Research On Online Control Method For Assembly Process Quality Of Complex Mechanical Products

Complex product, defined as “hybrid structure assembly” with technical requirements, iscomposed of many kinds of parts according to the corresponding process parameters and certainassembly sequence. Complex product assembly process is a serial-parallel-hybrid-multi-stagemanufacturing process.In the process of WIP (Working In Process)flowing to the downstream,product quality attributes are accumulated by the various types of quality characteristics of WIP. Asa result, the quality characteristics of the final product are determined by the coupling qualitycharacteristics in each assembly procedure. Therefore，to realize the online optimization ofassembly quality and dynamic compensation of accumulated errors,from the global perspective, itis significant and pratical to explore the coupling laws in different types of quality characteristicsand design the control optimization strategy for improving the assembly quality stability. Toimprove the assembly quality stability of complex product, from the sight of assembly qualityformation mechanism, the research objects are extended from the assembly sizes to other kinds ofelements such as torque, force. Based on the model-driven philosophy, the integration law and theinteraction mechanism among the different types of the quality characteristics in assembly processare studied, considering the instantiated data of the upstream quality control points, the timelyresponse and adjustment of the on-line quality information are carried out.The research contents and innovations of the dissertation are as follows:1) The concept of quality control points and quality attributes are proposed.Based on networkflow theory, the Correlation-Model between quality attributes and quality control points isestablished, and the constraint relationships among the assembly quality characteristics areexpressed by this model, Correlation-Model can lay the foundation of future research of theassembly quality active control and online optimization.2) The tolerance distribution model of quality control points oriented to assembly quality ispresented to characterize the nonlinear coupling relationships among different types of qualitycontrol points,which provides policy support for online optimization of the quality control points.The optimization strategy is a pattern of model-driven control mode which can well adapt to thesmall-batch flexible manufacturing environment due to being independent of historicalsamples.The chaos theory and two-stage variation strategy are adopted to improve multipleobjective particle swarm optimization (MOPSO). The diversity of pareto optimal set is ensured.3) The assembly quality data chain model with the ability of self-coordination isestablished.The assembly resources, assembly process and intelligent control strategies are integrated into this model to achieve the quality state of WIP of "visualization "and" controllability".The dynamic compensation of error accumulation in assembly process is resolved by real-timeadjustment according to the real-time quality information. The simulation of the model dynamicbehavior is the basis of the system reachability analysis and the development of the online qualitycontrol system.4) To prove the optimization method can effectively improve the assembly quality stability ofcomplex product, two groups of assembly quality data sequences, which are generated from theoptimization strategy and the traditional assembly mode,respectively, are compared by thestatistical theory including the verification of distribution state, variance homogeneity analysis andaverage contrast. To verify the previous assertion, the average membership grade and closenessdegree between the sample sequence and the standard sequence are calculated by the fuzzyassociation analysis.5) To provide technical support for improving the quality stability of the assembly process, theonline quality control system for complex mechanical assembly process is developed, integratedseamlessly with the intelligent computing, telemetry and industrial data transmission networks inthe online quality control system.