Risk mitigation framework for a robust design process

The increasing complexity of new manufacturing processes and the continuously growing range of fabrication options mean that critical decisions about the insertion of new technologies must be made as early as possible in the design process. Mitigating the technology risks under limited knowledge is a key factor and major requirement to secure a successful development of the new technologies. In order to address this challenge, a risk mitigation methodology that incorporates both qualitative and quantitative analysis is required. This paper outlines the methodology being developed under a major UK grand challenge project - 3D-Mintegration. The main focus is on identifying the risks through identification of the product key characteristics using a product breakdown approach. The assessment of the identified risks uses quantification and prioritisation techniques to evaluate and rank the risks. Traditional statistical process control based on process capability and six sigma concepts are applied to measure the process capability as a result of the risks that have been identified. This paper also details a numerical approach that can be used to undertake risk analysis. This methodology is based on computational framework where modelling and statistical techniques are integrated. Also, an example of modeling and simulation technique is given using focused ion beam which is among the investigated in the project manufacturing processes.

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.

Peat, pine stumps and people: interactions behind climate, vegetation change and human activity in wetland archaeology at Loch Farlary, Northern Scotland

First paragraph: In 1993, a peat-cutter, Bruce Field, working on the blanket peat bank he rented from the Sutherland Estate by Loch Farlary, above Golspie in Sutherland (fig 1), reported to Scottish Natural Heritage and Historic Scotland several pieces of pine wood bearing axe marks. Their depth in the peat suggested the cut marks to be prehistoric. This paper summarizes the work undertaken to understand the age and archaeological significance of this find (see also Tipping et al 2001 in press). The pine trees were initially thought to be part of a population that flourished briefly across northern Scotland in the middle of the Holocene period from c 4800 cal BP (Huntley, Daniell & Allen 1997). The subsequent collapse across northernmost Scotland of this population, the pine decline, at around 4200-4000 cal BP is unexplained: climate change has been widely assumed (Dubois & Ferguson 1985; Bridge, Haggart & Lowe 1990; Gear & Huntley 1991) but anthropogenic activity has not been disproved (Birks 1975; Bennett 1995). It was hypothesized that the Farlary find would allow for the first time the direct link between human woodland clearance and the Early Bronze Age pine decline.