A disassembly Sequence Planning Approach for maintenance
Abstract
In recent years, more and more research has been conducted in close collaboration with manufacturers to design robust and profitable dismantling systems. Thus, engineers and designers of new products have to consider constraints and disassembly specifications during the design phase of products not only in the context of the end of life but more precisely in the product life cycle. Consequently, optimization of disassembly process of complex products is essential in the case of preventive maintenance. In Fact, Disassembly Sequence Plan (DSP), which is among the combinatorial problems with hard constraints in practical engineering, becomes an NP-hard problem. In this research work, an automated DSP process based on a metaheuristic method named “Ant Colony Optimization” is developed. Beginning with a Computer Aided Design (CAD) model, a collision analysis is performed to identify all possible interferences during the components’ motion and then an interference matrix is generated to identify dynamically the disassembly parts and to ensure the feasibility of disassembly operations. The novelty of the developed approach is presented in the introduction of new criteria such as the maintainability of the usury component with several other criteria as volume, tools change and disassembly directions change. Finally, to highlight the performance of the developed approach, an implemented tool is developed and an industrial case is studied. The obtained results prove the satisfactory side of these criteria to identify a feasible DSP in a record time.
Keywords
Disassembly Sequence Plan Computer Aided Design Interference Analysis Optimization Ant Colony algorithm MaintenancePreview
Unable to display preview. Download preview PDF.
References
- 1.Moore K. E., Gungor A. and Gupta M. S. Petri net approach to disassembly process planning for products with complex AND/OR precedence relationships. Computer and Industrial Engineering, Vol 35, 1998, pp.165-168.Google Scholar
- 2.Chung C.H. and Peng Q.J. An integrated approach to selective-disassembly sequence planning. Robotics & Computer-Integrated Manufacturing, Vol. 21, No. 4, 2005, pp. 475-85.Google Scholar
- 3.Lambert A. J. D. Optimizing disassembly processes subjected to sequence-dependent cost. Computers and Operations Research, Vol 34 (2), 2007, pp. 536-55.Google Scholar
- 4.Grassé, P. P. La reconstruction du nid et les coordinations interindividuelles chez Bellicoitermes natalenis et Cubitermes sp. La théorie de la stigmergie: Essai d’interprétation des termites constructeurs, Insectes Sociaux, Vol. 6, 1959, pp. 41-81.Google Scholar
- 5.Wang J F., Liu J H and Zhong Y. F. Intelligent selective disassembly using the ant colony algorithm. Artificial intelligence for engineering design, analysis and manufacturing, Vol 17, 2003, pp. 325-333.Google Scholar
- 6.Mullen R. J., Monekosso D.; Barman S. and Remagnino P. A review of ant algorithms. Expert Systems with Application, Vol 36, 2009, pp 9608-9617.Google Scholar
- 7.Aghaie A. and Mokhtari H. Ant colony optimization algorithm for stochastic project crashing problem in PERT networks using MC simulation. International Journal of Advance Manufacturing Technology, Vol 45, 2009, pp. 1051–1067.Google Scholar
- 8.Ben Hadj R., Trigui M., and Aifaoui N. Toward an integrated CAD assembly sequence planning solution. Journal of Mechanical Engineering Science, Vol 229, 2014, pp. 2987-3001.Google Scholar
- 9.Kheder M., Trigui M., and Aifaoui N. Disassembly sequence planned based on a genetic algorithm. Journal of Mechanical Engineering Science, Vol 229, 2015, pp. 2281-2290.Google Scholar