Study on Reliability Design of the Domestic Compressor Subjected to Repetitive Internal Stresses by Parametric Accelerated Life Testing

This chapter explains the parametric accelerated life testing (ALT) to recognize design defects in mechanical products. A life-stress model and a sample size formulation are suggested. A compressor is used to demonstrate this method. Compressors were failing in the field. At the first ALT, the compressor failed due to a fractured suction reed valve. The failure modes were similar to those valves returned from the field. The fatigue of the suction reed valves came from an overlap between the suction reed valve and the valve plate. The problematic design was modified by the trespan dimensions, tumbling process, a ball peening, and brushing process for the valve plate. At the second ALT, the compressor locked due to the intrusion between the crankshaft and thrust washer. The corrective action plan performed the heat treatment to the exterior of the crankshaft made of cast iron. After the design modifications, there were no troubles during the third ALT. The lifetime of compressor was secured to have a B1 life 10 years.

Statistical Inference Under Step Stress Partially Accelerated Life Testing for Adaptive Type-II Progressive Hybrid Censored Data

Accelerated life tests (ALTs) are designed to investigate the lifetime of extraordinarily reliable things by exposing them to increased stress levels of stressors such as temperature, voltage, pressure, and so on, in order to cause early breakdowns. The Nadarajah-Haghighi (NH) distribution is of tremendous importance and practical relevance in many real-life scenarios due to its attractive qualities such as its density function always has a zero mode and its hazard rate function can be increasing, decreasing, or constant. In this article, the NH distribution is considered as a lifetime distribution under the step stress partially accelerated life testing (SSPALT) model with adaptive type II progressively hybrid censored samples. The unknown model parameters and acceleration factors are estimated using maximum likelihood estimation (MLE) method assuming that the impact of stress change in SSPALT is explained by a tampered random variable (TRV) model. The Fisher information matrix, which is based on large sample theory, is also constructed and used to produce the approximate confidence intervals (ACIs). Furthermore, two potential optimum test strategies based on the A and D optimality criteria are evaluated. To investigate the performance of the proposed methodologies and statistical assumptions established in this article, extensive simulations using R software have been conducted. Finally, to further illustrate the suggested approach, a real-world example based on the times between breakdowns for a repairable system has been provided.

High Reliability Evaluation and Lifetime Prediction of 50 GHz Athermal AWG Module

A 96-channel (50 GHz-spacing) athermal AWG has been developed. It has a wide operating range due to reduced temperature dependence than conventional AWG. The temperature dependence of the center wavelength of the developed module satisfied the ±0.05 nm range in all channels in the temperature range of −40 °C to 85 °C, and the insertion loss variation was also less than ±0.5 dB. As a result of validating its reliability through tests based on Telcordia-GR-1209 and GR-1221, the temperature dependence of the center wavelength satisfied the ±0.022 nm range, and the insertion loss variation was also less than ±0.2 dB. Accelerated life testing showed an expected service life of over 36.7 years, ensuring long-term safety of communication quality in harsh indoor and outdoor environments.

Effect of Lamination Parameters and Mechanical Folding on SOH Degradation of Li-ion Battery Subjected to Accelerated Life Testing

The growing interest in the flexible field of electronics has provided impetus to incorporation of electronic components such as resistors, capacitors, LEDs, sensors, etc. into flexible circuits. Power sources are another significant component of a majority of electronic circuits which need to be integrated in flexible circuits so as to push the bounds of the wearable technology. One way to do this is by using a laminated film to laminate ultra-thin pouch batteries and then bind them to a flexible substrate. During the lamination process, these batteries are exposed to higher temperatures (above 100 °C), albeit for a short period of time, which can result in damage to the battery’s internals. In this study, a Li-ion pouch cell has been laminated using a hot roller lamination process with different conditions of lamination speed and temperature. The laminated batteries have then been subjected to accelerated life testing in presence and absence of static and dynamic mechanical folding so as to investigate the effect of folding on the laminated batteries. Further, the SOH degradation of the tested batteries is computed and has been incorporated in a regression model so as to study the effect of lamination parameters.

Sustainability Analysis of a ZnO-NaCl-Based Capacitor Using Accelerated Life Testing and an Intelligent Modeling Approach

From small toys to satellites, capacitors play a vital role as an energy storage element, filtering or controlling other critical tasks. This research paper focuses on estimating the remaining useful life of a nanocomposite-based fabricated capacitor using various experimental and artificial intelligence techniques. Accelerated life testing is used to explore the sustainability and remaining useful life of the fabricated capacitor. The acceleration factors affecting the health of capacitors are investigated, and experiments are designed using Taguchi’s approach. The remaining useful lifetime of the fabricated capacitor is calculated using a statistical technique, i.e., regression analysis using Minitab 18.1 software. An expert model is designed using artificial neural networks (ANN), which warns the user of any upcoming faults and failures. The average remaining useful life of the fabricated capacitor, using accelerated life testing, regression, and artificial neural network, is reported as 13,724.3 h, 14,515.9 h, and 14,247.1 h, respectively. A comparison analysis is conducted, and performance metrics are analyzed to opt for the most efficient technique for the prediction of the remaining useful life of the fabricated capacitor, which confirms 93.83% accuracy using the statistical method and 95.82% accuracy using artificial neural networks. The root mean square error (RMSE) of regression and artificial neural networks is found to be 0.102 and 0.167, respectively, which validates the consistency of the reliability methods.