Optimization and finite element analysis for reliable electronic packaging

This paper demonstrates a modeling and design approach that couples computational mechanics techniques with numerical optimisation and statistical models for virtual prototyping and testing in different application areas concerning reliability of eletronic packages. The integrated software modules provide a design engineer in the electronic manufacturing sector with fast design and process solutions by optimizing key parameters and taking into account complexity of certain operational conditions. The integrated modeling framework is obtained by coupling the multi-phsyics finite element framework - PHYSICA - with the numerical optimisation tool - VisualDOC into a fully automated design tool for solutions of electronic packaging problems. Response Surface Modeling Methodolgy and Design of Experiments statistical tools plus numerical optimisaiton techniques are demonstrated as a part of the modeling framework. Two different problems are discussed and solved using the integrated numerical FEM-Optimisation tool. First, an example of thermal management of an electronic package on a board is illustrated. Location of the device is optimized to ensure reduced junction temperature and stress in the die subject to certain cooling air profile and other heat dissipating active components. In the second example thermo-mechanical simulations of solder creep deformations are presented to predict flip-chip reliability and subsequently used to optimise the life-time of solder interconnects under thermal cycling.

Microwave curing for high density package

Summary form only given. Currently the vast majority of adhesive materials in electronic products are bonded using convection heating or infra-red as well as UV-curing. These thermal processing steps can take several hours to perform, slowing throughput and contributing a significant portion of the cost of manufacturing. With the demand for lighter, faster, and smaller electronic devices, there is a need for innovative material processing techniques and control methodologies. The increasing demand for smaller and cheaper devices pose engineering challenges in designing a curing systems that minimize the time required between the curing of devices in a production line, allowing access to the components during curing for alignment and testing. Microwave radiation exhibits several favorable characteristics and over the past few years has attracted increased academic and industrial attention as an alternative solution to curing of flip-chip underfills, bumps, glob top and potting cure, structural bonding, die attach, wafer processing, opto-electronics assembly as well as RF-ID tag bonding. Microwave energy fundamentally accelerates the cure kinetics of polymer adhesives. It provides a route to focus heat into the polymer materials penetrating the substrates that typically remain transparent. Therefore microwave energy can be used to minimise the temperature increase in the surrounding materials. The short path between the energy source and the cured material ensures a rapid heating rate and an overall low thermal budget. In this keynote talk, we will review the principles of microwave curing of materials for high density packing. Emphasis will be placed on recent advances within ongoing research in the UK on the realization of "open-oven" cavities, tailored to address existing challenges. Open-ovens do not require positioning of the device into the cavity through a movable door, hence being more suitable for fully automated processing. Further potential advantages of op- - en-oven curing include the possibility for simultaneous fine placement and curing of the device into a larger assembly. These capabilities promise productivity gains by combining assembly, placement and bonding into a single processing step. Moreover, the proposed design allows for selective heating within a large substrate, which can be useful particularly when the latter includes parts sensitive to increased temperatures.

A novel neural/symbolic hybrid approach to heuristically optimized fuel allocation and automated revision of heuristics in nuclear engineering

FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

Fire field modelling using the SMARTFIRE automated dynamic solution control environment

SMARTFIRE is a fire field model based on an open architecture integrated CFD code and knowledge-based system. It makes use of the expert system to assist the user in setting up the problem specification and new computational techniques such as Group Solvers to reduce the computational effort involved in solving the equations. This paper concentrates on recent research into the use of artificial intelligence techniques to assist in dynamic solution control of fire scenarios being simulated using fire field modelling techniques. This is designed to improve the convergence capabilities of the software while further decreasing the computational overheads. The technique automatically controls solver relaxations using an integrated production rule engine with a blackboard to monitor and implement the required control changes during solution processing. Initial results for a two-dimensional fire simulation are presented that demonstrate the potential for considerable savings in simulation run-times when compared with control sets from various sources. Furthermore, the results demonstrate enhanced solution reliability due to obtaining acceptable convergence within each time step unlike some of the comparison simulations.

A fully polynomial approximation scheme for the single machine weighted total tardiness problem with a common due date

We develop a fully polynomial-time approximation scheme (FPTAS) for minimizing the weighted total tardiness on a single machine, provided that all due dates are equal. The FPTAS is obtained by converting an especially designed pseudopolynomial dynamic programming algorithm.