The 'what' and 'how' of learning in design, invited paper

Previous experiences hold a wealth of knowledge which we often take for granted and use unknowingly through our every day working lives. In design, those experiences can play a crucial role in the success or failure of a design project, having a great deal of influence on the quality, cost and development time of a product. But how can we empower computer based design systems to acquire this knowledge? How would we use such systems to support design? This paper outlines some of the work which has been carried out in applying and developing Machine Learning techniques to support the design activity; particularly in utilising previous designs and learning the design process

Preparation of Translationally Competent tRNA by Direct Chemical Acylation

Nonsense codon suppression for unnatural amino acid incorporation requires the preparation of a suppressor aminoacyl-tRNA. Chemical acylation strategies are general but inefficient and arduous. A recent report (J. Am. Chem. Soc. 2007, 129, 15848) showed acylation of RNA mediated by lanthanum(III) using amino acid phosphate esters. The successful implementation of this methodology to full-length suppressor tRNA is described, and it is shown that the derived aminoacyl-tRNA is translationally competent in Xenopus oocytes

Modularity in support of design for re-use

We explore the structuring principle of modularity with the objective of analysing its current ability to meet the requirements of a 're-use' centred approach to design. We aim to highlight the correlation's between modular design and 're-use', and argue that it has the potential to aid the little-supported process of 'design-for-re-use'. In fulfilment of this objective we not only identify the requirements of 'design-for-re-use', but also propose how modular design principles can be extended to support 'design-for-re-use'

A formalism for coupled design learning activities

This paper presents a formalism to represent the inextricable link that exists between design and learning. It provides an approach to study and analyse the complex relationships that may exist between design and learning. It suggests that design and learning are linked at the knowledge level (epistemic link), in a temporal manner and in a purposeful manner through the design and learning goal

Re-using knowledge : why, what and where

Previously the 're-use' focus has centred on specific and/or standard parts, more recently however, [standard components] are being developed...to enable both the re-use of the part and the experience associated with that part'. This notion is further extended by Finger who states that 'designers may re-use a prior design in it's entirety,...may re-use an existing shape for a different function, or may re-use a feature from another design'. Reinforcing this notion we currently consider re-use to reflect the utilisation of any knowledge gained from a design activity and not just past designs of artefacts. Our research concerns the improvement of formal 're-use' support and as such we have identified a need to gain a better understanding of how design knowledge can be utilised to support 're-use'. Thus, we discuss the requirements of successful 're-use' and attempt to ascertain within this skeleton: what knowledge can be re-used; how to maximise its' applicability; and where and when it can be utilised in new design

Knowledge transformers : a link between learning and creativity

The purpose of this paper is to investigate whether knowledge transformers which are featured in the learning process, are also present in the creative process. This is achieved by reviewing models and theories of creativity and identifying the existence of the knowledge transformers. The investigation shows that there is some evidence to show that the creative process can be explained through knowledge transformers. Hence, it is suggested that one of links between learning and creativity is through the knowledge transformers

Shape matching and clustering in design

Generalising knowledge and matching patterns is a basic human trait in re-using past experiences. We often cluster (group) knowledge of similar attributes as a process of learning and or aid to manage the complexity and re-use of experiential knowledge [1, 2]. In conceptual design, an ill-defined shape may be recognised as more than one type. Resulting in shapes possibly being classified differently when different criteria are applied. This paper outlines the work being carried out to develop a new technique for shape clustering. It highlights the current methods for analysing shapes found in computer aided sketching systems, before a method is proposed that addresses shape clustering and pattern matching. Clustering for vague geometric models and multiple viewpoint support are explored

Process performance measurement support : a critical analysis

Design development processes, within engineering disciplines, lack the necessary mechanisms in identifying the specific areas where improved design development performance may be obtained. In addition, they lack the means to consider and align the goals and respective performance levels of related development activities with an organisation's overall goals and performance levels. Current research in organisational performance behaviour, formalised through performance frameworks and methodologies, has attempted to identify and focus upon those critical factors which impinge upon a wealth creation system while attempting to, simultaneously, remain representative of organisational functions, processes, people, decisions and goals. Effective process improvements remain conditional upon: the ability to measure the potential performance gains which may result from an improvement initiative; the ability to understand existing process dynamics and in turn understand the subsequent impact of some change to a system/process; and, the ability to identify potential areas for improvement. The objective of this paper is to discuss some of the management techniques, which are purported to support various process performance concerns and perspectives, and present the major factors that remain unsupported in identifying, measuring and understanding design process performance