Representation, Generation, and Analysis of Mechanical Assembly Sequences With k-ary Operations

Author(s):  
Haixia Wang ◽  
Dariusz Ceglarek

A new methodology is presented to generate all of the assembly sequences for a production system configured as a N-station assembly line with kn (n  = 1, 2,…, N) parts or subassemblies to be assembled at stations 1, 2,…, N, respectively. This expands current approaches in sequence generation applicable for binary assembly process to a k-ary assembly process by including: (i) nonbinary state between two parts, i.e., multiple joints between two parts or subassemblies, is taken into consideration, and (ii) simultaneous assembly of Y (Y≥3) parts or subassemblies. The methodology is based upon proposed k-piece graph and k-piece mixed graph approaches for the assemblies without and with assembly precedence relationship, respectively. Compared with the currently used liaisons graph (or datum flow chain) representation which shows part-to-part assembly relations, the k-piece graph (or k-piece mixed graph) shows all of the feasible subassemblies and their constituent parts and joints (pairs of mating features). Based upon the k-piece graph or k-piece mixed-graph approach, all of the feasible subassemblies for a predetermined assembly line configuration are identified, and all of the sequences for a k-ary assembly process are generated. Case studies are presented to illustrate the advantages of the presented methodology over the state-of-the-art research in assembly sequence generation.

Author(s):  
MVA Raju Bahubalendruni ◽  
Bibhuti Bhusan Biswal

Sequence of feasible mechanical assembly operations plays significant role in overall cost optimisation process for manufacturing industry and thus great importance is given to assembly sequence generation from past four decades. Though achieving at least one feasible sequence is focused in the earlier stages of research, the introduction of soft computing techniques attracted the industrial engineers towards cost-effective, optimised assembly sequences to attain economical manufacturing process. The integration of assembly sequence generation methods with computer aided design environment ensures more correctness and flexibility to automate the process. In this paper, a detailed review on various methods, their applications and limitations is presented and well discussed.


2015 ◽  
Vol 35 (4) ◽  
pp. 309-316 ◽  
Author(s):  
M. V. A. Raju Bahubalendruni ◽  
Bibhuti Bhusan Biswal ◽  
Manish Kumar ◽  
Radharani Nayak

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.


2019 ◽  
Vol 40 (2) ◽  
pp. 319-334 ◽  
Author(s):  
Yanru Zhong ◽  
Chaohao Jiang ◽  
Yuchu Qin ◽  
Guoyu Yang ◽  
Meifa Huang ◽  
...  

Purpose The purpose of this paper is to present and develop an ontology-based approach for automatic generation of assembly sequences. Design/methodology/approach In this approach, an assembly sequence planning ontology is constructed to represent the structure and interrelationship of product geometry information and assembly process information. In the constructed ontology, certain reasoning rules are defined to describe the knowledge and experience. Based on the ontology with reasoning rules, the algorithm for automatically generating assembly sequences is designed and implemented. Findings The effectiveness of this approach is verified via applying it to generate the assembly sequences of a gear reducer. Originality/value The main contribution of the paper is presenting and developing an ontology-based approach for automatically generating assembly sequences. This approach can provide a feasible solution for the issue that mathematics-based assembly sequence generation approaches have great difficulty in explicitly representing assembly experience and knowledge.


Author(s):  
MVA Raju Bahubalendruni ◽  
Bibhuti Bhusan Biswal

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.


2015 ◽  
Vol 6 (3) ◽  
pp. 83-87 ◽  
Author(s):  
Marcin Suszyński ◽  
Jan Żurek

Abstract The purpose of the paper is to explore the problem of modeling technological assembly process, particularly generating assembly sequence for parts and machinery sets. A new computer program Msassembly is introduced. The program was invented by the authors on the basis of an algorithm for determining assembly sequence for parts and machinery sets. The algorithm is based on hypergraphs and directed graphs, as well as on assessment of transitions between assembly states. The principles of operation of Msassembly are presented on the example of modelling the assembly sequence of a ball joint. At the end of the paper, research findings are submitted.


2010 ◽  
Vol 97-101 ◽  
pp. 3243-3246
Author(s):  
Yan Feng Xing ◽  
Yan Song Wang ◽  
Xiao Yu Zhao

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.


2020 ◽  
Vol 14 (1) ◽  
pp. 6-17
Author(s):  
Atsuko Enomoto ◽  
Noriaki Yamamoto ◽  
Yoshio Yamamura ◽  
Yoshio Sugawara ◽  
◽  
...  

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.


2011 ◽  
Vol 230-232 ◽  
pp. 978-981
Author(s):  
Yan Feng Xing ◽  
Yan Song Wang ◽  
Xiao Yu Zhao

This paper proposes a genetic algorithm to generate and optimize assembly sequences for compliant assemblies. An assembly modeling is presented to describe the geometry of the assembly, which includes three sets of parts, relationships and joints among the parts. Based on the assembly modeling, an assembly sequence is denoted as an individual, which is assigned an evaluation function that consists of the fitness and constraint functions. The fitness function is used to evaluate feasible sequences; in addition, the constraint function is employed to evolve unfeasible sequences. The genetic algorithm starts with a randomly initial population of chromosomes, evolves new populations by using reproduction, crossover and mutation operations, and terminates until acceptable sequences output. Finally an auto-body side assembly is used to illustrate the algorithm of assembly sequence generation and optimization.


1999 ◽  
Vol 11 (4) ◽  
pp. 315-320 ◽  
Author(s):  
Takeshi Murayama ◽  
◽  
Bungo Takemura ◽  
Fuminori Oba ◽  

The authors propose acquiring heuristic rules automatically for generating assembly sequences efficiently. Heuristic rules are reduced from training examples by inductive learning. Additional training examples are made from information on assembly sequences and used for modifying heuristic rules. As the assembly sequence generation and modification of heuristic rules are executed more, heuristic rules are refined and assembly sequences are generated efficiently. An experiment demonstrated the effectiveness of the approach.


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