Tang Xiaoqing’s research while affiliated with Beihang University and other places

Operations in assembling and joining large size aircraft components are changed to novel digital and flexible ways by digital measurement assisted alignment. Positions and orientations (P&O) of aligned components are critical characters which assure geometrical positions and relationships of those components. Therefore, evaluating the P&O of a component is considered necessary and critical for ensuring accuracy in aircraft assembly. Uncertainty of position and orientation (U-P&O), as a part of the evaluating result of P&O, needs to be given for ensuring the integrity and credibility of the result; furthermore, U-P&O is necessary for error tracing and quality evaluating of measurement assisted aircraft assembly. However, current research mainly focuses on the process integration of measurement with assembly, and usually ignores the uncertainty of measured result and its influence on quality evaluation. This paper focuses on the expression, analysis, and application of U-P&O in measurement assisted alignment. The geometrical and algebraical connotations of U-P&O are presented. Then, an analytical algorithm for evaluating the multi-dimensional U-P&O is given, and the effect factors and characteristics of U-P&O are discussed. Finally, U-P&O is used to evaluate alignment in aircraft assembly for quality evaluating and improving. Cases are introduced with the methodology.

The uncertainty of mechanical assembly process usually brings great challenge to product quality control and assurance. The systematic approach should be employed in the research to find a comprehensive solution. The quality assurance model for assembly (QAMA), based on the analysis of the major problems in the mechanical assembly process and the factors that affect the quality of products, is established by means of three working models: the assembly process model (APM), the activity control model (ACM), and the quality data model (QDM). The APM formulates the assembly process starting with the analysis of process flow, logical scheme, and key factors. The ACM is built by defining the attributes of control activity, mapping relationship between the control activities and its objects in the multiview space and layers. The ACM presents the control flow with the logical relations among control activities as well as the control rules. Based on the two models mentioned above, the QDM supports the acquisition of quality data through data-collecting carriers along assembly process and defines the data structure to support the system model. All of the three models are grouped into a framework which integrates the technical approaches and solutions for quality assurance in mechanical assembly. Based on modeling studies, a computer-integrated and internet-based system called quality assurance system in mechanical assembly (QAS/MA) has been developed. And the development of QAS/MA proves that APM, ACM, QDM, and QAMA are practical and feasible. KeywordsMechanical assembly-Quality assurance-Assembly process model (APM)-Activity control model (ACM)-Quality data model (QDM)