Solving Assembly Sequence Planning Using Distance Evaluated Simulated Kalman Filter

This paper presents an implementation of simulated Kalman filter (SKF) algorithm for optimizing an assembly sequence planning (ASP) problem. The SKF search strategy contains three simple steps; predict-measure-estimate. The main objective of the ASP is to determine the sequence of component installation to shorten assembly time or save assembly costs. Initially, permutation sequence is generated to represent each agent. Each agent is then subjected to a precedence matrix constraint to produce feasible assembly sequence. In this paper, the distance evaluated SKF (DESKF) is proposed for solving ASP problem. The performance of the proposed DESKF is compared against previous works in solving ASP by applying BGSA, BPSO, and MSPSO. Using a case study of ASP, the results show that DESKF outperformed all the algorithms in obtaining the best solution.

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Assembly Modeling for 3D Component Based on Polychromatic Sets

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.411.388 ◽

2011 ◽

Vol 411 ◽

pp. 388-392 ◽

Cited By ~ 3

Author(s):

Yun Long Li ◽

Jian Min Gao ◽

Lei Shi ◽

Song Wang

Keyword(s):

Information Matrix ◽

Spatial Location ◽

Assembly Sequence Planning ◽

Assembly Model ◽

Assembly Sequence ◽

Assembly Modeling ◽

Sequence Planning ◽

Location Modeling ◽

Dynamic Interference

In order to improve the efficiency of assembly modeling and provide a complete assembly model for assembly sequence planning (ASP), a method of assembly modeling based on polychromatic sets (PS) is proposed. Firstly, the assembly information of 3D Component is obtained by API function in SolidWorks. In addition, assembly incident matrix, information matrix and mapping matrix are built. On the basis of these matrixes, a method of location modeling is explored. The interference relation matrix is developed by judging the spatial location and analyzing dynamic interference relation among parts. Finally, a case study is given to verify the method.

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A case study of energy efficient assembly sequence planning problem

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/469/1/012013 ◽

2019 ◽

Vol 469 ◽

pp. 012013 ◽

Cited By ~ 1

Author(s):

M A Abdullah ◽

M F F Ab Rashid ◽

Z Ghazali ◽

A N M Rose

Keyword(s):

Energy Efficient ◽

Assembly Sequence Planning ◽

Planning Problem ◽

Assembly Sequence ◽

Sequence Planning

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Solving Assembly Sequence Planning using Angle Modulated Simulated Kalman Filter

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/319/1/012044 ◽

2018 ◽

Vol 319 ◽

pp. 012044 ◽

Cited By ~ 2

Author(s):

Ainizar Mustapa ◽

Zulkifli Md. Yusof ◽

Asrul Adam ◽

Badaruddin Muhammad ◽

Zuwairie Ibrahim

Keyword(s):

Kalman Filter ◽

Assembly Sequence Planning ◽

Assembly Sequence ◽

Sequence Planning

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Genetic simulated annealing algorithm-based assembly sequence planning

International Technology and Innovation Conference 2006 (ITIC 2006) ◽

10.1049/cp:20061017 ◽

2006 ◽

Cited By ~ 11

Author(s):

Shan Hongbo ◽

Li Shuxia ◽

Gong Degang ◽

Lou Peng

Keyword(s):

Simulated Annealing ◽

Simulated Annealing Algorithm ◽

Assembly Sequence Planning ◽

Assembly Sequence ◽

Sequence Planning ◽

Genetic Simulated Annealing Algorithm ◽

Annealing Algorithm

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Optimization of Assembly Sequence Planning of Turbine Low-pressure Rotor Blades Based on the Improved Simulated Annealing Algorithm

Journal of Physics Conference Series ◽

10.1088/1742-6596/1939/1/012098 ◽

2021 ◽

Vol 1939 (1) ◽

pp. 012098

Author(s):

Liu Jun-kong ◽

LI Li-li

Keyword(s):

Simulated Annealing ◽

Simulated Annealing Algorithm ◽

Low Pressure ◽

Assembly Sequence Planning ◽

Rotor Blades ◽

Assembly Sequence ◽

Sequence Planning ◽

Annealing Algorithm

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Geometrical and physical cost evaluation for robot assembly sequence planning

Proceedings of IEEE International Conference on Intelligent Engineering Systems ◽

10.1109/ines.1997.632468 ◽

2002 ◽

Cited By ~ 3

Author(s):

H. Mosemann ◽

F. Rohrdanz ◽

F.M. Wahl

Keyword(s):

Assembly Sequence Planning ◽

Cost Evaluation ◽

Assembly Sequence ◽

Sequence Planning

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Using memetic algorithms with guided local search to solve assembly sequence planning

Expert Systems with Applications ◽

10.1016/j.eswa.2006.05.025 ◽

2007 ◽

Vol 33 (2) ◽

pp. 451-467 ◽

Cited By ~ 40

Author(s):

Hwai-En Tseng ◽

Wen-Pai Wang ◽

Hsun-Yi Shih

Keyword(s):

Local Search ◽

Memetic Algorithms ◽

Assembly Sequence Planning ◽

Assembly Sequence ◽

Guided Local Search ◽

Sequence Planning

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An approach to multi-criteria assembly sequence planning using genetic algorithms

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-008-1576-4 ◽

2008 ◽

Vol 42 (1-2) ◽

pp. 180-188 ◽

Cited By ~ 29

Author(s):

Young-Keun Choi ◽

Dong Myung Lee ◽

Yeong Bin Cho

Keyword(s):

Genetic Algorithms ◽

Assembly Sequence Planning ◽

Assembly Sequence ◽

Sequence Planning

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Applications of Mating Conditions in Assembly Sequence Planning Task

Volume 2: 24th Design Automation Conference ◽

10.1115/detc98/dac-5612 ◽

1998 ◽

Author(s):

Pongsak Dulyapraphant ◽

Tulga Ozsoy

Keyword(s):

Degrees Of Freedom ◽

Tolerance Analysis ◽

Assembly Sequence Planning ◽

Assembly Model ◽

Assembly Sequence ◽

Kinematics Analysis ◽

Sequence Planning ◽

Planning Task ◽

Intuitive Interface ◽

Mating Conditions

Abstract Because of their intuitive interface, mating conditions have been prevalently used in assembly modelling. Besides their use for modelling purposes, other type of information, such as spatial relationships between parts and local degrees of freedom, can be directly derived from mating conditions. This information in turn can be used in various engineering analysis applications, such as kinematics analysis or automatic tolerance chain generation for tolerance analysis. In this paper, application of mating conditions in an assembly sequence-planning task is investigated. The proposed approach mainly engages the mating information represented in the CAD assembly model to automatically generate sequence plans based on the minimization of the number of assembly directions.

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