Simulation of 2-D metal cutting by means of a distributed algorithm

Temperature distributions involved in some metal-cutting or surface-milling processes may be obtained by solving a non-linear inverse problem. A two-level concept on parallelism is introduced to compute such temperature distribution. The primary level is based on a problem-partitioning concept driven by the nature and properties of the non-linear inverse problem. Such partitioning results to a coarse-grained parallel algorithm. A simplified 2-D metal-cutting process is used as an example to illustrate the concept. A secondary level exploitation of further parallel properties based on the concept of domain-data parallelism is explained and implemented using MPI. Some experiments were performed on a network of loosely coupled machines consist of SUN Sparc Classic workstations and a network of tightly coupled processors, namely the Origin 2000.

Uncertainty analysis to minimise risk in designing micro-electronics manufacturing processes

A design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the process control of micro and nano-electronics based manufacturing processes is presented in this paper. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to help understand how a pre-defined geometry of micro- and nano- structures can be achieved using this technology. The process performance is characterised on the basis of developed Reduced Order Models (ROM) and are generated using results from a mathematical model of the Focused Ion Beam and Design of Experiment (DoE) methods. Two ion beam sources, Argon and Gallium ions, have been used to compare and quantify the process variable uncertainties that can be observed during the milling process. The evaluations of the process performance takes into account the uncertainties and variations of the process variables and are used to identify their impact on the reliability and quality of the fabricated structure. An optimisation based design task is to identify the optimal process conditions, by varying the process variables, so that certain quality objectives and requirements are achieved and imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

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.

In vitro release of bovine serum albumin from alginate/HPMC hydrogel beads

In recent years, the use of swelling polymeric matrices for the encapsulation and controlled release of protein drugs has received significant attention. The purpose of the present study was to investigate the release of albumin, a model protein from alginate/hydroxypropyl-methylcellulose (HPMC) gel beads. A hydrogel system comprised of two natural, hydrophilic polymers; sodium alginate and HPMC was studied as a carrier of bovine serum albumin (BSA) which was used as a model protein. The morphology, bead size and the swelling ratio were studied in different physical states; fully swollen, dried and reswollen using scanning electron microscopy and image analysis. Finally the effect of different alginate/HPMC ratios on the BSA release profile in physiological saline solution was investigated. Swelling experiments revealed that the bead diameter increases with the viscosity of the alginate solution while the addition of HPMC resulted in a significant increase of the swelling ratio. The BSA release patterns showed that the addition of HPMC increased the protein-release rate while the release mechanism fitted the Peppas model. Alginate/HPMC beads prepared using the ionic gelation exhibited high BSA loading efficiency for all formulations. The presence of HPMC increased the swelling ability of the alginate beads while the particle size remained unaffected. Incorporation of HPMC in the alginate gels also resulted in improved BSA release in physiological saline solution. All formulations presented a non-Fickian release mechanism described by the Peppas model. In addition, the implementation of non-parametric tests showed significant differences in the release patterns between the alginate/HPMC and the pure alginate beads, respectively.