanning acoustic microscopy (SAM) uses an ultrasound point source to scan across the sample surface. The reflected ultrasonic waves indicate the internal conditions of the component [7,8]. Because of the edge effect and poor resolution, by the SAM method exact inspection of the solder defects is difficult. The requirement of liquid couplant in
X. Lu et al. / NDT&E International 44 (2011) 484–489
SAM detection is also a drawback. Other inspection methods have also been proposed. Liu et al. [9] developed a novel system that employs laser ultrasound and interferometer techniques to monitor the transient out-of-plane displacement response of the electronic package under pulsed laser excitation. It is effective to detect the solder bumps with large diameter and pitch. However, as solder bumps are being developed into small ones with finer pitch and higher density, the transient vibration signals would become too weak. Infrared thermography is also used for solder joint inspection. Chai et al. [10] utilized the hot spots of thermography to detect the solder bumps of high density when an electrical current passes through the daisy chained chips. It is suitable for voids and partial cracks detection. In this paper, a novel approach based on pulsed phase thermography (PPT) was investigated for defect inspection of solder joints. The test chip was excited by a thermal pulse, and the consequent transient response was recorded. The filter technique and fitting operation were used to improve the signal to noise ratio (SNR). Then the thermal data were processed according to the procedure of PPT. The obtained phase–frequency curves were compared, and the missing bumps were identified. The results prove that the approach based on PPT is effective for defect inspection of solder bumps in high density packages.
2. Pulsed phase thermography methodology Infrared thermography is a rapid, non-invasive and full-field technique for nondestructive testing and evaluation. With many achievements in IR instrumentation and image processing techniques, it has been extended far beyond simple hot-spot detection and has become one of the most promising techniques [11,12]. Typically, it is conducted in a passive or active way. Passive thermography measures the temperature distribution of an object and describes the anomalies qualitatively. In active thermography, an external heat source is required to stimulate the specimen for inspection. Depending on the way of thermal excitation, active approach can be divided into pulsed thermography, step heating, lockin thermography and vibrothermography. Pulsed phase thermography is a link between pulsed thermography (PT) and lockin thermography (LT). It combines their advantages since it is as rapid and easy to deploy as PT, and provides the phase delay information through data processing as LT does. The phase is less affected than thermal data by problems such as non-uniform heating, surface emissivity variations and non-planar surfaces [13–15]. PPT is an efficient approach for nondestructive test and evaluation. It consists of heating the
485
specimen briefly and analyzing the phase–frequency characteristics of the recorded thermal data. Fig. 1 illustrates the data processing procedure involved in PPT. After pulsed heating of the sample surface, thermograms are recorded at regular time intervals Dt. The temperature evolution of each pixel (i, j) is extracted as a vector Tij(k) from the thermogram sequence, and processed using discrete Fourier transform as
Fn ¼ Dt
N1 X
Tðk DtÞej2pnk=N ¼ Ren þ j Imn
ð1Þ
k¼0
where N is the number of the thermogram sequence, Dt is the sampling interval, n designates the frequency increment (f ¼ n=ðN DtÞ, n ¼0, 1,y,N), j is an imaginary number and Re and Im are, respectively, the real and the imaginary parts. The amplitude and phase of the transform can be calculated by An ¼ 9Fn 9 ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Re2n þ Im2n and fn ¼ tan1 ðImn =Ren Þ
ð2Þ
When a heating pulse is imposed on the top surface of the flip chip, the thermal front is launched and propagates inside the package by diffusion according to Fourier’s law of diffusion. Because of high thermal conductivity and high diffusivity of the silicon chip materials it requires rapid measurement and data processing, and PPT is a proper technique to fulfill these requirements.
Fig. 2. Experimental setup of solder joint inspection system.
Fig. 1. Data processing procedure involved in pulsed phase thermography.
486
X. Lu et al. / NDT&E International 44 (2011) 484–489
3. Experimental investigation The experimental setup was deployed based on PPT to identify the solder joint defects in surface mounting components. As shown in Fig. 2, a commercial thermal imager of VH 680 (manufactured by InfraTec) was used to measure the transient response of the test chip under thermal excitation of an IR lamp. The thermal imager with a micro-bolometer FPA detector has a temperature resolution better than 80 mK, and its spectral response ranges from 7.5 to
14 mm. The frame size is 640 480 pixels. A microscopic lens with a pixel resolution of 25 mm is equipped for the thermal imager to improve the spatial resolution. The temperature evolutions were observed in both reflection and transmission during the test procedure. However, because of the complex structure of the surface mount components, the observation in transmission is not always possible, and the reflection method with greater resolution is preferred. To verify the feasibility of this approach, a FA10 flip chip package was chosen as the test vehicle. The thickness of the silicon wafer is about 635 mm, and the die is 5.08 mm 5.08 mm. Fig. 3 shows the optical image of the chip. It is a full array with 317 bumps formed in a 18 18 pattern minus the four pairs of corner bumps. The addition of a key bump in the bottom-left corner addresses alignment requirements when bonding to the substrate. The bumps are 135 mm in diameter and spaced with a pitch of 254 mm. Several solder bumps have been removed deliberately in order to introduce the defects of missing bumps when the chip was bonded on the FR4 test board.
4. Results and discussion
Fig. 3. Test vehicle of FA10 200 200 before bonding.
The chip with missing bumps was inspected using this approach. After pulsed thermal excitation by the IR lamp, 600 thermograms were recorded at the frame frequency of 60 Hz. Fig. 4(a) shows the original thermal image captured at 2.5 s. Due to the transparency of the silicon material in the wavelength range longer than 1.1 mm the front side of the silicon chip, where the circuit and solder interconnection are located, can be seen from the back side. However, there were no hot or dark spots presented in the thermal image except for the broken corner of the die. The missing solder bumps cannot be identified in the original thermal image. Therefore, the temperature evolution of each pixel was extracted from the thermogram sequence. Fig. 5(a) shows the
Fig. 4. (a) Original thermal image (t ¼ 2.5 s), (b) fitted thermal image (t ¼ 3.2 s) and (c) phase image (f ¼0.8 Hz).
X. Lu et al. / NDT&E International 44 (2011) 484–489
487
Temperature evolution
Temperature evolution 27
Missing bump
Missing bump Solder bump
26.5
Solder bump
Temperature/¡æ
Temperature/¡æ
26.5
26
26
25.5
25.5 25 25
0
2
4
6
8
10
time/s Fig. 6. Temperature curve after smoothing and fitting.
24.5 0
2
4
6
8
10
time/s Phase−frequency curve 60 40 20
Phase/deg
0 −20 −40 −60 −80 Missing bump
−100
solder bump −120 0
5
10
15 20 Frequency/Hz
25
30
Fig. 5. (a) Original temperature evolution curve and (b) original phase–frequency characteristic.
temperature evolutions in the defect area (missing solder bumps) and sound area (with solder bumps). As can be seen, the temperature values of both the defect and sound areas decay exponentially with the elapse of time. The phase–frequency characteristic obtained using fast Fourier transform (FFT) on the original data is shown in Fig. 5(b). Because of the thermal noise the phase–frequency curve oscillates heavily, which increases the difficulty for defect recognition. To improve SNR, the original data were processed as follows. Firstly, each thermogram was input to an improved median filter with a 5 5 mask to remove the peak noise [16] while preserving the edge information of the metal under solder bumps. Then the temperature evolution of each pixel was extracted from the filtered thermogram sequence and processed using the moving
average operation with a span of 5. Then the peak noise was removed, as shown in Fig. 6. The smoothed data was fitted with an exponential function. The coefficients were stored in a threedimensional matrix to substitute for the thermograms sequence, which reduces the storage space significantly. The fitted temperature curves of the defect area and the sound area are also shown in Fig. 6. The values of all pixels in the flip chip region were processed using the routines. Fig. 4(b) shows the fitted thermal image at 3.2 s. Compared with Fig. 4(a) the image blurring was improved slightly in the fitted thermal image, which implies that we conducted the fitting operation accurately and obtained a better SNR. However, there exist large emissivity variations between metal areas and their gaps, and heating non-uniformities also impede defect recognition. As depicted in Section 2, the phase information can help solve such problems better than thermal data and allows us to probe more deeply under the chip surface. Therefore, the fitted temperature data in time domain was converted into phase information in frequency domain by FFT. The phase–frequency curves are shown in Fig. 7. It was noted that the curves of the missing bump and the reference bump overlapped in the high frequency range. Then the curve section in low frequency was intercepted and amplified. As can be seen in Fig.7(b), the phase of missing bump was differentiated from that of the reference solder bump at low frequency. All the defects of missing bumps in test chip were inspected and compared with the sound area. Fig. 8 shows three sets of the phase comparison between the defect area and the sound area, in which M and S represent the area of the missing bump and the sound area with solder bump, respectively, and the numbers correspond to different positions on the test chip, as illustrated in Fig. 3. We calculated the phase information of all pixels. Fig. 4(c) depicts the phase image at 0.8 Hz, in which the missing solder bumps can be identified more explicitly. The results demonstrate that the PPT method employing phase difference can characterize the defects of missing bumps in high density packages. However the structure of flip chip is rather complex, and the thermal difference between the metal areas and their gaps is much larger than that between the defective solder bumps and the good ones. It increases the difficulty and complexity of test procedure and data processing. High thermal conductivity and thermal diffusivity of silicon material also bring some challenge. These problems are still under investigation.
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X. Lu et al. / NDT&E International 44 (2011) 484–489
Phase−frequency curve
Phase−frequency curve
0 −80
−10
Missing bump solder bump
−20
−80.5 −81 Phase/deg
Phase/deg
−30 −40 −50
−81.5 −82
−60
−82.5
−70 Missing bump −80
−83
solder bump
−90 0
5
10
15 20 Frequency/Hz
25
30
0.8
1
1.2
1.4
1.6
1.8
Frequency/Hz
Fig. 7. Phase–frequency curve based on the fitting data: (a) phase–frequency curve and (b) phase–frequency curve at low frequency.
Fig. 8. Three sets of phase comparison at low frequency.
5. Conclusion
Acknowledgment
In this paper, a nondestructive approach based on the pulsed phase thermography was investigated for defect inspection of solder bumps in high density packages. A flip chip package with artificial defects was chosen as the test vehicle to verify the feasibility of this method. After pulsed thermal excitation, the transient response of the test chip was captured by the thermal imager. However, the phase–frequency curve obtained by FFT from the original data oscillated heavily because of the thermal noise. To improve SNR each thermogram was input to the improved median filter, and the temperature decay of each pixel in the chip region was extracted and smoothed by the moving average operation. Then the temperature data were fitted with an exponential function and transformed to the frequency domain through FFT. The phase–frequency curves were obtained, and the curve of the missing solder bump was differentiated from that of the reference solder bump at low frequency. The phase image shows the defects more explicitly than the thermal images. The results demonstrated that the inspection approach based on PPT is effective for identification of the missing bumps in high density packages.
This research work is supported by National Fundamental Research Program of China (Grant no. 2009CB724204) and National Natural Science Foundation of China (Grant nos. 50975106 and 50805061).
References [1] Oresjo S. New study reveals component defect levels. Circuits Assembly 2002:39–43. [2] Pascariu G, Cronin P, Crowley D. Next generation electronics packaging utilizing flip chip technology. In: Proceedings of the 28th IEEE/CPMT/SEMI international electronics manufacturing technology symposium, July 2003. p. 423–6. [3] Martin PL. Electronic failure analysis handbook, vol. 13. McGraw-Hill; 1999. p. 26–8. [4] Kim T-H, Cho T-H, Moon YS, Park SH. Visual inspection system for the classification of solder joints. Pattern Recognition 1999;32(4):565–75. [5] Kalukin AR, Sankaran V, Chartrand B, Millard DL, Kraft RP, Embrechts MJ. An improved method for inspection of solder joints using X-ray laminography and X-ray microtomography. In: Proceedings of the 19th IEEE/CPMT international electronics manufacturing technology symposium, 14–16 October 1996, Austin, TX, USA. p. 438–45.
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[6] Moore TD, Vanderstraeten D, Forssell PM. Three-dimensional X-ray laminography as a tool for detection and characterization of BGA package defects. IEEE Transactions on Components and Packaging Technologies 2002;25(2):224–9. [7] Zhang G-M, Harvey DM, Braden DR. Microelectronic package characterization using scanning acoustic microscopy. NDT and E International 2007;40(8): 609–17. [8] Kato H, Kobayashi H. Acoustic microscopy of interfacial crack in Sn–Ag–Cu alloy solder joints under shear fatigue testing. Materials Transactions 2008;49(9):2068–75. [9] Liu S, Erdahl D, Ume IC. A novel approach for flip chip solder joint quality inspection: laser ultrasound and interferometer system. IEEE Transactions on Components and Packaging Technologies 2001;24(4):616–24. [10] Chai TC, Wong BS, Bai WM, Trigg A, Lam YKA. Novel defect detection technique using active transient thermography for high density package and interconnections. In: Proceedings of the 53rd electronic components and technology conference, 27–30 May 2003, New Orleans, 2003. p. 920–5.
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[11] Sham FC, Huang YH, Liu L, Chen YS, Hung YY, Lo TY. Computerized tomography technique for reconstruction of obstructed temperature field in infrared thermography. Infrared Physics and Technology 2010;53(1):1–9. [12] Omar MA, Zhou Y. A quantitative review of three flash thermography processing routines. Infrared Physics and Technology 2008;51(4):300–6. [13] Maldague X, Galmiche F, Ziadi A. Advances in pulsed phase thermography. Infrared Physics and Technology 2002;43:175–81. [14] Ibarra-Castanedo C, Gonza´lez DA, Maldague X. Automatic algorithm for quantitative pulsed phase thermography calculations. In: Proceedings of WCNDT on CD, August 30–September 3 2004, Montreal, Quebec, 2004. [15] Rudi Heriansyah, SAR Abu-Bakar. Defect detection in thermal image for nondestructive evaluation of petrochemical equipments. NDT and E International 2009;42(8):729–40. [16] Ben Hamza A, Luque-Escamilla PL, Martinez-Aroza J, Roman-Roldan R. Removing noise and preserving details with relaxed median filter. Journal of Mathematical Imaging and Vision 1999;11(2):161–77.
Contents lists available at ScienceDirect
NDT&E International journal homepage: www.elsevier.com/locate/ndteint
A novel approach for flip chip solder joint inspection based on pulsed phase thermography Xiangning Lu a, Guanglan Liao a,n, Zheyu Zha a, Qi Xia a, Tielin Shi b a b
State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China Wuhan National Laboratory for Optoelectronics, Wuhan, Hubei 430074, PR China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 27 September 2010 Received in revised form 19 April 2011 Accepted 4 May 2011 Available online 11 May 2011
Surface mount components have been extensively used in microelectronic packaging. However, it brings great challenge for defect inspection with the development of solder bumps towards ultra-fine pitch and high density. Traditional nondestructive detection methods are insufficient for solder joint assessment due to their own disadvantages. Therefore, it is necessary to explore new methods for solder joint inspection. A novel approach based on the pulsed phase thermography was investigated for identifying the defects of solder joints. In this approach, the test chip was stimulated by a thermal pulse, and the consequent transient response was captured by a commercial thermal imager. The spacial and temporal filtering techniques were adopted to improve the signal to noise ratio. The recorded thermograms were input to an improved median filter with a 5 5 mask, and the temperature evolution of each pixel was extracted and smoothed by the moving average operation. Then the temperature–time curve was fitted with an exponential function. To eliminate emissivity variations and heating non-uniformity, we converted the fitted temperature values in time domain to the phase information in frequency domain using the fast Fourier transform. In low frequency range, the phase– frequency curve of the defect area was differentiated from that of the sound area. The results demonstrate that this approach is effective for identification of the missing bumps, and can be used in the solder joint inspection in high density packaging. & 2011 Elsevier Ltd. All rights reserved.
Keywords: Flip chip Solder joints Inspection Pulsed phase thermography
1. Introduction The miniaturization of electronic devices has driven the extensive use of surface mount components, such as flip chips (FC), ball grid array (BGA) and chip scale packages (CSPs). These components use solder bumps to realize interconnection between chips and substrates or printed wiring board (PWB). The solder bump technology provides decreased package size, greater I/O density and larger speed of signal propagation. It plays an increasingly important role in the electronic packaging process [1,2]. However there exist common manufacturing defects, including open, cracked, missing and misaligned solder bumps, which are hidden between the chip and the substrate. With the trend of solder bumps towards ultra-fine pitch and high density, the inspection of these defects becomes more difficult. Traditional nondestructive detection methods are insufficient for solder joint assessment due to their own disadvantages. For example, electrical testing cannot trace the specific location of the defects [3]. It would pass the partial cracks and cold joints,
n
Corresponding author. Tel.: þ86 27 87793103; fax: þ86 27 87792413. E-mail address: [email protected] (G. Liao).
0963-8695/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.ndteint.2011.05.003
because such defects provide partial or intermittent electrical connections between chip and substrate. Additionally it is operated in a contact way, which may damage the specimen. As the hidden solder joints deny the access of light beams, visual inspection becomes almost infeasible [4]. A novel visual method has been proposed that employs a microscope assisted with a 901 prism, but only the peripheral solder joints can be viewed. It is also subjected to human visual errors. X-ray radiography applies transmission of X-rays through the package. The obtained changes in the amplitude of transmitted energy indicate changes in the material between the transmitter and the receiver. However fine crack and open bump with small air gap, which does not attenuate X- rays, is not detected by this method. X-ray laminography circumvents this problem by focusing the X-ray beam on one plane at a time and slicing the board horizontally [5,6]. It is extremely effective and can detect almost all solder joint defects but the equipment and operation cost is unaffordable. X-ray is also harmful to the human body. Scanning acoustic microscopy (SAM) uses an ultrasound point source to scan across the sample surface. The reflected ultrasonic waves indicate the internal conditions of the component [7,8]. Because of the edge effect and poor resolution, by the SAM method exact inspection of the solder defects is difficult. The requirement of liquid couplant in
X. Lu et al. / NDT&E International 44 (2011) 484–489
SAM detection is also a drawback. Other inspection methods have also been proposed. Liu et al. [9] developed a novel system that employs laser ultrasound and interferometer techniques to monitor the transient out-of-plane displacement response of the electronic package under pulsed laser excitation. It is effective to detect the solder bumps with large diameter and pitch. However, as solder bumps are being developed into small ones with finer pitch and higher density, the transient vibration signals would become too weak. Infrared thermography is also used for solder joint inspection. Chai et al. [10] utilized the hot spots of thermography to detect the solder bumps of high density when an electrical current passes through the daisy chained chips. It is suitable for voids and partial cracks detection. In this paper, a novel approach based on pulsed phase thermography (PPT) was investigated for defect inspection of solder joints. The test chip was excited by a thermal pulse, and the consequent transient response was recorded. The filter technique and fitting operation were used to improve the signal to noise ratio (SNR). Then the thermal data were processed according to the procedure of PPT. The obtained phase–frequency curves were compared, and the missing bumps were identified. The results prove that the approach based on PPT is effective for defect inspection of solder bumps in high density packages.
2. Pulsed phase thermography methodology Infrared thermography is a rapid, non-invasive and full-field technique for nondestructive testing and evaluation. With many achievements in IR instrumentation and image processing techniques, it has been extended far beyond simple hot-spot detection and has become one of the most promising techniques [11,12]. Typically, it is conducted in a passive or active way. Passive thermography measures the temperature distribution of an object and describes the anomalies qualitatively. In active thermography, an external heat source is required to stimulate the specimen for inspection. Depending on the way of thermal excitation, active approach can be divided into pulsed thermography, step heating, lockin thermography and vibrothermography. Pulsed phase thermography is a link between pulsed thermography (PT) and lockin thermography (LT). It combines their advantages since it is as rapid and easy to deploy as PT, and provides the phase delay information through data processing as LT does. The phase is less affected than thermal data by problems such as non-uniform heating, surface emissivity variations and non-planar surfaces [13–15]. PPT is an efficient approach for nondestructive test and evaluation. It consists of heating the
485
specimen briefly and analyzing the phase–frequency characteristics of the recorded thermal data. Fig. 1 illustrates the data processing procedure involved in PPT. After pulsed heating of the sample surface, thermograms are recorded at regular time intervals Dt. The temperature evolution of each pixel (i, j) is extracted as a vector Tij(k) from the thermogram sequence, and processed using discrete Fourier transform as
Fn ¼ Dt
N1 X
Tðk DtÞej2pnk=N ¼ Ren þ j Imn
ð1Þ
k¼0
where N is the number of the thermogram sequence, Dt is the sampling interval, n designates the frequency increment (f ¼ n=ðN DtÞ, n ¼0, 1,y,N), j is an imaginary number and Re and Im are, respectively, the real and the imaginary parts. The amplitude and phase of the transform can be calculated by An ¼ 9Fn 9 ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Re2n þ Im2n and fn ¼ tan1 ðImn =Ren Þ
ð2Þ
When a heating pulse is imposed on the top surface of the flip chip, the thermal front is launched and propagates inside the package by diffusion according to Fourier’s law of diffusion. Because of high thermal conductivity and high diffusivity of the silicon chip materials it requires rapid measurement and data processing, and PPT is a proper technique to fulfill these requirements.
Fig. 2. Experimental setup of solder joint inspection system.
Fig. 1. Data processing procedure involved in pulsed phase thermography.
486
X. Lu et al. / NDT&E International 44 (2011) 484–489
3. Experimental investigation The experimental setup was deployed based on PPT to identify the solder joint defects in surface mounting components. As shown in Fig. 2, a commercial thermal imager of VH 680 (manufactured by InfraTec) was used to measure the transient response of the test chip under thermal excitation of an IR lamp. The thermal imager with a micro-bolometer FPA detector has a temperature resolution better than 80 mK, and its spectral response ranges from 7.5 to
14 mm. The frame size is 640 480 pixels. A microscopic lens with a pixel resolution of 25 mm is equipped for the thermal imager to improve the spatial resolution. The temperature evolutions were observed in both reflection and transmission during the test procedure. However, because of the complex structure of the surface mount components, the observation in transmission is not always possible, and the reflection method with greater resolution is preferred. To verify the feasibility of this approach, a FA10 flip chip package was chosen as the test vehicle. The thickness of the silicon wafer is about 635 mm, and the die is 5.08 mm 5.08 mm. Fig. 3 shows the optical image of the chip. It is a full array with 317 bumps formed in a 18 18 pattern minus the four pairs of corner bumps. The addition of a key bump in the bottom-left corner addresses alignment requirements when bonding to the substrate. The bumps are 135 mm in diameter and spaced with a pitch of 254 mm. Several solder bumps have been removed deliberately in order to introduce the defects of missing bumps when the chip was bonded on the FR4 test board.
4. Results and discussion
Fig. 3. Test vehicle of FA10 200 200 before bonding.
The chip with missing bumps was inspected using this approach. After pulsed thermal excitation by the IR lamp, 600 thermograms were recorded at the frame frequency of 60 Hz. Fig. 4(a) shows the original thermal image captured at 2.5 s. Due to the transparency of the silicon material in the wavelength range longer than 1.1 mm the front side of the silicon chip, where the circuit and solder interconnection are located, can be seen from the back side. However, there were no hot or dark spots presented in the thermal image except for the broken corner of the die. The missing solder bumps cannot be identified in the original thermal image. Therefore, the temperature evolution of each pixel was extracted from the thermogram sequence. Fig. 5(a) shows the
Fig. 4. (a) Original thermal image (t ¼ 2.5 s), (b) fitted thermal image (t ¼ 3.2 s) and (c) phase image (f ¼0.8 Hz).
X. Lu et al. / NDT&E International 44 (2011) 484–489
487
Temperature evolution
Temperature evolution 27
Missing bump
Missing bump Solder bump
26.5
Solder bump
Temperature/¡æ
Temperature/¡æ
26.5
26
26
25.5
25.5 25 25
0
2
4
6
8
10
time/s Fig. 6. Temperature curve after smoothing and fitting.
24.5 0
2
4
6
8
10
time/s Phase−frequency curve 60 40 20
Phase/deg
0 −20 −40 −60 −80 Missing bump
−100
solder bump −120 0
5
10
15 20 Frequency/Hz
25
30
Fig. 5. (a) Original temperature evolution curve and (b) original phase–frequency characteristic.
temperature evolutions in the defect area (missing solder bumps) and sound area (with solder bumps). As can be seen, the temperature values of both the defect and sound areas decay exponentially with the elapse of time. The phase–frequency characteristic obtained using fast Fourier transform (FFT) on the original data is shown in Fig. 5(b). Because of the thermal noise the phase–frequency curve oscillates heavily, which increases the difficulty for defect recognition. To improve SNR, the original data were processed as follows. Firstly, each thermogram was input to an improved median filter with a 5 5 mask to remove the peak noise [16] while preserving the edge information of the metal under solder bumps. Then the temperature evolution of each pixel was extracted from the filtered thermogram sequence and processed using the moving
average operation with a span of 5. Then the peak noise was removed, as shown in Fig. 6. The smoothed data was fitted with an exponential function. The coefficients were stored in a threedimensional matrix to substitute for the thermograms sequence, which reduces the storage space significantly. The fitted temperature curves of the defect area and the sound area are also shown in Fig. 6. The values of all pixels in the flip chip region were processed using the routines. Fig. 4(b) shows the fitted thermal image at 3.2 s. Compared with Fig. 4(a) the image blurring was improved slightly in the fitted thermal image, which implies that we conducted the fitting operation accurately and obtained a better SNR. However, there exist large emissivity variations between metal areas and their gaps, and heating non-uniformities also impede defect recognition. As depicted in Section 2, the phase information can help solve such problems better than thermal data and allows us to probe more deeply under the chip surface. Therefore, the fitted temperature data in time domain was converted into phase information in frequency domain by FFT. The phase–frequency curves are shown in Fig. 7. It was noted that the curves of the missing bump and the reference bump overlapped in the high frequency range. Then the curve section in low frequency was intercepted and amplified. As can be seen in Fig.7(b), the phase of missing bump was differentiated from that of the reference solder bump at low frequency. All the defects of missing bumps in test chip were inspected and compared with the sound area. Fig. 8 shows three sets of the phase comparison between the defect area and the sound area, in which M and S represent the area of the missing bump and the sound area with solder bump, respectively, and the numbers correspond to different positions on the test chip, as illustrated in Fig. 3. We calculated the phase information of all pixels. Fig. 4(c) depicts the phase image at 0.8 Hz, in which the missing solder bumps can be identified more explicitly. The results demonstrate that the PPT method employing phase difference can characterize the defects of missing bumps in high density packages. However the structure of flip chip is rather complex, and the thermal difference between the metal areas and their gaps is much larger than that between the defective solder bumps and the good ones. It increases the difficulty and complexity of test procedure and data processing. High thermal conductivity and thermal diffusivity of silicon material also bring some challenge. These problems are still under investigation.
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Phase−frequency curve
Phase−frequency curve
0 −80
−10
Missing bump solder bump
−20
−80.5 −81 Phase/deg
Phase/deg
−30 −40 −50
−81.5 −82
−60
−82.5
−70 Missing bump −80
−83
solder bump
−90 0
5
10
15 20 Frequency/Hz
25
30
0.8
1
1.2
1.4
1.6
1.8
Frequency/Hz
Fig. 7. Phase–frequency curve based on the fitting data: (a) phase–frequency curve and (b) phase–frequency curve at low frequency.
Fig. 8. Three sets of phase comparison at low frequency.
5. Conclusion
Acknowledgment
In this paper, a nondestructive approach based on the pulsed phase thermography was investigated for defect inspection of solder bumps in high density packages. A flip chip package with artificial defects was chosen as the test vehicle to verify the feasibility of this method. After pulsed thermal excitation, the transient response of the test chip was captured by the thermal imager. However, the phase–frequency curve obtained by FFT from the original data oscillated heavily because of the thermal noise. To improve SNR each thermogram was input to the improved median filter, and the temperature decay of each pixel in the chip region was extracted and smoothed by the moving average operation. Then the temperature data were fitted with an exponential function and transformed to the frequency domain through FFT. The phase–frequency curves were obtained, and the curve of the missing solder bump was differentiated from that of the reference solder bump at low frequency. The phase image shows the defects more explicitly than the thermal images. The results demonstrated that the inspection approach based on PPT is effective for identification of the missing bumps in high density packages.
This research work is supported by National Fundamental Research Program of China (Grant no. 2009CB724204) and National Natural Science Foundation of China (Grant nos. 50975106 and 50805061).
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