Study On The Key Technologies Of The Spatial Assembly Sequence Planning

Assembly sequence planning (ASP) is one of the hot research topics in concurrent engineering (CE). There are two key issues in ASP: (1) Geometric feasible assembly sequence planning;(2) Assembly sequences evaluating and the optimal sequences selecting. In this thesis, the spatial ASP problem is explored systematically and the related key techniques are study thoroughly.Firstly, focus on the geometric feasible assembly sequence reasoning, the OBB box and separation axis theory are integrated into the geometry constraints analysis (GCA) theory. A 3D-GCA method is proposed by which the 3D assembly precedence relations (APRs) can be derived correctly and completely. Thereafter, all the spatial geometric feasibly assembly sequences can be derived accordingly.Secondly, focus on the assembly sequence evaluation, 4 criteria, i.e., assembly angle (AA), assembly direction (AD), reorientation (RE), and stability (ST) are proposed. The calculate processes of each criterior are designed based on 3D-GCA method. Furthermore, an entropy theory based fuzzy comprehensive evaluation method is proposed for the optimal sequences selection.Moreover, to overcome the NP hard problem in large scale ASP, an Immune Genetic Algorithm(IGA)is proposed. In this algorithm, the antibody is selected based on the information entropy. Meanwhile, four kinds of vaccine, i.e., KP, BP, NT, and NL are defined. A number of numerical tests demonstrate that IGA is much better than simply genetic algorithm (SGA).Finaly, a hierarchical approach is proposed for ASP reasoning of the sophasitic products. And the corresponding computer aided system named spatial assembly sequence planning system (SASPS) is developed. A case study demonstrates that this system can reason out the optimal sequences in four steps as assembly modeling, 3D-GCA reasoning, assembly evaluation functions calculating, and IGA based optimal sequences searching.