An effective integration approach toward assembly sequence planning and evaluation

An integration strategy for assembly sequence planning and sequence scheme evaluation is proposed. This strategy can be used to plan a reasonable assembly sequence, to optimize a sequence scheme, and to predict whether a collision will occur between the assembly tool and assembled components by considering factors like target components and assembly resources.A hybrid method is presented for assembly sequence modeling that combines human-computer interactive operations to manually build a hierarchical assembly sequence main model and a hybrid graph method to automatically generate sub-assembly sequence schemes of the main model. An optimization algorithm based on time-cost is introduced to handle a best candidate components selection. This relieves the problem of limited capability found when handling large size assembly models with traditional methods. The essential issues involved in system implementation are discussed as well; these include a representation method for the assembly consequence model, an optimization model of assembly sequence planning, and an object-oriented system architecture model employed with multi-agent technology for visually evaluating the assembling process.This system, KM computer-aided assembly process planning, KMCAAPP, has been developed on the basis of our previous work, KMCAD3; KMCAAPP uses the presented approach. KMCAAPP can be integrated with CAD model from KMCAD3D. A case study shows that the presented approach can use large CAD assembly models and delivers a feasible and effective way to integrate the assembly sequence planning process with scheme evaluation by visually evaluating the assembling process. This allows the identification of design errors in a timely manner and mitigates economic loss.

[1]  Arthur C. Sanderson,et al.  A correct and complete algorithm for the generation of mechanical assembly sequences , 1991, IEEE Trans. Robotics Autom..

[2]  Diqing Hu,et al.  Mechanical Product Disassembly Sequence and Path Planning Based on Knowledge and Geometric Reasoning , 2002 .

[3]  Christian Mascle Feature-based assembly model for integration in computer-aided assembly , 2002 .

[4]  Leora Morgenstern,et al.  Motivated Action Theory: a Formal Theory of Causal Reasoning , 1994, Artif. Intell..

[5]  S. Tor,et al.  A Novel Representation Scheme for Disassembly Sequence Planning , 2002 .

[6]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[7]  Arthur C. Sanderson,et al.  AND/OR graph representation of assembly plans , 1986, IEEE Trans. Robotics Autom..

[8]  Yanxi Liu,et al.  Planning for assembly from solid models , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[9]  A. J. Clewett,et al.  Introduction to sequencing and scheduling , 1974 .

[10]  Lawrence Davis,et al.  Applying Adaptive Algorithms to Epistatic Domains , 1985, IJCAI.

[11]  Wayne Wobcke,et al.  Intelligent Agent Systems Theoretical and Practical Issues , 1996, Lecture Notes in Computer Science.

[12]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[13]  Jean-Claude Latombe,et al.  Geometric Reasoning About Mechanical Assembly , 1994, Artif. Intell..

[14]  Chengqi Zhang,et al.  Multi-Agent Systems Methodologies and Applications , 1996, Lecture Notes in Computer Science.