科研之友
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摘要
Assembly plan is considered one of the important stages to minimize the cost of manufacturer and to ensure the safety of assembly operation, the main problem of assembly sequence planning approach is how to reduce the deviation from the real manufacture conditions. In this paper, we have extensively investigated a novel approach to automatically generate the assembly sequences for industrial field, which is especially applied to other large-scale structures. A physically based assembly representation model includes not only the pre-determined basic assembly information, such as precedence relations between parts or subassemblies, geometric constraints, different assembly types, and also the dynamic real-time physical properties, such as the center position of gravity, the force strength of the part, et al. This representation model considered the influences on optimum sequences by assembly operations will be modified by the feedback from interactive virtual environment. Then, we select the safety, efficiency and complexity as the optimization objectives. A hybrid search approach may be used to find the optimum assembly sequence, which will be integrated into an interactive assembly virtual environment (IAVE). It means that the results of assembly interaction can be provided to update the assembly planning model as a feedback, by which the approach will take advantages of the immune memory for local optimum search. The user can adjust the assembly sequences with obvious good objective by interaction with IAVE to improve the performance of the search algorithm. We describe human-machine cooperation (HMC) method for ASP in this work, by which human also can play a pivotal role instead of pure soft-computing. A series of numerical experiments are done to validate the performance of the physically based approach (PBA) to generate assembly sequence, which shows the efficiency and the operability to guide the assembly work.
