Assembly sequence optimization based on hybrid symbiotic organisms search and ant colony optimization

Assembly sequence optimization aims to find the optimal or near-optimal assembly sequences under multiple assembly constraints. Since it is NP-hard for complex assemblies, the heuristic algorithms are widely used to find the optimal or near-optimal assembly sequences in an acceptable computation time. Considering the multiple assembly constraints, an assembly model is presented for assembly sequence optimization. Then, the hybrid symbiotic organisms search and ant colony optimization is used to find the optimal or near-optimal assembly sequences. The symbiotic organisms search has a relatively strong global optimization capability but weak local optimization capability. On the other hand, the ant colony optimization has the relatively strong local optimization capability for assembly sequence optimization even though the parameters are not optimized. The hybrid symbiotic organisms search and ant colony optimization take advantages of their capacities for assembly sequence optimization. The case study demonstrates that the hybrid symbiotic organisms search and ant colony optimization finds the better assembly sequences within less iteration than the individual ant colony optimization and symbiotic organisms search in most experiments under the same preconditions.

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

[2]  Franco Failli,et al.  Optimization of Disassembly Sequences for Recycling of End-of-Life Products by Using a Colony of Ant-Like Agents , 2001, IEA/AIE.

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

[4]  Junfeng Wang,et al.  A novel ant colony algorithm for assembly sequence planning , 2005 .

[5]  Hoda A. ElMaraghy,et al.  Knowledge-based model for constructing master assembly sequence , 2015 .

[6]  Bibhuti Bhusan Biswal,et al.  Optimal Assembly Sequence Planning Using Hybridized Immune-Simulated Annealing Technique , 2017 .

[7]  Fuminori Oba,et al.  ASSEMBLY SEQUENCE PLANNING USING K-NEAREST-NEIGHBOR RULE , 2007 .

[8]  Min-Yuan Cheng,et al.  Symbiotic Organisms Search: A new metaheuristic optimization algorithm , 2014 .

[9]  Alfred J.D. Lambert,et al.  Disassembly Modeling for Assembly, Maintenance, Reuse and Recycling , 2004 .

[10]  Sai Cheong Fok,et al.  Integrated knowledge-based assembly sequence planning , 1998 .

[11]  Sukhan Lee,et al.  Assembly planning based on subassembly extraction , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[12]  Geoffrey Boothroyd,et al.  Product design for manufacture and assembly , 1994, Comput. Aided Des..

[13]  Thomas Stützle,et al.  Ant Colony Optimization , 2009, EMO.

[14]  Hui Wang,et al.  Mechanical assembly planning using ant colony optimization , 2014, Comput. Aided Des..

[15]  Marco Santochi,et al.  Automated Sequencing and Subassembly Detection in Assembly Planning , 1992 .

[16]  Ihsan Sabuncuoglu,et al.  Ant colony optimization for the single model U-type assembly line balancing problem , 2009 .

[17]  Sabry Ahmed Haroun,et al.  A Performance Comparison of GA and ACO Applied to TSP , 2015 .

[18]  Hans Kurt Tönshoff,et al.  A knowledge-based system for automated assembly planning , 1992 .

[19]  F. Bonneville,et al.  A genetic algorithm to generate and evaluate assembly plans , 1995, Proceedings 1995 INRIA/IEEE Symposium on Emerging Technologies and Factory Automation. ETFA'95.

[20]  Moez Trigui,et al.  Assembly sequences plan generation using features simplification , 2018, Adv. Eng. Softw..

[21]  C. A. van Luttervelt,et al.  The Use of Heuristics in Assembly Sequence Planning , 1989 .

[22]  Morteza Ghobakhloo,et al.  A technical comment on “a review on assembly sequence planning and assembly line balancing optimisation using soft computing approaches” , 2014 .

[23]  Hamzah Ahmad,et al.  An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm , 2015 .

[24]  Damian M. Lyons,et al.  Assembly and task planning: a taxonomy , 1994, IEEE Robotics & Automation Magazine.

[25]  Saeid Motavalli,et al.  Multi-criteria assembly sequencing , 1997 .

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

[27]  Chun-Ting Huang,et al.  Disassembly matrix for disassembly processes of products , 2002 .

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

[29]  Y. Wang,et al.  Chaotic particle swarm optimization for assembly sequence planning , 2010 .

[30]  Z. H. Che,et al.  A multi-objective optimization algorithm for solving the supplier selection problem with assembly sequence planning and assembly line balancing , 2017, Comput. Ind. Eng..

[31]  Arthur C. Sanderson,et al.  Representations of mechanical assembly sequences , 1991, IEEE Trans. Robotics Autom..

[32]  Simeng Liu,et al.  Assembly sequence planning for reflector panels based on genetic algorithm and ant Colony optimization , 2016, The International Journal of Advanced Manufacturing Technology.

[33]  Aderemi Oluyinka Adewumi,et al.  Discrete symbiotic organisms search algorithm for travelling salesman problem , 2017, Expert Syst. Appl..

[34]  Hongbo Shan,et al.  Research on assembly sequence planning based on genetic simulated annealing algorithm and ant colony optimization algorithm , 2009 .

[35]  Santosh D. Dalvi.  Optimization of Assembly Sequence Plan Using Digital Prototyping and Neural Network , 2016 .