QUALITY FUNCTION DEPLOYMENT IN BOTTOM-UP PROCESS FOR DESIGN REUSE

To deal with a bottom up process model for design reuses a specific extended house of quality(EHOQ)is proposed Two kinds of supported functions,basic supported functions and new supported functions,are defined.Two processes to determine two kinds of functions are presented A kind of EHOQ matrix for a company is given and its management steps are studied.

DESIGN REUSE METHOD FOR ASSEMBLIES IN CONCEPT DESIGN

Aiming at difficult sorting and retrieving complicated structure assembliesin assembly lib, a method for compartmentalizing assembly design resource by conceptual productstructure model is presented. The similar assembly retrieval mechanisms of symbol assembly relationgraph matching and symbol assembly relation graph similarity are discussed. The method is validatedby taking valve rod assemblies as example.

A Model for the Design Process Gene Based on the Extensible Basic-element and the Mutation of the Design Process Gene

In this paper a method is developed to model the design process gene based on the extensible basic-element with the purpose of design process optimization and reuse. First, the principle of genetic engineering based design process optimization and reuse is put forward and analyzed. Second, the extensible basic-element model of the design process gene is established based on the models of the design process base and the base pair through analyzing the concept and structure of the design process gene and the extensible basic-element as well as its extensibility. Third, the features of divergence and scalability of the extensible basic-element model of the design process gene are discussed for carrying out the extension translation to the design process gene by way of inserting, deleting and updating design process bases. Finally, an example of building extensible basic-element models for the design process base, base pair and design process gene in mechanical product design and the mutation process of the design process gene in airplane design is presented which demonstrates the application of the method proposed in this paper.

The Analysis of Frequency Reuse Irregular Patterns in Mobile Telephone Network

Some frequency reuse irregular patterns in radionetwork design are proposed,the characteristic and applica-tion measures of these patterns are analyzed.Then this paperaccounts that frequency reuse irregular patterns is a usefulway to impove spectrum efficiency and it is significative forartificial intelligence to be applied in this field.

Semantic Driven Design Reuse for 3D Scene Modeling

The increasing scale and complexity of 3D scene design work urge an efficient way to understand the design in multi-disciplinary team and exploit the experiences and underlying knowledge in previous works for reuse.However the previous researches lack of concerning on relationship maintaining and design reuse in knowledge level.We propose a novel semantic driven design reuse system,including a property computation algorithm that enables our system to compute the properties while modeling process to maintain the semantic consistency,and a vertex statics based algorithm that enables the system to recognize scene design pattern as universal semantic model for the same type of scenes.With the universal semantic model,the system conducts the modeling process of future design works by suggestions and constraints on operation.The proposed framework empowers the reuse of 3D scene design on both model level and knowledge level.

A deep learning approach to the classification of 3D CAD models

Model classification is essential to the management and reuse of 3D CAD models.Manual model classification is laborious and error prone.At the same time,the automatic classification methods are scarce due to the intrinsic complexity of 3D CAD models.In this paper,we propose an automatic 3D CAD model classification approach based on deep neural networks.According to prior knowledge of the CAD domain,features are selected and extracted from 3D CAD models first,and then preprocessed as high dimensional input vectors for category recognition.By analogy with the thinking process of engineers,a deep neural network classifier for 3D CAD models is constructed with the aid of deep learning techniques.To obtain an optimal solution,multiple strategies are appropriately chosen and applied in the training phase,which makes our classifier achieve better performance.We demonstrate the efficiency and effectiveness of our approach through experiments on 3D CAD model datasets.