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The dynamic modeling and trajectory tracking control of a mobile robot is handled by a hierarchical constraint approach in this study. When the wheeled mobile robot with complex generalized coordinates has structural constraints and motion constraints, the number of constraints is large and the properties of them are different. Therefore, it is difficult to get the dynamic model and trajectory tracking control force of the wheeled mobile robot at the same time. To solve the aforementioned problem, a creative hierarchical constraint approach based on the Udwadia–Kalaba theory is proposed. In this approach, constraints are classified into two levels, structural constraints are the first level and motion constraints are the second level. In the second level constraint, arbitrary initial conditions may cause the trajectory to diverge. Thus, we propose the asymptotic convergence criterion to deal with it. Then, the analytical dynamic equation and trajectory tracking control force of the wheeled mobile robot can be obtained simultaneously. To verify the effectiveness and accuracy of this methodology, a numerical simulation of a three-wheeled mobile robot is carried out.

The teaching of the traditional mold courses focus on the illustration of theoretical knowledge. Therefore, associating the design, evaluation, and manufacture links as a whole is difficult. Students cannot shape system knowledge, thereby making the study difficult. In addition, traditional teaching cannot meet the current enterprise needs of talents who have mold CAD/CAE/CAM technology. This study presents a teaching method that applies CAD/CAE/CAM technology to mold teaching. First, the positive effects of these technologies on the mold design and manufacturing process are introduced. Thereafter, lamp cover is used as an example to establish a series of computer-aided teaching development processes using existing software for mold design, mold flow analysis, and machining simulation. Lastly, survey results demonstrate that the effects of the proposed teaching method are better than the traditional method. Moreover, students and enterprises are substantially recognized in this teaching method.

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In most Cloud Manufacturing (CMfg) systems, Design Resource (DR) is encapsulated into cloud service under a fine-grained condition. However, due to the small granularity of DRs provided by cloud provider, it is difficult for the cloud services to match with design tasks if there is no initiative resource. For example, because of the lack of initiative perception capabilities, it is difficult for design software to match with design tasks directly. A method of DR multi-granularity modeling with two-stage aggregation is proposed, by which the resource granularity is increased and dynamic design capability is formed. In the proposed DR multi-granularity model, DRs are classified into three granularities: Static Physical Resource (SPR), Dynamic Capacity Resource (DCR), and Cross-functional Design Unit (CDU). Their ontology models are set up to represent the basic function, structure and component of DRs. In the two-stage aggregation of DRs, two strategies are proposed to increase the granularity of DRs. The first is DCR aggregation strategy based on auxiliary resources actively pushing, and the second is CDU aggregation strategy based on meta task and meta capability matching. Using the operation parameters of DRs and the associated evaluation matrix, a method of DCR and CDU evaluation is proposed to optimize the searched DRs. With the help of the preceding multi-granularity DR modeling and the two-stage access strategy, DR granularity is enlarged and initiative design capability is formed, which solves the problem of DRs matching with design tasks because of small resource granularity.

Mechanical design course covers various contents, and most of them are complex theoretical knowledge. However, current teaching modes in China mainly combine textbook with PPT (PowerPoint) created in advance. This monotonous mode cause students to lose interests in their curriculum, and knowledge becomes difficult to gain. To improve teaching effectiveness, we propose a novel teaching mode by applying simulation technology to a particular mechanical design course. Using the chapter of gear transmission as an example, we also introduce a specific approach. Comparing traditional modes with the proposed mode, we demonstrate that combining simulation analysis technology with the content of mechanical design course can enrich the teaching process and improve students’ learning interests. The proposed approach can also help students analyze and solve problems with relevant knowledge and enhance their practical abilities. Thus, these students can satisfy the requirements of modern society for mechanical engineering graduates.

In order to prevent a roof fall accident of a coal mine roadway mining face, temporary support must be provided before the permanent support of the roadway. At present, the commonly used forepoling bar support has poor reliability and low efficiency, and other machine-mounted or self-moving temporary supports are also difficult to use widely due to the complex geological conditions and limited working space at the heading face. On the basis of the mechanical characteristics analysis and numerical simulation of the wall rock support system, we propose a temporary support scheme that can adapt to the uneven roof of the roadway and the complex geological conditions on site, and that can ensure the cooperative operation of multiple equipment on site. A self-moving temporary support (SmTS) is designed, and its mechanical characteristics are analyzed to meet the mechanical requirements of the wall rock support system on the mining face. The multiobjective optimization of the main beam structure based on response surface methodology (RSM) is carried out to eliminate the design redundancy on the premise of meeting the support requirements of the main beam. Our research provides a novel method and corresponding equipment for the temporary support of a mining face. Applications of the proposed approach in the 7900 mining area of a mine proves the effectiveness of the method and equipment.

Automatic Feature Recognition (AFR) is considered as the key connection technique of the integration of Computer Aided Design (CAD) and Computer Aided Process Planning (CAPP). At present, there is a lack of a systematic method to identify and evaluate the local features of 3D CAD models. The process information such as topological structure, shape and size, tolerance and surface roughness should be considered. Therefore, a novel Model Based Definition (MBD) based on 3D CAD model AFR and similarity evaluation are proposed in this paper. A Multi-Dimensional Attributed Adjacency Matrix (MDAAM) based on MBD is established based on the fully consideration of the topological structure, shape and size, surface roughness, tolerance and other process information of the B-rep model. Based on the MDAAM, a two-stage model local feature similarity evaluation method is proposed, which combines the methods of optimal matching and adjacency judgment. First, the faces of source feature and target model are used as independent sets to construct a bipartite graph. Secondly, supplement the vertices in the independent set of source feature to make the number of vertices in two independent sets equal. Thirdly, based on MDAAM data, the weighted complete bipartite graph is constructed with the face similarity between two independent sets as the weight. Fourthly, Kuhn-Munkres algorithm is used to calculate the optimal matching between the faces of source feature and target model. Fifthly, the adjacency between matching faces in target model is judged. Finally, the similarity between matching faces of the two models is calculated, which is used as the similarity evaluation result. The effectiveness of this method is verified by three applications.INDEX TERMS Automatic feature recognition, similarity evaluation, multi-dimensional attributed adjacency matrix, weighted complete bipartite graph, Kuhn-Munkres algorithm.