An Innovative Methodology of Product Design from Nature

Nature is an information sourcebook of behaviour, function, colour and shape which can inspire visual design and invention. Studying the form and functional characteristics of a natural object can provide inspiration for product design and help to improve the marketability of manufactured products. The inspiration can be triggered either by direct observation or captured by three-dimensional （3D） digitising techniques to obtain superficial information （geometry and colour）. An art designer often creates a concept in the form of a two-dimensional （2D） sketch while engineering methods lead to a point cloud in 3D. Each has its limitations in that the art designer commonly lacks the knowledge to build a final product from a 2D sketch and the engi- neering designer＇s 3D point clouds may not be very beautiful. We propose a method for Product Design from Nature （PDN）, coupling aesthetic intent and geometrical characteristics, exploring the interactions between designers and nature＇s systems in PDN. We believe that this approach would considerably reduce the lead time and cost of product design from nature.

3D Modelling of Biological Systems for Biomimetics

With the advanced development of computer-based enabling technologies, many engineering, medical, biology, chemistry, physics and food science etc have developed to the unprecedented levels, which lead to many research and development interests in various multi-discipline areas. Among them, biomimetics is one of the most promising and attractive branches of study. Biomimetics is a branch of study that uses biological systems as a model to develop synthetic systems. To learn from nature, one of the fundamental issues is to understand the natural systems such animals, insects, plants and human beings etc. The geometrical characterization and representation of natural systems is an important fundamental work for biomimetics research. 3D modeling plays a key role in the geometrical characterization and representation, especially in computer graphical visualization. This paper firstly presents the typical procedure of 3D modelling methods and then reviews the previous work of 3D geometrical modelling techniques and systems developed for industrial, medical and animation applications. Especially the paper discusses the problems associated with the existing techniques and systems when they are applied to 3D modelling of biological systems. Based upon the discussions, the paper proposes some areas of research interests in 3D modelling of biological systems and for Biomimetics.

Optimising Body Layout Design of Limbed Machines

This paper presents our efforts to explain why mammals have large thigh muscles while insects have small ones. After a discussion of this observation a definition of body foot ratio is defined which describes how animals stand and how their legs are arranged. To investigate the mechanics, we present a closed optimum solution of the body foot ratio for a 2D two-leg walking machine. A multi-walker is used as a case for 3D general analysis, and the numerical simulation is presented. Both 2D and 3D case studies can explain the above observations of mammals and insects. These findings can also be used as a guide for the design of man-made limbed machines.

An Evaluation Model of Supply Chain Performances Using 5DBSC and LMBP Neural Network Algorithm

A high efficient Supply Chain （SC） would bring great benefits to an enterprise such as integrated resources, reduced logistics costs, improved logistics efficiency and high quality of overall level of services. So it is important to research various methods, performance indicator systems and technology for evaluating, monitoring, predicting and optimizing the performance of a SC. In this paper, the existing performance indicator systems and methods are discussed and evaluated. Various nature-inspired algorithms are reviewed and their applications for SC Performance Evaluation （PE） are discussed. Then, a model is proposed and developed using 5 Dimensional Balanced Scorecard （5DBSC） and LMBP （Levenberg-Marquardt Back Propagation） neural network for SC PE. A program is written using Matlab tool box to implement the model based on the practical values of the 14 indicators of 5DBSC of a given previous period. This model can be used to evaluate, predict and optimize the performance of a SC. The analysis results of a case study of a company show that the proposed model is valid, reliable and effective. The convergence speed is faster than that in the previous work.