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To establish new measurement technologies in textiles and clothing.

Three areas are covered, diverse in methodology and approach: measurement of fabric mechanics, measurement of seam quality, and measurement of human size and shape.

Three new measurement technologies have been established.

The mechanics are limited to the measurement of lightweight fabrics. The human measurement needs clear photographs.

All techniques can make measurement more accurate and efficient in all three areas.

All techniques are original and have a major contribution to textile and clothing science and technology.

The drape attributes of fabrics, number of folds, depth of folds and evenness of folds were measured together with the drape coefficient. The relationship between these measurements and the subjective evaluation of the fabric drape was modelled for each end‐use on a neural network using back propagation, which can correctly predict the grades of 90 per cent of the samples. The relationship between the drape attributes and fabric bending, shear and weight was also modelled using neural networks. It was found that using the natural logarithm of the material property divided first by the weight of the fabric produced the most predictive model. Together, these models provide a powerful predictive tool to determine both the drape attributes and the drape grade from the mechanical properties of a fabric. The accuracy of the prediction of this system was found to be 83 per cent overall. Combining this with a novel feedback system, the drape grade or drape attributes of a fabric can be modified to fit the customer requirements and then the changes to the material properties required to achieve them can be determined.

Reports the dynamic modelling of garments on synthetic humans. Develops the model based on a physical analogue to a deep shell system for describing and predicting the real 3‐D shape of clothes. Determines the garment motion by fabric deformation energy, gravity and external constraints of the garment, such as collision forces, using the deformable node bar concept. Justifies the model by agreement between real fabric prediction of static and dynamic drapes using our newly developed drape metre. Demonstrates the garment simulation using garments from two different fabrics in a virtual fashion show. Also describes the work on modelling and animating a synthetic female. The advantages of this model are that engineering parameters can be used as model parameters directly and that the model is configured based on the surface co‐ordinate system, which are important for the next generation of fashion CAD systems incorporating virtual fashion shows. This consideration is fundamental in the context of global retailing and becomes an integral part of intelligent textile and garment manufacture. Proposes the consequences of this work in cinema, TV, advertising and in graphics and animation are also important, but does not examine these.