Optimisation methodology for risk mitigation in advanced micro-system electronics manufacturing

This paper presents a design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the development of new advanced technologies in the area of micro and nano systems. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to provide knowledge of how a pre-defined geometry can be achieved through this direct milling. The geometry characterisation is obtained using a Reduced Order Models (ROM), generated from the results of a mathematical model of the Focused Ion Beam, and Design of Experiment (DoE) methods. In this work, the focus is on the design flow methodology which includes an approach on how to include process parameter uncertainties into the process optimisation modelling framework. A discussion on the impact of the process parameters, and their variations, on the quality and performance of the fabricated structure is also presented. The design task is to identify the optimal process conditions, by altering the process parameters, so that certain reliability and confidence of the application is achieved and the imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

Predictive reliability, prognostics and risk assessment for power modules

This paper describes a framework that is being developed for the prediction and analysis of electronics power module reliability both for qualification testing and in-service lifetime prediction. Physics of failure (PoF) reliability methodology using multi-physics high-fidelity and reduced order computer modelling, as well as numerical optimization techniques, are integrated in a dedicated computer modelling environment to meet the needs of the power module designers and manufacturers as well as end-users for both design and maintenance purposes. An example of lifetime prediction for a power module solder interconnect structure is described. Another example is the lifetime prediction of a power module for a railway traction control application. Also in the paper a combined physics of failure and data trending prognostic methodology for the health monitoring of power modules is discussed.