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In-Situ state heat conduction in drilling workpiece results in time-varying temperature field, which affects the final machining accuracy. From the joint action of many factors, such as geometry, material, and thermal convection characteristics, it is difficult to accurately model and describe the time-varying characteristics of the temperature field. Therefore, the time-varying model of the In-Situ state temperature field is analyzed in this paper, which lays a foundation for establishing a high-precision multi-physical field model. First, following the geometric characteristics of the drilling hole and the three-dimensional heat transfer mechanism, the heat transfer model of the drilled part is established, and the relationship between the temperature field and the physical parameters of the workpiece is characterized. Then, combining radial and axial unsteady heat conduction mechanisms, the dimensionless temperature calculation method is adopted to realize the construction of a temperature time-varying model. After that, the model parameters are revised according to the In-Situ state evolution process of the checkpoints. Finally, the experiments are carried out to calculate the credibility of the model. The results show that the prediction model is consistent with the experimental data, and the credibility of non-room temperature dynamic interval is 99.23%, which can effectively reflect the real temperature field conduction process.

To improve the tank aiming accuracy, this paper studies on the nonlinear vibration characteristics caused by the clearance between the barrel and lining. Based on the parameter identification, a free beam modeling method with clearance is proposed. Firstly, based on the Hamilton principle and hypothesis mode method, the free beam dynamic model framework with clearance is established. Secondly, the clearance time-varying stiffness and damping are obtained by the wavelet identification method from experimental data. Hence, the clearance dynamic model is established to describe the nonlinear dynamic behavior accurately. Finally, based on the similarity theory, the scaled model is used to verify the modeling method effectiveness by evaluating the frequency response function (FRF) error between the proposed model and test model. The results show that the FRF relative error is less than 2% between the measured and simulated value based on time-varying parameters, the coincidence index is more than 85%, under the 95% confidence index. It is proved that the dynamic modeling method could improve the barrel-lining dynamic model accuracy effectively with the clearance factor.

Through literature review, found that female college students generally do not love sports, not interested in physical education, understanding of the importance of physical education is insufficient; this paper analyzed through theoretical analysis of the main factors of influencing female college students' interest in sports, found the existing problems and corresponding suggestions are put forward.

Fixture Tolerance is one of the most important factors influencing the machined part accuracy. However caused by the manufacturing error and the assembly error of locator, the workpiece location error should not be neglected, which has led to fixture accuracy decay. A location error verification method is presented to improve the workpiece location accuracy. First, the origin of location error and the transfer process of error between locators and the workpiece are given. Second, random numbers and statistical analysis method are used to simulate locators’ errors. Finally, the location layout optimization model and the process are given. This method can be used to verify the location error and fixture design process.

In order to develop an intelligent Case-based Reasoning system and meet the need of knowledge reuse of fixture design process, ontology technology is integrated in CBR system, Fixture design domain ontology is constructed, and concepts and relations are defined and represented. Semantic annotation of fixture design case is achieved. The similarity estimation approach is presented to resolve the problem of semantic retrieval of fixture design case. Finally, prototype system based on proposed method is introduced and the information retrieval approach is proved efficiently.

It is a common phenomenon that 3D model and 2D engineering drawings are widely used together in modern manufacturing scenario. Therefore it makes a lot of extra tasks to do for both of them which lead to such results as high time consuming, labor intensive during the process. The Model-based Definition (MBD) approach is definitely an effective method to solve above problems. To facility the usage of the MBD Technology, this paper introduces two kinds of MBD model (design-MBD, process-MBD), and describes their contents as well. The paper also focuses on constructing the dMBD model and pMBD model from two aspects: information organization and annotation standard so that these models can guide production more effective.

Most fixture design process are based on the reuse of the previous design knowledge and experience, in this paper, we use a case-based design (CBD) method to design fixture. Based on the analysis of various CBD methods, we found that most methods used to calculate the similarity between new part and cases are too single, so we put forward a method combining the semantic attribute similarity and the shape similarity together, use a weighted algorithm to calculate the similarity. Using this method, we designed a Fixture Design System on CATIA V5 R19, and use this system to retrieve and design fixture, the retrieved results are more close to the new part and reusable, the design process is more efficient.

In the assembly design process of aircraft products, plenty used standard parts make it boring and difficult to extract assembly features and assembly constraints between the products and standard parts.Therefore,in this paper, the practical methodology for light-weight of the tree-dimensional model for rapid assembly and the automatic determination for specification of the parts are proposed. Eventually the assembly for the standard parts can be implemented rapidly, intelligently, in batch, and automatically.

To solve manufacturing resources heterogeneous description and matching problems on cloud manufacturing mode，manufacturing resources modeling and matching technology based on semantic was proposed. The modeling method based on manufacturing feature for manufacturing resources by ontology semantic was presented. Manufacturing resources based on manufacturing feature were encapsulated as manufacturing capacity which can be catch with manufacturing feature of product by semantic similarity. Mapping rules were structured between feature of manufacturing capacity and manufacturing feature of products. Manufacturing capacity evaluation of enterprise was achieved. An application prototype with manufacturing resources modeling and matching based on manufacturing feature was developed.

Automatic generation of manufacturing setup planning is studied in this work. The mathematical model to describe the tolerance information and datum-machining feature relationship has been formulated based on extended graphics. By means of the transformation between the feature tolerance relationship graph(FTG) and the datum-machining feature relationship graph (DMG), the algorithm to automatically generate setup planning has been given based on the tolerance analysis and manufacturing resources capability model. The algorithm can identify the machining feature and datum, optimize setup groups based on the manufacturing resource capability and tolerance analysis, as well as minimize the influence of the locating error stack-up on the machining quality. Finally, a case study of setup planning is presented to verify the feasibility of the methodology.