# Development of a Non-Invasive On-Chip Interconnect Health Sensing Method Based on Bit Error Rates
## 1 Introduction  
Timely maintenance of systems and assets is critical for the prevention of loss in revenue owing to unexpected system downtime. Therefore, proactive maintenance strategies were developed that are optimized to increase the availability of products and systems. In particular, condition-based maintenance is a proactive maintenance strategy that involves monitoring the performance and environmental conditions of a target system. One of the key factors associated with proactive maintenance is the use of appropriate sensors to collect system health data for fault diagnosis and prognosis.  
Many researchers conducted studies to develop system health monitoring methods using electrical parameters in the time or frequency domain. [PERSON] et al. [1] suggested a quantitative measurement tool based on the serial ohmic resistance changes at solder joints; the serial ohmic resistance in such cases was used to monitor crack propagation in the solder joints of a quad flat non-leads (QFN) package. Their experimental results showed that the serial ohmic resistance increased as a result of the crack growth. [PERSON] et al. [2] proposed a condition monitoring method for insulated-gate bipolar transistor (IGBT) power modules based on voltage measurements. In particular, they designed anadditional measurement circuit for the monitoring system to measure voltage. [PERSON] et al. [3] applied acoustic emission detection to detect damage in the solder interconnections between components and the printed circuit board. [PERSON] et al. [4] used joint time-frequency domain reflectometry (JTFDR) to monitor incipient power cable faults; their results showed that the JTFDR time-frequency cross correlation peak increased during cable aging testing. [PERSON] et al. [5] used a vector network analyzer (VNA) to measure the S-parameters of a through-silicon via (TSV) stacked die, and showed the potential of high-frequency signal-based measurement for assessing the reliability of TSV stacked dies. Researchers also reported defect sensing methods using eddy current pulsed thermography [6; 7] and acoustic micro imaging [8]. [PERSON] et al. [9] applied normal fiber Bragg grating (FBG) sensors to have real-time health monitoring of composite materials. [PERSON] et al. [10] reviewed the sensing devices, such as X-ray, scanning acoustic microscope, infrared (IR) camera sensor magnetic field, and optical vibration measurement, for integrated circuit (IC) package inspection. Nevertheless, these existing methods often require external and additional sensing devices, such as multimeters, oscilloscopes, and VNAs, which might disturb real-time system operation of these packages or devices, and eventually increase operating costs. Therefore, a non-destructive and non-invasive health monitoring method is required for fault diagnosis and prognosis that helps in reducing monitoring time and costs.  
In this study, we present an on-chip health sensing method for non-destructive and non-invasive interconnect degradation detection based on digital signal characteristics; in particular, bit error rate (BER), defined as the ratio of the number of erroneously transmitted bits to the generated bits, was used to measure the physical degradation of an interconnect. Accelerated life tests on solder joints were conducted with in situ monitoring of the BER and DC resistance to verify the health sensing performance of the proposed method, as well as compare it with that of the DC resistance measurement. The advantage of the proposed method is that BER, which can be programmed and analyzed using a chip, does not require external and additional devices to monitor interconnect degradation.  
The remainder of this paper is organized as follows: Section 2 introduces the concept of digital signal characteristics, and how BER is measured. Section 3 presents our proposed interconnect health sensing method based on BER. The experiment-based sensing performance validation of our proposed approach is discussed in Section 4. Finally, Section 5 summarizes and concludes the paper.