A neural network based interactive physical programming approach is proposed in this paper. The approximate model of Pareto surface at a given Pareto design is developed based on neural networks, and a map from Pareto designs to their corresponding evaluation values is built. Genetic algorithms is used to find the Pareto design that best satisfies the designer

Hong-Zhong Huang received the B.S. degree from Wuhan University, Wuhan, China, in 1983, the M.S. degree from Chongqing University, Chongqing, China, in 1988, and the Ph.D. degree from Shanghai Jiao Tong University, Shanghai, China, in 1999. He is Professor in the School of Mechanical Engineering at Dalian University of Technology, Dalian, China. He is currently a Visiting Professor of Department of Mechanical Engineering, University of Alberta, Edmonton, Canada. He has published 120 journal articles and 5 books in fields of reliability engineering, optimization design, and fuzzy sets theory. He is a (senior) member of several professional societies, and has served on the boards of several professional societies. His research interests include reliability engineering, robust design, and optimization design.

The contents and meanings of mapping relationships between physical domain and function domain in different design stages, such as conceptual design, detail design and enhancement design, were analyzed. According to the analysis results, the fuzzy mapping between physical domain and function domain in different design stages was established by integrating objective information and subjective information in the design process, such as expert's knowledge, designer's preferences and customer's requirements, where the fuzzy sets, fuzzy mapping and fuzzy transition were used. The property table of structure behavior parameters was established based on the fuzzy mapping relationships. The fuzzy mapping is very important to optimize product structure, perfect product function, meet the diversified and individual requirements of customers. Finally, an example was used to illustrate the fuzzy mapping relationships between physical domain and function domain in different design stages.

The preliminary design optimization of multi-stage spur gear reduction units has been a subject of considerable interest, since many high-performance power transmission applieations (e.g., automotive in the optimal design of multi-stage spur gear reduction unit, such as minimizing the volume and maximizing the surface fatigue life. It is reasonable to formulate the design of spur gear reductio unit as a multi-objective optimization problem, and find an design of spur gear reduction unit as a multi-objective optimization problem. and find an appropriate approach to solve it. In this paper an interactive physical programming approach is developed to place physical programming into an interactive framework in a natural way. Class functions, which are used to represent the designer's preferences on design objectives, are fixed during the interactive physical programming procedure. After a Pareto solution is generated, a preference offset is added into the class function of each objective based on whether the designer would like to improve this objective or sacrifice the objective so as to improve other objectives. The preference offsets are adjusted during the interactive physical programming procedure, and an optimal solution that satisfies the designer's preferences is supposed to be obtained by the end of the procedure. An optimization problem of three-stage spur gear reduction unit is given to illustrate the effectiveness of the proposed approach.

A preliminary analysis of the perturbation fuzzy finite element was provided by Yang et al. (Appl. Math. Mech. 20(7) (1999) 795). In this paper, we provide a detailed analysis of the perturbation fuzzy finite element method based on variational principle. Firstly, on the basis of the second-order perturbation principle of small parameter, the fuzzy functional of total potential energy and the definite perturbation expansions are proposed. Secondly, definite recursion equation of fuzzy variational principle is deduced and fuzzy finite element recursion functional is presented based on fuzzy variational principle. Thirdly, the proposed approach is compared with the conventional fuzzy finite element method. Finally, a numerical example is given to illustrate the method.

In view of the lack of efficient coordination of interdependent task in the collaborative design system, the mechanisms for temporal and resource coordination problems are established based on Petri Nets, respectively. Both of the mechanisms are encapsulated and implemented in the coordination component so as to increase the flexibility and acceptability of the system. We model the CSCW system based on Petri Nets for simulation, analysis and optimization. A case study on the overhead traveling crane is given to demonstrate and validate our theory.

When the failure probability of a system is extremely small or necessary statistical data from the system is scarce, it is very difficult or impossible to evaluate its reliability and safety with conventional fault tree analysis (FTA) techniques. New techniques are needed to predict and diagnose such a system's failures and evaluate its reliability and safety. In this paper, we first provide a concise overview of FTA. Then, based on the posbist reliability theory, event failure behavior is characterized in the context of possibility measures and the structure function of the posbist fault tree of a coherent system is defined. In addition, we define the AND operator and the OR operator based on the minimal cut of a posbist fault tree. Finally, a model of posbist fault tree analysis (posbist FTA) of coherent systems is presented. The use of the model for quantitative analysis is demonstrated with a real-life safety system.

In this paper, a new multiobjective optimization approach named interactive physical programming is proposed and used to solve the reliability and redundancy apportionment optimization problem. Interactive physical programming extends physical programming6 to an interactive framework. After the designer speci es which objectives need to be improved and which objectives can be sacri ced, interactive physical programming can obtain the Pareto solutions satisfying such improving preferences. It has good convergence performance, and can obtain satisfactory design in the end. Interactive physical programming has been successfully applied to a reliability and redundancy apportionment optimization problem. It provides a new e ective approach for reliability optimization.

The feedback information (field data) of the machines from the actual users forms the main data used to analyse their reliability. Due to the fuzziness of the field data, however, it is difficult to analyse their reliability by the field data. Thus, taking the hydraulic truck crane model QY20A as an example, this paper proposed a method to evaluate the reliability of machines with the field data by the fuzzy sets theory. The effectiveness of the method is illustrated through an example. Copyright