The Study of the Reliability of Complex Components during the Electromigration Process

With the increasing number of inputs and outputs, and the decreasing interconnection spacing, electrical interconnection failures caused by electromigration (EM) have attracted more and more attention. The electromigration reliability and failure mechanism of complex components were studied in this paper. The failure mechanism and reliability of complex components during the electromigration process were studied through the simulation and the experiment, which can overcome the limitation of experimental measurement at a micro-scale. The simulation results indicated that the solder joint has obvious current crowding at the current inlet, which will significantly enhance the electromigration effect. Based on the atomic flux divergence method, the void formation of solder joints can be effectively predicted, and life prediction can be more accurate than Black's equation. Experimental results indicated that the resistance of the daisy chain could be significantly increased with the process of void formation in the solder and corrosion of the leads. Moreover, the growth of intermetallic compounds can be obviously promoted under current stress. The main composition of the intermetallic compounds changes from almost entirely Cu₅Sn₆ to Cu₅Sn₆ and Cu₃Sn; the cracks can be detected at the Cu₃Sn layer. Specifically, the mean time to failure is 1065 h under 1.4 A current and 125 °C based on IPC-9701A guidelines.

Predictive Maintenance Scheduling with Failure Rate Described by Truncated Normal Distribution

The method of risk assessment and planning of technical inspections of machines and optimization of production tasks is the main focus of this study. Any unpredicted failure resulted in the production plans no longer being valid, production processes needing to be rescheduled, costs of unused machine production capacity and losses due to the production of poor-quality products increase, as well as additional costs of human resources, equipment, and materials used during the maintenance. The method reflects the operation of the production system and the nature of the disturbances, allowing for the estimation of unknown parameters related to machine reliability. The machine failure frequency was described with the normal distribution truncated to the positive half of the axis. In production practice, this distribution is commonly used to describe the phenomenon of irregularities. The presented method was an extension of the Six Sigma concept for monitoring and continuous control in order to eliminate and prevent various inconsistencies in processes and resulting products. Reliability characteristics were used to develop predictive schedules. Schedules were assessed using the criteria of solution and quality robustness. Estimation methods of parameters describing disturbances were compared for different job shop scheduling problems. The estimation method based on a maximum likelihood approach allowed for more accurate prediction of scheduling problems. The paper presents a practical example of the application of the proposed method for electric steering gears.