## 8 Conclusions and Future Work  
Evaluating reliability is vital when evaluating the effectiveness of modern solar tracking systems, and numerous methods are available for this analysis, contingent upon the specific component under scrutiny [83]. This paper introduces a mathematical approach for assessing the dependability of state-of-the-art solar tracking devices. The novel maintenance-oriented metric system comprises three sub-metrics addressing the modularity, accessibility, and preventive maintenance of the solar tracker's electronic equipment. For demonstration purposes, a dual-axis solar tracking prototype is designed from several components including 1 \(\times\) Arduino Mega2560 microcontroller unit (MCU), 1 \(\times\) TB6560 stepper driver module (Toshiba Corporation, Tokyo, Japan), 2 \(\times\) stepper motors, 2 \(\times\) relay modules, 1 \(\times\) solar charge controller, 1 \(\times\) accumulator, and 1 \(\times\) voltage convertor. Additional hardware elements such as photoresistors, mechanical limit switches, rotary encoders, voltage, and current sensors are also included to complete the automation cycle of the solar tracking system. The reliability of the solar tracking prototype is evaluated via the reconfigurability property of a modified built-in logic block observer architecture, which is integrated into a low-cost and energy-efficient ASPCB layout created in Altium Designer v22. Furthermore, the solar tracker's maintainability is assessed by analyzing the modularity, accessibility, and preventive maintenance facilities of its hardware components. Regarding fault coverage, several test cases were conducted by simulating the reconfigurable built-in logic block observer architecture in the Altera Modelsim environment. The experimental results show that the modified BILBO design can achieve an average fault coverage of 44.79% using only one generator polynomial function (G1), an average cumulative fault coverage of 81.53% using two polynomial functions (G1, G2), and an average cumulative fault coverage of 97.9% by employing three characteristic polynomials (G1, G2, and G3) for all Sa0 and Sa1 fault scenarios. Therefore, the reconfigurable built-in self-test schematic improves the initial fault coverage by an average of 53% over a low simulation period (2.5 \(\times\) 10\({}^{-8}\) s), demonstrating its feasibility as a low-cost and adaptable design for efficient fault detection implementation. Regarding reliability, a probability-failure curve analysis of the solar tracking system was performed using the fault coverage values obtained in the previous experiments. The probability-to-failure graphical representation is an essential assessment tool for estimating the system's availability, and thus, the potential failure points of the system were determined via the computed solar reliability factor parameters based on the fault coverage-aware metrics. The probability-failure curve shows that the solar tracking system's availability starts to degrade at point \(p=64.07\%\) and reaches its critical threshold at F = 37.7%. The point-to-failure interval comprises the proactive and reactive domains, which rely mainly on repairing and replacing malfunctions components to avoid total system breakdown. However, extended maintenance operations are generally expensive and most of the time ineffective when dealing with multiple hardware problems. Therefore, shifting the focus to the predictive maintenance domain is a more accurate and cost-effective solution for decreasing system downtime. Regarding maintainability, the proposed metrics were applied to the solar tracking prototype to establish the modularity, accessibility, and predictive maintenance features of the hardware components. Thus, the dual-axis solar tracker exhibits MF = 84.21% design modularity, AS = 92.10% design accessibility, and PME = 21.05% preventive maintenance facilities.