A Holistic Solution for Reliability of 3D Parallel Systems

Monolithic 3D technology is emerging as a promising solution that can bring massive opportunities, but the gains can be hindered due to the reliability issues exaggerated by high temperature. Conventional reliability solutions focus on one specific feature and assume that the other required features would be provided by different solutions. Hence, this assumption has resulted in solutions that are proposed in isolation of each other and fail to consider the overall compatibility and the implied overheads of multiple isolated solutions for one system. This article proposes a holistic reliability management engine, R2D3, for post-Moore’s M3D parallel systems that have low yield and high failure rate. The proposed engine, comprising a controller, reconfigurable crossbars, and detection circuitry, provides concurrent single-replay detection and diagnosis, fault-mitigating repair, and aging-aware lifetime management at runtime. This holistic view enables us to create a solution that is highly effective while achieving a low overhead. Our solution achieves 96% coverage of defect; reduces V th degradation by 53%, leading to a 78% performance improvement on average over 8 years for an eight-core system; and ultimately yields a 2.16× longer mean-time-to-failure (MTTF) while incurring an overhead of 7.4% in area, 6.5% in power, and an 8.2% decrease in frequency.

AMROFloor: An Efficient Aging Mitigation and Resource Optimization Floorplanner for Virtual Coarse-Grained Runtime Reconfigurable FPGAs

With the rapid reduction of CMOS process size, the FPGAs with high-silicon accumulation technology are becoming more sensitive to aging effects. This reduces the reliability and service life of the device. The offline aging-aware layout planning based on balance stress is an effective solution. However, the existing methods need to take a long time to solve the floorplanner, and the corresponding layout solutions occupy many on-chip resources. To this end, we proposed an efficient Aging Mitigation and Resource Optimization Floorplanner (AMROFloor) for FPGAs. First, the layout solution is implemented on the Virtual Coarse-Grained Runtime Reconfigurable Architecture, which contributes to avoiding rule constraints for placement and routing. Second, the Maximize Reconfigurable Regions Algorithm (MRRA) is proposed to quickly determine the RRs’ number and size to save the solving time and ensure an effective solution. Furthermore, the Resource Combination Algorithm (RCA) is proposed to optimize the on-chip resources, reducing the on-Chip Resource Utilization (CRU) while achieving the same aging relief effect. Experiments were simulated and implemented on Xilinx FPGA. The results demonstrate that the AMROFloor method designed in this paper can extend the Mean Time to Failure (MTTF) by 13.8% and optimize the resource overhead by 19.2% on average compared to the existing aging-aware layout solutions.

An Adaptive Modeling Framework for Bearing Failure Prediction

Rolling element bearings are a common component in rotating equipment, a class of machines that is essential in a wide range of industries. Detecting and predicting bearing failures is then vital for reducing maintenance and production costs due to unplanned downtime. In previous literature, significant efforts have been devoted to building data-driven health models from historical bearing data. However, a common limitation is that these methods are typically tailored to specific failure instances and have limited ability to model bearing failures between repairs in the same system. In this paper, we propose a multi-state health model to predict bearing failures before they occur. The model employs a regression-based method to detect health state transition points and applies an exponential random coefficient model with a Bayesian updating process to estimate time-to-failure distributions. A model training framework is also introduced to make our proposed model applicable to more bearing instances in the same system setting. The proposed method has been tested on a publicly available bearing prognostics dataset. Case study results show that the proposed method provides accurate failure predictions across several system failures, and that the training approach can significantly reduce the time necessary to generate an effective, generalized model.

Fire performance of hybrid mass timber beam-end connections with perpendicular-to-wood grain reinforcement

PurposeThe fire resistance of timber structures is heavily dependent on the fire behaviour of the connections between its structural elements. The experimental study presented in this paper aimed to investigate the fire performance of glued-laminated timber beam connections reinforced perpendicular-to-wood grain with self-tapping screws (STS).Design/methodology/approachTwo full-size fire experiments were conducted on glulam beam-end connections loaded in flexure bending. Two connection configurations, each utilizing four steel bolts arranged in two different patterns, were reinforced perpendicular to wood grain using STS. The bolt heads and nuts and the steel plate top and bottom edges were fire protected using wood plugs and strips, respectively. Each connection configuration was loaded to 100% of the ultimate design load of the weakest unreinforced configuration. The test assemblies were exposed to elevated temperatures that followed the CAN/ULC-S101 standard fire time–temperature curve.FindingsThe experimental results show that the influence of the STS was significant as it prevented the occurrence of wood splitting and row shear-out and as a result, increased the fire resistance time of the connections. The time to failure of both connection configurations exceeded the minimum fire resistance rating specified as 45 min for combustible construction in applicable building codes.Originality/valueThe experimental data show the effectiveness of a simple fire protection system (i.e. wood plugs and strips) along with the utilization of STS on the rotational behaviour, charring rate, fire resistance time and failure mode of the proposed hybrid mass timber beam-end connection configurations.

Prediction of Material Failure Time for a Bucket Wheel Excavator Boom Using Computer Simulation

Breakdown of stackers and excavators in opencast mines is possible because of operating, manufacturing and structural causes, and it produces high financial losses. These can be prevented by using various measures, including analyses and strength tests, with computerized modeling and simulation using FEA or other techniques being implemented in the recent years. In this paper a fatigue study is conducted on the boom of a BWE. Based on a computer model of the boom previously developed in SOLIDWORKS by our author team, first the modal analysis is conducted for three positions of the boom by studying the frequency response during the excavation process. This is followed by the time response determination corresponding to the maximum displacement frequency, in order to assess the stress during the excavation process, which causes the material fatigue in the boom structure. It was found that the maximum displacements appear when the BWE boom operates in a horizontal position. The aim was to estimate the period of time to failure in order to prevent unwanted accidents, and to develop a method that is applicable to any surface mining or industrial machine with similar structure.

Reliability aspects in a dynamic time-to-failure degradation-based model

Although the ordinary time-to-failure degradation-based model has been extensively used in practice, it also has its limitations. In this paper, we consider a time-to-failure degradation-based model recently proposed by Albabtain et al., where a limiting conditional survival probability entertains further stochastic relationships between the failure time and the degree of degradation. In the particular case where the limited survival probability is available for the proportional failure rate model, the model is developed using two well-known degradation paths, namely the additive degradation path and the multiplicative degradation path, each of which has a component of random variation. Preservation of various stochastic orders and aging properties of the random variation component in the model in the described setting is developed. To illustrate the model in the modified design, some examples of interest in reliability are presented.

Investigation of Mean-Time-to-Failure Measurements from AlGaN/GaN High-Electron-Mobility Transistors Using Eyring Model

We present the mean-time-to-failure (MTTF) calculations for AlGaN/GaN high-electron-mobility transistors (HEMTs) using two independent acceleration factors. MTTF predictions are generally calculated through the Arrhenius relationship, based on channel temperature and acceleration, depend only on one parameter. Although the failure modes of the AlGaN/GaN HEMTs depend largely on the applied electric fields, the Eyring model is introduced to investigate both voltage and temperature dependent degradation of AlGaN/GaN devices. In anticipation of adequate MTTF values, studies were conducted on non-commercial devices. Further, we distinguished the cumulative failure percentages through the Weibull and log-normal distributions. We also explored the increase in gate leakage current at high temperatures for early device deterioration.