A knowledge-based approach to assembly sequence planning

Assembly planning plays a major role in the manufacturing industry. In order to reduce computational complexity, this paper presents a knowledge-based approach to the assembly sequence planning problem. The CSBAT (connection-semantics-based assembly tree) hierarchy proposed in this paper provides an appropriate way to consider both geometric information and non-geometric knowledge. In this research, the typical or standard CSBAT is applied to a given assembly problem. The structure of the KBASP (knowledge-based assembly sequence planning system) is proposed and there are different ways to construct plans for a CSBAT: by retrieving the typical base, by retrieving the standard base, and by geometric reasoning. The approach proposed in this paper can generate assembly sequences for each CSBAT directly, without the problem of merging plans for different child CSBATs. The application shows that the knowledge-based approach can reduce the computational complexity drastically and obtain more feasible and practical plans.

[1]  Jing Fan,et al.  KVAS: a Knowledge-based Virtual Assembly System , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).

[2]  Zhengxing Sun,et al.  Sketch-based User Interface for Creative Tasks , 2002 .

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

[4]  Kaleem Siddiqi,et al.  Matching Hierarchical Structures Using Association Graphs , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Randall H. Wilson.  Minimizing user queries in interactive assembly planning , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[6]  Jan Wolter,et al.  A structure-oriented approach to assembly sequence planning , 1997, IEEE Trans. Robotics Autom..

[7]  Josef Kittler,et al.  Using relaxation technique for region-based object recognition , 2002, Image Vis. Comput..

[8]  Arthur C. Sanderson,et al.  A correct and complete algorithm for the generation of mechanical assembly sequences , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[9]  Tiam-Hock Enga,et al.  Feature-based assembly modeling and sequence generation , 1999 .

[10]  Chen Zheng.  The Generation of Assembly Precedence Constraint Based on Knowledge , 1998 .

[11]  Boon-Lock Yeo,et al.  Segmentation of Video by Clustering and Graph Analysis , 1998, Comput. Vis. Image Underst..

[12]  Kaleem Siddiqi,et al.  Matching Hierarchical Structures Using Association Graphs , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Jinxiang Dong,et al.  Knowledge-based assembly sequence planning system , 2004, 8th International Conference on Computer Supported Cooperative Work in Design.

[14]  Thomas L. DeFazio,et al.  An integrated computer aid for generating and evaluating assembly sequences for mechanical products , 1991, IEEE Trans. Robotics Autom..

[15]  Satoshi Kanai,et al.  ASPEN: Computer-Aided Assembly Sequence Planning and Evaluation System Based on Predetermined Time Standard , 1996 .

[16]  Hong Yan,et al.  Recognition of handprinted Chinese characters by constrained graph matching , 1998, Image Vis. Comput..

[17]  Zhou-Ping Yin,et al.  A connector-based hierarchical approach to assembly sequence planning for mechanical assemblies , 2003, Comput. Aided Des..

[18]  Xuan F. Zha,et al.  A PDES/STEP-based model and system for concurrent integrated design and assembly planning , 2002, Comput. Aided Des..

[19]  Sukhan Lee.  Subassembly identification and evaluation for assembly planning , 1994, IEEE Trans. Syst. Man Cybern..

[20]  Thomas L. DeFazio,et al.  Simplified generation of all mechanical assembly sequences , 1987, IEEE Journal on Robotics and Automation.

[21]  K. Suzanne Barber,et al.  Design of an experience-based assembly sequence planner for mechanical assemblies , 1998, Robotica.

[22]  F. Dweiri.  Fuzzy development of crisp activity relationship charts for facilities layout , 1999 .

[23]  C. L. Philip Chen,et al.  An integration of neural network and rule-based systems for design and planning of mechanical assemblies , 1993, IEEE Trans. Syst. Man Cybern..

[24]  Kazem Abhary,et al.  Assembly sequence planning and optimisation using genetic algorithms: Part I. Automatic generation of feasible assembly sequences , 2003, Appl. Soft Comput..

[25]  Din-Chang Tseng,et al.  Invariant handwritten Chinese character recognition using fuzzy min-max neural networks , 1997, Pattern Recognit. Lett..

[26]  Ling Zhang,et al.  A collaborative approach to assembly sequence planning , 2005, Adv. Eng. Informatics.

[27]  K. Suzanne Barber,et al.  APE: an experience-based assembly sequence planner for mechanical assemblies , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[28]  Martti Mäntylä,et al.  Functional understanding of assembly modelling , 1994, Comput. Aided Des..

[29]  Ruey-Shun Chen,et al.  A hybrid genetic algorithm approach on multi-objective of assembly planning problem , 2002 .