Representation and selection of assembly sequences in computer-aided assembly process planning

1997 ◽  
Vol 35 (12) ◽  
pp. 3447-3466 ◽  
Author(s):  
R. B. Gottipolu ◽  
K. Ghosh
Author(s):  
Igor A. Mukhanov

Abstract We have developed a novel, efficient approach for assembly planning for complex products. This approach allows us to reflect the required information for assembly planning efficiently. Our approach has also been successfully used for the mathematical presentation of technological knowledge. An algorithm for the automatic generation of feasible assembly sequences for a given product has been developed. Within the assembly process-planning, feasible sequences are determined depending on the sequential assembly stages of the product. This approach permits the use of different criteria for the selection of a rational assembly plan, and it also allows for the influence of technological system elements (equipment, tools and periphery) on the given part of the product during a interval of the operation. We have successfully applied our approach for assembly process-planning of a complex product, a worm gear box. It has allowed us to reduce computation time greatly and to arrive at the optimal solution to real automated assembly.


2014 ◽  
Vol 575 ◽  
pp. 848-853
Author(s):  
Kai Zhang ◽  
Guo Xi Li ◽  
Jing Zhong Gong ◽  
Bao Zhong Wu ◽  
Meng Zhang ◽  
...  

Due to lack of considering the non-geometric process parameters during assembly process planning, it is difficult to control the production cycle, cost, quality, reliability, stability and consistency of high-performance mechanical systems. To change this situation, a prototype software is developed by taking into account the non-geometric process parameters. Based on the alignment information, this paper concentrates on the data modeling of the system. With the system, the manufacturing process can achieve the assembly materials management, assembly process planning, alignment process monitoring, alignment data collection and statistical analysis. After analyzing the process data, design parameters will be refined and assembly performance will be optimized.


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