Characterisation of Bioresorbable Composite Performance for Validation of New On-Line Process Monitoring Technology

There is an increasing interest in the biomedical field to create implantable medical devices to provide a temporary mechanical function for use inside the human body. In many of these applications bioresorbable polymer composites using PLLA with β-TCP , are increasingly being used due to their biocompatability, biodegradability and mechanical strength.1,3 These medical devices can be manufactured using conventional plastics processing methods such as injection moulding and extrusion, however there is great need to understand and control the process due to a lack of knowledge on the influence of processing on material properties. With the addition of biocompatible additives there is also a requirement to be able to predict the quality and level of dispersion within the polymer matrix. On-line UV-Vis spectroscopy has been shown to monitor the quality of fillers in polymers. This can eliminate time consuming and costly post-process evaluation of additive dispersion. The aim of this work was to identify process and performance relationships of PLLA/β-TCP composites with respect to melt-extrusion conditions. This is part of a wider study into on-line process monitoring of bioresorbable polymers as used in the medical industry.
These results show that final properties of the PLLA/ β-TCP composite are highly influenced by the particle size and loading. UV-Vis spectroscopy can be used on-line to monitor the final product and this can be utilised as a valuable tool for quality control in an application where consistent performance is of paramount importance.

Recent applications of Chemical Imaging to pharmaceutical process monitoring and quality control

Chemical Imaging (CI) is an emerging platform technology that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Vibrational spectroscopic methods, such as Near Infrared (NIR) and Raman spectroscopy, combined with imaging are particularly useful for analysis of biological/pharmaceutical forms. The rapid, non-destructive and non-invasive features of CI mark its potential suitability as a process analytical tool for the pharmaceutical industry, for both process monitoring and quality control in the many stages of drug production. This paper provides an overview of CI principles, instrumentation and analysis. Recent applications of Raman and NIR-CI to pharmaceutical quality and process control are presented; challenges facing Cl implementation and likely future developments in the technology are also discussed. (C) 2007 Elsevier B.V. All rights reserved.

Assessing the Impact of Technology on Aircraft Systems using Technology Impact Forecasting

In today’s atmosphere of constrained defense spending and reduced research budgets, determining how to allocate resources for research and design has become a critical and challenging task. In the area of aircraft design there are many promising technologies to be explored, yet limited funds with which to explore them. In addition, issues concerning uncertainty in technology readiness as well as the quantification of the impact of a technology (or combinations of technologies), are of key importance during the design process. This paper presents a methodology that details a comprehensive and structured process in which to quantitatively explore the effects of technology for a given baseline aircraft. This process, called Technology Impact Forecasting (TIF), involves the creation of a assessment environment for use in conjunction with defined technology scenarios, and will have a significant impact on resource allocation strategies for defense acquisition. The advantages and limitations of the method are discussed. In addition, an example TIF application, that of an Uninhabited Combat Aerial Vehicle, is presented and serves to illustrate the applicability of this methodology to a military system.

Investigation of precision grinding process for production of silicon diaphragms

The application of precision grinding for the formation of a silicon diaphragm is investigated. The test structures involved 2-6 mm diam diaphragms with thicknesses in the range of 25-150 //m. When grinding is performed without supporting the diaphragm, bending occurs due to nonuniform removal of the silicon material over the diaphragm region. The magnitude of bending depends on the µNal thickness of the diaphragm. The results demonstrate that the use of a porous silicon support can significantly reduce the amount of bending, by a factor of up to 300 in the case of 50 m thick diaphragms. The use of silicon on insulator (SOI) technology can also suppress or eliminate bending although this may be a less economical process. Stress measurements in the diaphragms were performed using x-ray and Raman spectroscopies. The results show stress of the order of 1 X107-! X108 Pa in unsupported and supported by porous silicon diaphragms while SOI technology provides stress-free diaphragms. Results obtained from finite element method analysis to determine deterioration in the performance of a 6 mm diaphragm due to bending are presented. These results show a 10% reduction in performance for a 75 µm thick diaphragm with bending amplitude of 30 fim, but negligible reduction if the bending is reduced to

Dynamic Multivariate Statistical Process Control using Subspace Identification

This paper points out a serious flaw in dynamic multivariate statistical process control (MSPC). The principal component analysis of a linear time series model that is employed to capture auto- and cross-correlation in recorded data may produce a considerable number of variables to be analysed. To give a dynamic representation of the data (based on variable correlation) and circumvent the production of a large time-series structure, a linear state space model is used here instead. The paper demonstrates that incorporating a state space model, the number of variables to be analysed dynamically can be considerably reduced, compared to conventional dynamic MSPC techniques.