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Design method based on linguistics and logic

โœ Scribed by J. Korn


Publisher
Elsevier Science
Year
1992
Tongue
English
Weight
643 KB
Volume
7
Category
Article
ISSN
0954-1810

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โœฆ Synopsis


Design seems to involve much of what is generally called creative thinking engendering methods like brain storming, morphological analysis and others. Experience is considered essential. All this appears to have little, or no, basis in the accepted branches of knowledge. Teaching of design can be difficult.

The proposed method aims to bring deductive thinking closer to design by introducing an analysis stage before design theory and by making significant use of implication inherent in linguistic modelling. In this stage, concepts such as state and its change, properties, interactions, systems and products are established and the required symbology is developed. The method differentiates between systems and product design and identifies the 'problem' and the 'solution' parts of the design process leading to an organised procedure.

The solution part makes use of linguistic modelling, a development of natural language, in the form of stative and dynamics abstract functions which define the role of devices without reference to hardware. These are used for the generation of schemes for systems and plans for products in an abstract domain leaving the choice of hardware open. Symbolic logic and Prolog enable such schemes and plans to be tested regarding their feasibility and the possibility of emergence of specified outcomes. Components in functional terms are identified, leading to the question of interfacing, quiescent properties, users, suppliers, absorbers, structural effects and disturbances. Engineering knowledge enters the design process at this point, creativity is given ample scope in identification of the problem and in selecting and inventing hardware.


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This work describes a new methodology for making easier the design process of interpretable knowledge bases. It considers both expert knowledge and knowledge extracted from data. The combination of both kinds of knowledge is likely to yield robust compact systems with a good trade-off between accura