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Computer supported collaborative work (CSCW) technology is used to solve the resource-sharing problems in collaborative design, analysis, and manufacture. To address this need, a system called CollabVue for collaborative product design between designers and manufacturers is proposed in this study. This paper first introduces the framework of tolerance analysis system based on CollabVue, and then discusses the utilization of geometric topology information in 3D model to resolve the problem of dimension information input and the related specific operations. Based on object-oriented technology, a new data structure to interactively pick up and store dimension information is established. Finally the model uses iterative method to compute technological dimension chain equation.

This work presents a study of a new adaptive sampling strategy for the construction of explicit boundaries using Support Vector Machines (SVMs), referred to as Explicit Design Space Decomposition (EDSD). The new adaptive sampling strategy called local minimum point is based on choosing the sample on the current SVM boundary with the minimum distance to the most important support for the current SVM. The proposed scheme can not only prevent locking the SVM boundary and balance the negative class and positive one, but also be used as a main refining scheme. And the ability of this scheme was illustrated by two analytical functions, a three dimensional problem and a five dimensional problem.

Purpose -The purpose of this paper is to present a study of the parallelization of the construction of explicit constraints or limit-state functions using support vector machines. These explicit boundaries have proven to be beneficial for design optimization and reliability assessment, especially for problems with large computational times, discontinuities, or binary outputs. In addition to the study of the parallelization, the objective of this article is also to provide an approach to select the number of processors. Design/methodology/approach -This article investigates the parallelization in two ways. First, the efficiency of the parallelization is assessed by comparing, over several runs, the number of iterations needed to create an accurate boundary to the number of iterations associated with a theoretical "linear" speedup. Second, by studying these differences, an "appropriate" range of parallel processors can be inferred. Findings -The parallelization of the construction of explicit boundaries can lead to a markedly reduced computational burden. The study provides an approach to select the number of processors for an optimal use of computational resources. Originality/value -The construction of explicit boundaries for design optimization and reliability assessment is designed to alleviate many hurdles in these areas. The parallelization of the construction of the boundaries is a much needed study to reinforce the efficacy and efficiency of this approach.

Response surface method (RSM) is widely used in structural reliability analysis with implicit performance function (PF) which requires formidable computational effort. The ill conditioned coefficient matrix of normal equation in classical RSM prevents it from being used in high order conditions. The stochastic response surface method (SRSM), deriving from classical RSM, offers one alternative to solve this problem. Yet the regression method of conventional SRSM is based on normal least square method which ignores the different significance of each sample point through which the response surface function (RSF) is formed. To yield RSF close to the limit state which leads to better estimation of probability of failure, this paper introduces the weighted regression into SRSM and several examples with hypothetic explicit PF are given to test the performance of SRSM. In addition, we use this method in the fatigue reliability analysis of crankshaft with implicit PF. All these examples demonstrate the advantages of the proposed method.