Deviation matrix and asymptotic variance for GI/M/1-type Markov chains

We investigate deviation matrix for discrete-time GI/M/1-type Markov chains in terms of the matrix-analytic method, and revisit the link between deviation matrix and the asymptotic variance. Parallel results are obtained for continuous-time GI/M/1-type Markov chains based on the technique of uniformization. We conclude with A. B. Clarke＇s tandem queue as an illustrative example, and compute the asymptotic variance for the queue length for this model.

Improved Quality Prediction Model for Multistage Machining Process Based on Geometric Constraint Equation

Product variation reduction is critical to improve process efficiency and product quality, especially for multistage machining process（MMP）. However, due to the variation accumulation and propagation, it becomes quite difficult to predict and reduce product variation for MMP. While the method of statistical process control can be used to control product quality, it is used mainly to monitor the process change rather than to analyze the cause of product variation. In this paper, based on a differential description of the contact kinematics of locators and part surfaces, and the geometric constraints equation defined by the locating scheme, an improved analytical variation propagation model for MMP is presented. In which the influence of both locator position and machining error on part quality is considered while, in traditional model, it usually focuses on datum error and fixture error. Coordinate transformation theory is used to reflect the generation and transmission laws of error in the establishment of the model. The concept of deviation matrix is heavily applied to establish an explicit mapping between the geometric deviation of part and the process error sources. In each machining stage, the part deviation is formulized as three separated components corresponding to three different kinds of error sources, which can be further applied to fault identification and design optimization for complicated machining process. An example part for MMP is given out to validate the effectiveness of the methodology. The experiment results show that the model prediction and the actual measurement match well. This paper provides a method to predict part deviation under the influence of fixture error, datum error and machining error, and it enriches the way of quality prediction for MMP.

Perturbation analysis for continuous-time Markov chains

We investigate perturbation for continuous-time Markov chains(CTMCs) on a countable state space. Explicit bounds on ?D and D are derived in terms of a drift condition, where ? and D represent the perturbation of the intensity matrices and the deviation matrix, respectively. Moreover, we obtain perturbation bounds on the stationary distributions, which extends the results by Liu(2012) for uniformly bounded CTMCs to general(possibly unbounded) CTMCs. Our arguments are mainly based on the technique of augmented truncations.

Precise calibration of a rotation photogrammetric system

Rotation photogrammetric systems are widely used for 3D information acquisition,where high-precision calibration is one of the critical steps.This study first shows how to derive the rotation model and deviation model in the object space coordinate system according to the basic structure of the system and the geometric relationship of the related coordinate systems.Then,overall adjustment of multi-images from a surveying station is employed to calibrate the rotation matrix and the deviation matrix of the system.The exterior orientation parameters of images captured by other surveying stations can be automatically calculated for 3D reconstruction.Finally,real measured data from Wumen wall of the Forbidden City is employed to verify the performance of the proposed calibration method.Experimental results show that this method is accurate and reliable and that a millimetre level precision can be obtained in practice.