This paper researches on the levitation and drag forces of Halbach permanent-magnet electrodynamic suspension. First, construct an analytical model to calculate the magnetic field in the air gap and the current in the secondary conductor plate, thus deducing analytical expressions of the levitation and drag forces. Second, establish a 2D and a 3D finite element model, using ANSYS. Finally, at different speeds, from 0 to 250 km/h, compare the forces calculating results through the above three methods. Results generating from the 2D-FEM and the analytical algorithm have less than 3% of relative error, but for having not taken the horizontal components of eddy current in the reaction plate into consideration, thus 10% more than the 3D-FEM calculating results.

As performance of processes in a manufacturing system determines the quality of product, the factors that have effects on the processes need to be taken into account to guarantee the product quality during manufacturing. As impacting factors’ effects are usually qualitatively described and hence result in difficulties of quantifying and evaluating, this paper proposes organizing a group of experts to evaluate the effects of the impacting factors and applying a fuzzy Impact-Matrix method to quantify the evaluation results. The proposed method provides engineers with a general perspective to identify important impacting factors and thus facilitates the control of processes.

Fuzzy linear regression has been extensively studied since its inception symbolized by the work of Tanaka et al. in 1982. As one of the main estimation methods, fuzzy least squares approach is appealing because it corresponds, to some extent, to the well known statistical regression analysis. In this article, a restricted least squares method is proposed to fit fuzzy linear models with crisp inputs and symmetric fuzzy output. The paper puts forward a kind of fuzzy linear regression model based on structured element, This model has precise input data and fuzzy output data, Gives the regression coefficient and the fuzzy degree function determination method by using the least square method, studies the imitation degree question between the observed value and the forecast value.

The definition of process system reliability was provided. The study focused on the process reliability model with the quality parameter as index. Taking into account the effect of error propagation in working procedures on the whole process, it proposed the calculating methods of working procedures and process system reliability, which can effectively evaluate the ability of process subsystem in fulfilling design requirement.