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The purpose of this study is to propose an extended reliability method for an industrial motor drive by integrating the physics of failure (PoF).

Industrial motor drive systems (IMDS) are currently expected to perform beyond the desired operating conditions to meet the demand. The PoF of the subsystem affects its reliability under such harsh operating circumstances. It is crucial to estimate reliability by integrating PoF, which helps in understanding its impact and to develop a fault-tolerant design, particularly in such an integrated drive system. An integrated PoF extended reliability method for industrial drive system is proposed to address this issue. In research, the numerical failure rate of each component of industrial drive is obtained first with the help of the MIL-HDBK-217 military handbook. Furthermore, the mathematically deduced proposed approach is modeled in the GoldSim Monte Carlo reliability workbench.

From the results, for a 15% rise in integrated PoF, the reliability and availability of the entire IMDS dropped by 23%, resulting in an impact on mean time to failure (MTTF).

The integrated PoF of the motor and motor controller affects industrial drive reliability, which falls to 0.18 with the least MTTF (2.27 years); whose overall reliability of industrial drive drops to 0.06 if it is additionally integrated with communication protocol.

This paper presents the defects that occur during the assembly and manufacturing of solder joints in single‐sided insertion‐mount printed wiring boards (PWBs). Each type of defect is discussed, with particular focus on how these defects are related to solderability issues, the mechanisms of failure due to defect‐induced failure accelerators, and the effect of the defect on solder joint reliability.

The purpose of this paper is to describe a novel methodology for predicting reliability for consumer electronics or any other hardware systems that experience a complex lifecycle environmental profile.

This Physics-of-Failure–based three-step methodology can be used to predict the degradation rate of a population using a Monte Carlo approach. The three steps include: using an empirical equation describing the degradation of a performance metric, a degradation consistency condition and a technique to account for cumulative degradation across multiple life-cycle stress conditions (e.g. temperature, voltage, mechanical load, etc.).

Two case studies are provided to illustrate the methodology including one related to repeated touch-load induced artifacts for displays.

This novel methodology can be applied to a wide range of applications from mechanical systems to electrical circuits. The results can be fed into the several stages of engineering validation to speed up product qualification.

The purpose of this paper is to highlight the need for degradation data in order to improve the reliability and the mean residual life estimation of a specific item of equipment and to adapt the preventive maintenance tasks accordingly.

An initial reliability model which uses a degradation-based reliability model that is built from the collection of hitting times of a failure threshold. The proposed maintenance model is based on the cost/availability criterion. The estimation of both reliability and optimum time for preventive maintenance are updated with all new degradation data that are collected during operating time.

An improvement for the occurrences of maintenance tasks which minimizes the mean cost per unit of time and increases the availability.

Inspection tasks to measure the degradation level should be realized at least one time for each item of equipment at a specific time determined by the proposed methodology.

The introduction of a criterion which helps the maintainer to decide to postpone or not the preventive replacement time depending on the measured degradation level of a specific item of equipment.

To present key challenges associated with the evolution of system‐in‐package technologies and present technical work in reliability modeling and embedded test that contributes to these challenges.

Key challenges have been identified from the electronics and integrated MEMS industrial sectors. Solutions to optimising the reliability of a typical assembly process and reducing the cost of production test have been studied through simulation and modelling studies based on technology data released by NXP and in collaboration with EDA tool vendors Coventor and Flomerics.

Characterised models that deliver special and material dependent reliability data that can be used to optimize robustness of SiP assemblies together with results that indicate relative contributions of various structural variables. An initial analytical model for solder ball reliability and a solution for embedding a low cost test for a capacitive RF‐MEMS switch identified as an SiP component presenting a key test challenge.

Results will contribute to the further development of NXP wafer level system‐in‐package technology. Limitations are that feedback on the implementation of recommendations and the physical characterisation of the embedded test solution.

Both the methodology and associated studies on the structural reliability of an industrial SiP technology are unique. The analytical model for solder ball life is new as is the embedded test solution for the RF‐MEMS switch.

This paper seeks to introduce a set of key practices that can be used to assess whether an organization has the ability to design, develop and manufacture reliable electronic products.

The ability to design, develop and manufacture reliable electronic products is defined in the paper in terms of a reliability capability maturity model, which is a measure of the practices within an organization that contribute to the reliability of the final product, and the effectiveness of these practices in meeting the reliability requirements of customers.

The paper presents a procedure for evaluating and benchmarking reliability capability. Criteria for assigning different capability maturity levels are presented. The paper also presents a case study corresponding to reliability capability benchmarking of an electronics company.

The paper provides a set of practices for evaluating and benchmarking reliability capability.

Railway transport maintenance plays an important role in delivering safe, reliable and competitive transport services. An appropriate maintenance strategy not only reduces the assets’ lifecycle cost, but also will ensure high standards of safety and comfort for rail passengers and workers. In recent years, the majority of studies have been focused on the application of risk-based tools and techniques to maintenance decision making of railway infrastructure assets (such as tracks, bridges, etc.). The purpose of this paper is to present a risk-based modeling approach for the inspection and maintenance optimization of railway rolling stock components.

All the “potential failure modes and root causes” related to rolling stock systems are identified from an extensive literature review followed by an expert’s panel assessment. The failure causes are categorized into six groups of electrical faults, structural damages, functional failures, degradation, human errors and natural (external) hazards. Stochastic models are then proposed to estimate the likelihood (probability) of occurrence of a failure in the rolling stock system. The consequences of failures are also modeled by an “inflated cost function” that involves safety-related costs, corrective maintenance and renewal (M&R) costs, the penalty charges due to train delays or service interruptions as well as the costs associated with loss of reputation (or loss of fares) in the case of trip cancellation. Lastly, a time-varying risk-cost function is formulated to determine the optimal frequency of preventive inspection and maintenance actions for rolling stock components.

For the purpose of clearly illustrating the proposed risk-based inspection and maintenance modeling methodology, a case study of the Class 380 train’s pantograph system from a Scottish train operating company is provided. The results indicate that the proposed model has a substantial potential to reduce the M&R costs while ensuring a higher level of safety and service quality compared to the currently used inspection methodologies.

The railway rolling stocks should be regularly inspected and maintained so as to ensure network availability and reliability, passenger safety and comfort, and operations efficiency. Despite the best efforts of the maintenance staff, it is reported that a considerable amount of maintenance resources (e.g. budget, time, manpower) is wasted due to insufficiency or inefficiency of current periodic M&R interventions. The model presented in this paper helps the maintenance engineers to assess the current maintenance practices and propose or initiate improvement actions when needed.

There are few studies investigating the application of risk-based tools and techniques to inspection and maintenance decision making of railway rolling stock components. This paper presents a modeling approach aimed at planning the preventive repair and maintenance interventions for rolling stock components based on risk measures. The author’s model is also capable of incorporating real measurement information gathered at each inspection epoch to update future inspection plans.

The purpose of this study is to define configuration requirements needed to define “harmless” small unmanned aerial systems (sUAS) by taking into account mathematical models and ballistic approaches, already defined for small projectiles and now modified, with appropriate assumptions. These safety requirements are related to structures, materials, weight and dimensions, such as the radius of curvature.

In this paper, the state-of-the-art forensic and ballistic physics models are presented, and then safety requirements are defined for sUAS. This big challenge is due to a lack of regulation because each country and each regulatory authority have published their own regulations, where the imposed requirements are different because the mathematical models, and the related assumptions, are different from one country to another. Therefore, proper assumptions are introduced in these models to obtain safety requirements to define harmless final configuration.

If the final configuration meets the requirements defined in the methodology, there are no severe injuries on the human body, in case of impact with the sUAS. In other words, the inoffensive configuration can also be used in overcrowded areas without risks for the human life.

The final configuration proposed in this paper has some design features substantially modified, compared to the conventional configuration, and in particular, the sUAS could be the first harmless multicopter certified in Italy.

A simple tapered plastic optical fiber (POF) sensor is proposed and demonstrated for measurement of uric acid concentrations in de-ionized water. The paper aims to discuss these issues.

The sensor operates based on intensity modulation technique as the tapered POF probe which was coated by a single walled carbon nonotubes polyethylene oxide (SWCNT-PEO) composite is immersed into the uric acid solution. The probe was fabricated using an etching method and has a waist diameter of 0.46 mm and tapering length of 10 mm.

As the concentration varies from 0 to 500 ppm, the output voltage of the sensor increases linearly from 6.13 to 7.35 mV with a sensitivity of 0.0023 mV/% and a linearity of more than 97.20 percent. The SWCNT-PEO composite coating increases the sensitivity of the proposed sensor due to the effective cladding refractive index, which increases with the coating and thus allows more light to be transmitted from the tapered fiber.

This is the first demonstration of the tapered POF sensor for measurement of uric acid concentrations in de-ionized water.