# Reliable Method to Detect Alloy Soldering Fractures under Accelerated Life Test
## 5 Methodology  
As mentioned above, in the development of this research, 17 electronic assemblies with dimensions of 2 cm\(\times\) 2 cm were fabricated, where components such as leads and electric resistance were used, with the objective of analyzing the characteristics of the soldering alloy. Electronic components of this type are among the most used worldwide in all types of electronics components such as: TVs, cell phones, tablets, computers; resistors, diodes, LEDs, and capacitors. For this work, the components were built based on an LED and a diode. Five control factors were selected, as follows: soldering alloy, path, width, temperature levels, pretreatment, and vibration levels. The levels of the soldering alloy are Sn40 Pb60 and Sn0.3 Cu0.5 Ag3.5, path 0.38 and 0.56  temperature 90 \({}^{\circ}\)C and 125 \({}^{\circ}\)C, pretreatment with thermal shock (0 \({}^{\circ}\)C) and without thermal shock, and vibration with resonance (40 Hz) and without resonance. The ALT was divided into two stages. In the first stage, the basis of the design of the test were established. In this stage, four tools were used, which are the functional block diagram, the Fault Tree Analysis (FTA), the FMEA, and the parameter diagram. To prepare these tools, field information, terms of use and technical sheets were used. At the other extreme, stage two consisted of the test design, where the failure modes, the stress variables, and the test conditions were established. In the failure mode effect analysis, the fracture in the soldering alloy was the highest failure mode with a Level of Risk Priority (LRP) of 300, which is due to the soldering alloy found in the pines of each component allowing the current flow. With the FTA, the causes of the failure were found, which are the temperature and vibration [9; 10; 11; 12; 13; 15; 16; 17; 18; 19; 20]. In the reliability test, it is important to know which of failure modes is in use, and what causes it. Due to this, analysis of the system must be done before proceeding with the tests. Therefore, information about the phenomena that originated the failure must be obtained, which will be the experimental variables. In this research, a design of experiment was used [20; 21; 22]. This allowed definition of the different combinations of the variables that duplicate the failure modes in minor time compared to the traditional methods. Table 1 shows the optimal experimental design obtained to realize the different combinations of the variables and its level, where -1 represents the low level and 1 represents the major level [10; 11; 12; 13; 15; 16; 17; 18; 19; 20; 21; 22; 23]. Figure 3: Weibull distribution. Adapted from the theories proposed by [PERSON] et al. [10]. Minitab v 18 (r) [24] made the corresponding calculations of the statistical analysis and the experiments design for calculating the accelerated factor of the temperature test. [PERSON]'s equation was used (Equation (4)). This mathematical equation allows escalation of the time of the test with the time of use [12]. \[A_{f}=e^{\left[\frac{E_{t}}{1}(\frac{1}{T_{1}}-\frac{1}{T_{2}})\right]} \tag{4}\]  
where:  
* \(A_{f}=\) pre-exponential factor or frequency factor. * \(k=\) kinetic constant Boltzmann's constant (physical constant that relates absolute temperature and energy). * \(E_{a}=\) activation energy. * \(T_{1}=\) Field-use temperature
* \(T_{2}=\) Accelerated test temperature.