A Green Design for Assembly Model for Integrated Design Evaluation and Assembly and Disassembly Sequence Planning
A green design for assembly model is presented to
integrate design evaluation and assembly and disassembly sequence
planning by evaluating the three activities in one integrated model. For
an assembled product, an assembly sequence planning model is
required for assembling the product at the start of the product life cycle.
A disassembly sequence planning model is needed for disassembling
the product at the end. In a green product life cycle, it is important to
plan how a product can be disassembled, reused, or recycled, before
the product is actually assembled and produced. Given a product
requirement, there may be several design alternative cases to design
the same product. In the different design cases, the assembly and
disassembly sequences for producing the product can be different. In
this research, a new model is presented to concurrently evaluate the
design and plan the assembly and disassembly sequences. First, the
components are represented by using graph based models. Next, a
particle swarm optimization (PSO) method with a new encoding
scheme is developed. In the new PSO encoding scheme, a particle is
represented by a position matrix defining an assembly sequence and a
disassembly sequence. The assembly and disassembly sequences can
be simultaneously planned with an objective of minimizing the total of
assembly costs and disassembly costs. The test results show that the
presented method is feasible and efficient for solving the integrated
design evaluation and assembly and disassembly sequence planning
problem. An example product is implemented and illustrated in this
paper.
[1] A. C. Lin, and T. C. Chang, "An integrated approach to automated
assembly planning for three-dimensional mechanical products,"
International Journal of Production Research, vol. 31, no. 5, pp.
1201-1227, May 1993.
[2] T. A. Abdullah, K. Popplewell, and C. J. Page, "A review of the support
tools for the process of assembly method selection and assembly
planning," International Journal of Production Research, vol. 41, no. 11,
pp. 2391-2410, July 2003.
[3] H.Y. Lai, and C.T Huang, "A systematic approach for automatic
assembly sequence plan generation," International Journal of Advanced
Manufacturing Technology, vol. 24, pp. 752-763, November 2004.
[4] Y. M. Chen, and C. T. Lin, "A particle swarm optimization approach to
optimization component placement in printed circuit board assembly,"
International Journal of Advanced Manufacturing Technology, vol. 35,
no. 5-6, pp. 610-620, December 2007.
[5] Q. Su, "Computer aided geometric feasible assembly sequence planning
and optimizing," International Journal of Advanced Manufacturing
Technology, vol. 33, pp. 48-57, May 2007.
[6] T. Dong, R. Tong, and L. Zhang, "A knowledge-based approach to
assembly sequence planning," International Journal of Advanced
Manufacturing Technology, vol. 32, pp. 1232-1244, May 2007.
[7] Y.J. Tseng, J.Y. Chen, and F.Y. Huang, "A multi-plant assembly
sequence planning model with integrated assembly sequence planning
and plant assignment using GA," International Journal of Advanced
Manufacturing Technology , vol. 48, no. 1-4, pp. 333-345, April 2010.
[8] S. Jin, W. Cai, X. Lai, and Z. Lin, "Design automation and optimization
of assembly sequences for complex mechanical systems," International
Journal of Advanced Manufacturing Technology, vol. 48, no. 9-12, pp.
1045-1059, June 2010.
[9] Y.-J Tseng, H.-T. Kao, and F-Y. Huang, "Integrated assembly and
disassembly sequence planning using a GA approach," International
Journal of Production Research, vol. 48, no. 20, pp. 5991-6013.
[10] J. Kennedy and R. C. Eberhart, "Particle swarm optimization," in Proc.
1995 IEEE Int. Conf. Neural Networks, Piscataway, NJ, pp. 1942-1948.
[11] J. Kennedy and R. C. Eberhart, "A discrete binary version of the particle
swarm algorithm," in 1997 Proc. Int. Conf. Systems, Man and
Cybernetics, Piscataway, NJ, pp. 4104-4109.
[12] A. Banks, J Vincent, and C. Anyakoha, "A review of particle swarm
optimization. Part II: hybridization, combinatiorial, multicriteria and
constrained optimization, indicative applications," Natural Computing,
vol. 7, no. 1, pp. 109-124, March 2008.
[1] A. C. Lin, and T. C. Chang, "An integrated approach to automated
assembly planning for three-dimensional mechanical products,"
International Journal of Production Research, vol. 31, no. 5, pp.
1201-1227, May 1993.
[2] T. A. Abdullah, K. Popplewell, and C. J. Page, "A review of the support
tools for the process of assembly method selection and assembly
planning," International Journal of Production Research, vol. 41, no. 11,
pp. 2391-2410, July 2003.
[3] H.Y. Lai, and C.T Huang, "A systematic approach for automatic
assembly sequence plan generation," International Journal of Advanced
Manufacturing Technology, vol. 24, pp. 752-763, November 2004.
[4] Y. M. Chen, and C. T. Lin, "A particle swarm optimization approach to
optimization component placement in printed circuit board assembly,"
International Journal of Advanced Manufacturing Technology, vol. 35,
no. 5-6, pp. 610-620, December 2007.
[5] Q. Su, "Computer aided geometric feasible assembly sequence planning
and optimizing," International Journal of Advanced Manufacturing
Technology, vol. 33, pp. 48-57, May 2007.
[6] T. Dong, R. Tong, and L. Zhang, "A knowledge-based approach to
assembly sequence planning," International Journal of Advanced
Manufacturing Technology, vol. 32, pp. 1232-1244, May 2007.
[7] Y.J. Tseng, J.Y. Chen, and F.Y. Huang, "A multi-plant assembly
sequence planning model with integrated assembly sequence planning
and plant assignment using GA," International Journal of Advanced
Manufacturing Technology , vol. 48, no. 1-4, pp. 333-345, April 2010.
[8] S. Jin, W. Cai, X. Lai, and Z. Lin, "Design automation and optimization
of assembly sequences for complex mechanical systems," International
Journal of Advanced Manufacturing Technology, vol. 48, no. 9-12, pp.
1045-1059, June 2010.
[9] Y.-J Tseng, H.-T. Kao, and F-Y. Huang, "Integrated assembly and
disassembly sequence planning using a GA approach," International
Journal of Production Research, vol. 48, no. 20, pp. 5991-6013.
[10] J. Kennedy and R. C. Eberhart, "Particle swarm optimization," in Proc.
1995 IEEE Int. Conf. Neural Networks, Piscataway, NJ, pp. 1942-1948.
[11] J. Kennedy and R. C. Eberhart, "A discrete binary version of the particle
swarm algorithm," in 1997 Proc. Int. Conf. Systems, Man and
Cybernetics, Piscataway, NJ, pp. 4104-4109.
[12] A. Banks, J Vincent, and C. Anyakoha, "A review of particle swarm
optimization. Part II: hybridization, combinatiorial, multicriteria and
constrained optimization, indicative applications," Natural Computing,
vol. 7, no. 1, pp. 109-124, March 2008.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:58788", author = "Yuan-Jye Tseng and Fang-Yu Yu and Feng-Yi Huang", title = "A Green Design for Assembly Model for Integrated Design Evaluation and Assembly and Disassembly Sequence Planning", abstract = "A green design for assembly model is presented to
integrate design evaluation and assembly and disassembly sequence
planning by evaluating the three activities in one integrated model. For
an assembled product, an assembly sequence planning model is
required for assembling the product at the start of the product life cycle.
A disassembly sequence planning model is needed for disassembling
the product at the end. In a green product life cycle, it is important to
plan how a product can be disassembled, reused, or recycled, before
the product is actually assembled and produced. Given a product
requirement, there may be several design alternative cases to design
the same product. In the different design cases, the assembly and
disassembly sequences for producing the product can be different. In
this research, a new model is presented to concurrently evaluate the
design and plan the assembly and disassembly sequences. First, the
components are represented by using graph based models. Next, a
particle swarm optimization (PSO) method with a new encoding
scheme is developed. In the new PSO encoding scheme, a particle is
represented by a position matrix defining an assembly sequence and a
disassembly sequence. The assembly and disassembly sequences can
be simultaneously planned with an objective of minimizing the total of
assembly costs and disassembly costs. The test results show that the
presented method is feasible and efficient for solving the integrated
design evaluation and assembly and disassembly sequence planning
problem. An example product is implemented and illustrated in this
paper.", keywords = "green design, assembly and disassembly sequence
planning, green design for assembly, particle swarm optimization.", volume = "6", number = "6", pages = "1082-7", }