Subassembly identification based on grey clustering

Nowadays discarded electromechanical products are more and more common, and have done much harm to the ecological environment, human health and natural resources. In order to recycle discarded products effectively, it is necessary to disassemble them properly in an integrated consideration of economic returns and environmental protection. Therefore Disassembly Process Planning has become a key part in Environmentally Conscious Design. Because there may be a combination explosion when the disassembly process of a product with a large number of parts is planned, subassembly identification is often adopted to divide the product into some reasonable subassemblies. This paper uses a method of grey clustering based on grey system theory to perform subassembly identification. The clustered objects are part pairs with adjacency relation in a product, and the clustering indices consist of energy consumption of disassembly, disassembly time, disassemblable direction and diameter of part pair. The indices can be obtained by detailed estimate or direct input from a CAD system via secondary development. After five grey clusters are set up, their whitening weight functions are presented in detail. Several other key problems in subassembly identification based on grey clustering are also expounded, such as obtaining the nondimensional matrix of sample values, determining the weight of clustering index relative to grey cluster. A heat-sealing machine with 80 components is selected as an example to validate the method of subassembly identification based on grey clustering. The identification result of the example is feasible according to experiences, and at the same time it satisfies the requirement of Disassembly Process Planning.