Study on the generation of optimal assembly sequence based on a tree model

2006 ◽  
Author(s):  
Dai Guohong ◽  
Zhang Youliang ◽  
You Fei
Keyword(s):  
Assembly Sequence ◽  
Tree Model ◽  
Optimal Assembly

Practical Passive Assembly: Gripper Design and Assembly Sequence Optimization

1999 ◽  
Author(s):  
Jayavardhan N. Marehalli ◽  
Robert H. Sturges
Keyword(s):  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Automatic Assembly ◽  
Assembly Sequence ◽  
Feedback Systems ◽  
Preferred Direction ◽  
Ideal Orientation ◽  
Index Of Difficulty ◽  
Optimal Assembly ◽  
The Ideal

Abstract For efficient assembly without feedback systems (or, passive assembly), the assembler should know the ideal orientation of each component and the assembly sequence. A heuristic presented here finds an optimal assembly sequence and prescribes the orientation of the components for a minimum set of grippers — ideally one. The heuristic utilizes an index of difficulty (ID) that quantifies assembly. The ID for each task in the assembly process is computed based on a number of geometrical and operational properties. The objective of the optimization problem here is to minimize the assembly ID and categorize parts/subassemblies based on their preferred direction of assembly while allowing re-orientation of the base part. It is assumed that the preferred direction of assembly is vertically downwards consistent with manual as well as most automatic assembly protocols. Our attempt is to minimize the number of degrees of freedom required in a re-orienting fixture and mathematically derive the requirements for such a fixture. The assembly of a small engine is used as an example in this study due to the variety of ideally rigid parts involved.

Petri Net Models for Assembly Sequences Planning

2007 ◽  
Vol 10-12 ◽  
pp. 411-415 ◽  
Author(s):  
Y.L. Fu ◽  
R. Li ◽  
H.B. Feng ◽  
Y.L. Ma
Keyword(s):  
Petri Net ◽  
Assembly Sequence Planning ◽  
Assembly Model ◽  
Assembly Sequence ◽  
Assembly Operation ◽  
Knowledge Based ◽  
Assembly Sequences ◽  
Model Size ◽  
Assembly Sequences Planning ◽  
Optimal Assembly

Assembly sequences can be represented by a Petri net(PN) which characterizes dynamic system changes and provides a tool for obtaining optimal assembly sequences. In this study some assembly operation constraints are considered in order to obtain more practical sequences which are conformed to real situations. In order to enhancing the efficiency of the assembly sequence planning, knowledge-based Petri net, combining an usual Petri net with expert’s knowledge and experiences, is proposed to construct the assembly model. With the complexity of the product, the product’s assembly model size will be too large to analysis. So the basic subnets are used to reduce the large PN. And the reduced version can be used for the analysis of the original PN. To verify the validity and efficiency of the approach, a variety of assemblies including some complicated products from industry are tested, and the corresponding results are also presented.

Influence of assembly predicate consideration on optimal assembly sequence generation

2015 ◽  
Vol 35 (4) ◽  
pp. 309-316 ◽  
Author(s):  
M. V. A. Raju Bahubalendruni ◽  
Bibhuti Bhusan Biswal ◽  
Manish Kumar ◽  
Radharani Nayak
Keyword(s):  
Low Cost ◽  
Problem Formulation ◽  
Search Space ◽  
Computational Time ◽  
Assembly Sequence ◽  
Content Type ◽  
Sequence Generation ◽  
Assembly Sequences ◽  
Assembly Sequence Generation ◽  
Optimal Assembly

Purpose – The purpose of this paper is to find out the significant influence of assembly predicate consideration on optimal assembly sequence generation (ASG) in terms of search space, computational time and possibility of resulting practically not feasible assembly sequences. An appropriate assembly sequence results in minimal lead time and low cost of assembly. ASG is a complex combinatorial optimisation problem which deals with several assembly predicates to result an optimal assembly sequence. The consideration of each assembly predicate highly influences the search space and thereby computational time to achieve valid assembly sequence. Often, the ignoring an assembly predicate leads to inappropriate assembly sequence, which may not be physically possible, sometimes predicate assumption drastic ally raises the search space with high computational time. Design/methodology/approach – The influence of assuming and considering different assembly predicates on optimal assembly sequence generation have been clearly illustrated with examples using part concatenation method. Findings – The presence of physical attachments and type of assembly liaisons decide the consideration of assembly predicate to reduce the complexity of the problem formulation and overall computational time. Originality/value – Most of the times, assembly predicates are ignored to reduce the computational time without considering their impact on the assembly sequence problem irrespective of assembly attributes. The current research proposes direction towards predicate considerations based on the assembly configurations for effective and efficient ASG.

scholarly journals Robotic Optimal Assembly Sequence Using Improved Cuckoo Search Algorithm

2018 ◽  
Vol 133 ◽  
pp. 323-330 ◽  
Author(s):  
Gunji Bala Murali ◽  
Bbvl Deepak ◽  
Bb Biswal ◽  
Golak Bihari Mohanta ◽  
Amruta Rout
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Assembly Sequence ◽  
Improved Cuckoo Search Algorithm ◽  
Optimal Assembly

A Methodology for Assembly Sequence Optimization by Hybrid Cuckoo-Search Genetic Algorithm

2018 ◽  
Vol 17 (01) ◽  
pp. 47-59 ◽  
Author(s):  
G. V. S. K. Karthik ◽  
Sankha Deb
Keyword(s):  
Genetic Algorithm ◽  
Cuckoo Search ◽  
Metaheuristic Algorithm ◽  
Assembly Sequence ◽  
Sequence Optimization ◽  
Assembly Sequences ◽  
Ga Algorithm ◽  
The Cost ◽  
The Given ◽  
Optimal Assembly

In this paper, we have proposed and implemented a methodology for assembly sequence optimization by using a nature-inspired metaheuristic algorithm, known as hybrid cuckoo-search genetic algorithm (CSGA). The cost criteria for optimization in the present formulation takes into consideration the total assembly time and the number of reorientations during the assembly process. To demonstrate the application of the CSGA, an example assembly containing 19 parts has been presented and the results have been compared with those of another metaheuristic algorithm, Genetic Algorithm (GA). From the results, it has been observed that for the given problem, the CSGA not only produces optimal assembly sequences with costs comparable to that of GA, but the convergence of CSGA algorithm has been found to be faster than the GA algorithm.

An intelligent approach towards optimal assembly sequence generation

2016 ◽  
Vol 232 (4) ◽  
pp. 531-541 ◽  
Author(s):  
MVA Raju Bahubalendruni ◽  
Bibhuti Bhusan Biswal
Keyword(s):  
Objective Function ◽  
Efficient Method ◽  
Assembly Sequence ◽  
Sequence Generation ◽  
Computational Performance ◽  
Assembly Sequences ◽  
Working Principle ◽  
Assembly Sequence Generation ◽  
Intelligent Approach ◽  
Optimal Assembly

In this paper, a novel and efficient method is developed and proposed to obtain all valid assembly sequences and optimized assembly sequence for a given assembled product. The working principle of methodology is clearly illustrated with different example products. Four basic predicates namely “liaison predicate, geometrical feasibility, mechanical feasibility, and stability” are considered to validate each sequence. The proposed method is effective and proven efficient in the resulting all set of feasible assembly sequences described. Tool/gripper changes, assembly orientation changes, and part trajectory distances are considered to state the optimality of a valid assembly sequence. Achieving optimized assembly sequence through the proposed method for user-defined objective function is briefly illustrated. The computational performance of the method in achieving all valid assembly sequences is illustrated for various dissimilar products.

A Particle Swarm Algorithm for Assembly Sequence Planning

2010 ◽  
Vol 97-101 ◽  
pp. 3243-3246
Author(s):  
Yan Feng Xing ◽  
Yan Song Wang ◽  
Xiao Yu Zhao
Keyword(s):  
Particle Swarm ◽  
Tolerance Analysis ◽  
Assembly Sequence Planning ◽  
Particle Swarm Algorithm ◽  
Assembly Sequence ◽  
Sequence Generation ◽  
Assembly Sequences ◽  
Swarm Algorithm ◽  
Assembly Sequence Generation ◽  
Optimal Assembly

A particle swarm algorithm is proposed to generate optimal assembly sequences for compliant assemblies. Firstly, the liaison graph and the adjacency matrix describe the geometry of the compliant assemblies. An assembly sequence is represented by a character string, whose length is the number of all parts. The conceptual tolerance analysis is used to evaluate feasible sequences. Thereafter, the particle swarm algorithm is presented to generate assembly sequences, in which the elite ratio is applied to improve optimization results. Finally a fender assembly is used to illustrate the algorithm of assembly sequence generation and optimization.

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