The bathtub model has often been cited as a hazard rate profile that predicts not only human mortality but also the hazard rate of manufactured products. This article examines the inapplicability of the bathtub model to predict the hazard rate of electronic components, products, and systems. The article reviews various literature and uses numerous experiments and field failure data to support its argument. The factors affecting the hazard rate of electronics are then discussed, common hazard rate trends for electronics are identified, and recommendations for the assessment of hazard rates are given. This article recommends that a preconceived model of hazard rate over time should not be used.

Avionics applications generally require parts that operate reliably in temperature ranges much wider than the commercial 0-70/spl deg/C ranges. However, the availability of electronic parts rated for operating temperature ranges wider than 0-70/spl deg/C is decreasing, as semiconductor manufacturers gradually abandon the nonprofitable military markets and their wide operating temperature range parts. The focus of the semiconductor manufacturers is largely on commercial applications e.g., computers, audiovisual equipment, and cellular phones. One way of meeting this availability problem for parts is "uprating." Uprating is a process to assess the ability of a part to meet the functionality and performance requirements of the applications in which the part is used outside the manufacturers' specification range. An Avionics Working Group and the CALCE Electronic Products and Systems Consortium at the University of Maryland has developed a guidebook consisting of methods for uprating electronic parts. This article presents an overview of these methods including definitions and descriptions.

This paper presents the various ways that lithium-ion batteries are being counterfeited, the problems that counterfeit batteries present, how they enter the consumer market, and the difficulties of detection. Simple external visual inspection of the battery is unreliable. As shown in the presented case study, even for the same brand batteries, their internal structures are different. The current counterfeit prevention methods focus on the manufacturing step. To reduce the risk of counterfeit batteries, device manufacturers and retail stores should characterize the batteries they receive. In addition, related authorities or organizations should set standards to enable a universal battery tracking method along the supply chain to prevent counterfeit lithium-ion batteries from entering the market.

Power semiconductor switches such as Power Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) and Insulated Gate Bipolar Transistors (IGBTs) continue to be a leading cause of failure in power electronics systems. With the continued expansion of the power electronics market, reliable switching devices are of utmost importance in maintaining reliable operation of high power electronic systems. An overview of the failure mechanisms of power semiconductor switches identified by two failure analyses at CALCE is presented. The specific applications of power semiconducting switches have a wide range and include semiconductors found in converters for AC/DC power supplies and home appliance motor control board. All observed failures were from devices which experienced a short circuit between the collector and emitter terminals. The causes of the failures are hypothesized to be a combination of manufacturing defects and poor thermal management.

Insulated-gate bipolar transistors (IGBTs) are one of the most vulnerable components that account for a significant fraction of inverter and converter failures. This paper conducts a degradation analysis of IGBTs using run-to-failure measurements. Online assessment of the degradation state of IGBTs can prolong normal operation and enable proactive maintenance of the system. The research idea is to find a reliable and robust mechanism for IGBT degradation assessment. This paper developed a prediction interval-based degradation assessment methodology that accurately classifies different health states or degradation levels of IGBTs by adding prediction bounds and using them as a critical value for serious damage. It first computes the prediction interval and then uses the Mahalanobis distance to classify the state into degradation level 1 and degradation level 2, instead of just applying the base algorithm. The developed method outperforms distance-based classification schemes and self-organizing maps for online assessment of degradation levels. It only requires training of 1000 initial points which are assumed to be healthy. Furthermore, the generalizability of the method has been shown by validating the effectiveness of the proposed method on three other modules.