Assembly Sequence Planning for Aircraft Component Based on Improved Clashes Matrix

The aircraft parts contain the information of a great number of curves and surfaces, which makes it a big challenge for the aircraft components’ Assembly Sequence Planning (ASP) processes. The traditional interference matrix has limitation of expressing the assembly direction and can easily lead to the failure of ASP optimization. Hence, an improved interference matrix is provided in this paper to deal with the aircraft ASP problem based on the Genetic Algorithms (GA). With the mainly consideration of assembly time according to the assembly sequence evaluation criteria, the objective function is established and evaluated. This paper presents an application of the method in the aircraft cabin door assembly process supported by an 863 program. Meanwhile, the verification of the approach is shown in the practical example on MATLAB platform.

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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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A New Crossover Operator for Assembly Sequence Planning by Genetic Algorithms

Volume 5: 5th Flexible Assembly Conference ◽

10.1115/96-detc/fas-1359 ◽

1996 ◽

Author(s):

Milad Fares Sebaaly ◽

Hideo Fujimoto

Keyword(s):

Genetic Algorithms ◽

Decision Process ◽

Genetic Material ◽

Assembly Sequence Planning ◽

Assembly Sequence ◽

Crossover Operator ◽

Optimal Sequence ◽

Sequence Planning ◽

Complete Set ◽

Maximum Transmission

Abstract Assembly Sequence Planning (ASP) is the generation of the best or optimal sequence to assemble a certain product, given its design files. Although many planners were introduced in research to solve this problem automatically, it is still solved manually in many advanced assembly firms. The reason behind this is that most introduced planners are very sensitive to large increases in product parts. In fact, most of these planners seek the exact solution, while performing a part basis decision process. As a result, they are trapped in tedious and exhaustive search procedures, which make them inefficient and sometimes obsolete. To overcome these difficulties, Sebaaly and Fujimoto (1996) introduced a new concept of ASP based on Genetic Algorithms application, where the search procedure is performed on a sequence population basis rather than a part basis, and a best sequence is generated without searching the complete set of potential candidates. This paper addresses the problem of improving the GA performance for assembly application, by introducing a new crossover operator. The genetic material can be divided and classified as ‘good’ or ‘bad’. The new crossover insures the maximum transmission of ‘good’ features from one generation to another. This results in a faster GA convergence. The performance of the new algorithm is compared with that of the ordinary matrix crossover for a modified industrial example, where it proved to be faster and more efficient.

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Optimizing assembly sequence planning using precedence graph-based assembly subsets prediction method

Assembly Automation ◽

10.1108/aa-02-2019-0031 ◽

2019 ◽

Vol 40 (2) ◽

pp. 361-375 ◽

Cited By ~ 1

Author(s):

Nan Zhang ◽

Zhenyu Liu ◽

Chan Qiu ◽

Weifei Hu ◽

Jianrong Tan

Keyword(s):

High Efficiency ◽

Prediction Method ◽

Solution Space ◽

Assembly Sequence Planning ◽

Selection Strategy ◽

Assembly Process ◽

Assembly Sequence ◽

Content Type ◽

Sequence Planning ◽

Precedence Graph

Purpose Assembly sequence planning (ASP) plays a vital role in assembly process because it directly influences the feasibility, cost and time of the assembly process. The purpose of this study is to solve ASP problem more efficiently than current algorithms. Design/methodology/approach A novel assembly subsets prediction method based on precedence graph is proposed to solve the ASP problem. The proposed method adopts the idea of local to whole and integrates a simplified firework algorithm. First, assembly subsets are generated as initial fireworks. Then, each firework explodes to several sparks with higher-level assembly subsets and new fireworks are selected for next generation according to selection strategy. Finally, iterating the algorithm until complete and feasible solutions are generated. Findings The proposed method performs better in comparison with state-of-the-art algorithms because of the balance of exploration (fireworks) and exploitation (sparks). The size of initial fireworks population determines the diversity of the solution, so assembly subsets prediction method based on precedence graph (ASPM-PG) can explore the solution space. The size of sparks controls the exploitation ability of ASPM-PG; with more sparks, the direction of a specific firework can be adequately exploited. Practical implications The proposed method is with simple structure and high efficiency. It is anticipated that using the proposed method can effectively improve the efficiency of ASP and reduce computing cost for industrial applications. Originality/value The proposed method finds the optimal sequence in the construction process of assembly sequence rather than adjusting order of a complete assembly sequence in traditional methods. Moreover, a simplified firework algorithm with new operators is introduced. Two basic size parameters are also analyzed to explain the proposed method.

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Research on Aircraft Assembly Sequence Planning Technology Based on Key Characteristics

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.328.9 ◽

2013 ◽

Vol 328 ◽

pp. 9-16 ◽

Cited By ~ 1

Author(s):

Zhan Lei Sun ◽

Peng Fei Han ◽

Gang Zhao

Keyword(s):

Process Design ◽

Assembly Sequence Planning ◽

Assembly Process ◽

Assembly Sequence ◽

Assembly Quality ◽

Constraint Matrix ◽

Aircraft Assembly ◽

Sequence Planning ◽

Key Characteristics ◽

Assembly Sequences

Assembly Sequence Planning (ASP) is an essential question for aircraft assembly process design. Modern aircraft assembly contains plenty of complex shape components, which have so many assembly features to ensure, this leads to a large number of feasible assembly sequences using traditional sequence planning algorithms; and it is hard to evaluate the contribution to assembly quality for every sequence. A methodology called Key Characteristics Based ASP is proposed in this paper, which can significantly reduce unavailable sequences and ensure key features for quality in assembly process designing compared with previous methods. The methodology focuses on the final assembly quality and considers it as Assembly Key Characteristics (AKCs) in the beginning of assembly process design. With tools such as AKCs decomposition, Datum Flow Chain, precedence constraint matrix, the methodology describes the main process for ASP. To verify the technologys effectiveness, this paper presents an application of the algorithm in an aircraft component assembly by an 863 program.

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The Two Phased Method of Hull Block Assembly Sequence Planning

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.421.235 ◽

2011 ◽

Vol 421 ◽

pp. 235-239

Author(s):

Shi Peng Qu ◽

Zu Hua Jiang

Keyword(s):

Constraint Satisfaction ◽

Constraint Satisfaction Problem ◽

Assembly Sequence Planning ◽

Assembly Process ◽

Assembly Model ◽

Assembly Sequence ◽

Hierarchical Assembly ◽

Sequence Planning ◽

Whole Process ◽

Block Based

A hull block assembly sequence planning (ASP) problem is modeled as a constraint satisfaction problem where the precedence relations between operations are considered constraints. In order to generate the proper assembly sequence of the hull block, we analyzed the structure features of the block and built the hierarchical assembly model of the block. Based on this model, we divided the whole process of the block assembly into the small subassembly phase and the unit subassembly phase. There exists the rule that the assembly process of the subassembly in the same phase is similar, and it's different to the subassembly in the different phases. So, we proposed the different methods to plan the assembly sequence of the different phases. An example is given to illustrate that this two phased method can solves the block ASP problem effectively and accurately.

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Process Operators and Their Roles in Integrated Assembly Process Planning

Volume 4: 3rd Design for Manufacturing Conference ◽

10.1115/detc98/dfm-5753 ◽

1998 ◽

Author(s):

Zhi-Kui Ling ◽

XiangYu Zhou ◽

Chuck Mclean

Keyword(s):

Process Planning ◽

Physical Simulation ◽

Resource Planning ◽

Assembly Sequence Planning ◽

Assembly Process ◽

Assembly Sequence ◽

Assembly Process Planning ◽

Sequence Planning ◽

Assembly Design ◽

Assembly Simulation

Abstract An environment to facilitate assembly process planning is proposed in this study. It includes a design support system with two agents supporting the assembly process. One is assembly design agent, and the other is a geometric design agent. The assembly design agent consists of three modules: the assembly sequence planning module, the assembly resource planning module, and the assembly simulation module. The assembly sequence-planning module takes the design information and generates an assembly sequence. This sequence is structured in a tree form, called the Constructive Assembly Tree (CAT). The leaf nodes of the tree correspond to the components of the product. The intermediate nodes are the assembly process operators, each of which characterizes a particular assembly operation, and their associated subassemblies. The resource module assigns the necessary tools, fixtures, supply bins and other resources to each of the process operators. The assembly simulation module traverses a CAT, extracts the necessary assembly information, and drives external physical simulation/animation system to perform virtual assembly simulation/animation process.

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An Approach for Assembly Sequence Planning by Genetic Algorithms

IEEE Latin America Transactions ◽

10.1109/tla.2016.7530396 ◽

2016 ◽

Vol 14 (5) ◽

pp. 2066-2071 ◽

Cited By ~ 1

Author(s):

Gabriel Pedraza ◽

Maybel Diaz ◽

Hassan Lombera

Keyword(s):

Genetic Algorithms ◽

Assembly Sequence Planning ◽

Assembly Sequence ◽

Sequence Planning

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Process Knowledge Integrated Assembly Sequence Planning for Control Panel

International Journal of Automation Technology ◽

10.20965/ijat.2020.p0006 ◽

2020 ◽

Vol 14 (1) ◽

pp. 6-17

Author(s):

Atsuko Enomoto ◽

Noriaki Yamamoto ◽

Yoshio Yamamura ◽

Yoshio Sugawara ◽

◽

...

Keyword(s):

Assembly Sequence Planning ◽

Control Panel ◽

Assembly Process ◽

Assembly Sequence ◽

Automated Assembly ◽

Process Knowledge ◽

Sequence Planning ◽

Sequence Generation ◽

Assembly Sequence Generation

Completely automated assembly sequence planning for control panels is proposed. The proposed algorithm generates the manufacturing bill of material for the assembly processes and total assembly sequence. The algorithm integrates the knowledge of assembly process into a near optimum assembly sequence generation.

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