An enhanced genetic algorithm for automated assembly planning

Smith, Greg C.; Smith, Shana

doi:10.1016/s0736-5845(02)00029-7

Cited by 88 publications

(41 citation statements)

References 14 publications

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“…De Lit et al developed a GA to generate assembly trees, and used a system expert to choose optimal sequence [17]. In addition, Smith and Smith provided an automated assembly planning based on an enhanced GA which was more reliable and quicker than usual GA [18]. Tseng et al used an improved GA called memetic algorithm to generate feasible assembly sequences with large constraints using the connector concept [19].…”

Section: Assembly Sequence Planningmentioning

confidence: 99%

An assembly oriented design framework for product structure engineering and assembly sequence planning

Demoly¹,

Yan²,

Eynard³

et al. 2011

Robotics and Computer-Integrated Manufacturing

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The paper describes a novel framework for an Assembly-Oriented Design (AOD) approach as a new functional part of the Product Lifecycle Management (PLM) strategy, by considering product design and assembly sequence planning phases concurrently. Integration issues of product lifecycle into the product development process have received much attention over the last two decades, especially at the detailed design stage. The main objective of the research is to define assembly sequence into preliminary design stages by introducing and applying assembly process knowledge in order to provide an assembly context for the product development process, particularly for product structuring. The proposed framework highlights a novel algorithm based on a mathematical model integrating boundary conditions related to DFA rules, engineering decisions for assembly sequence and the product structure definition. This framework has been implemented in a new system called PEGASUS considered as an AOD module for a PLM system. A case study of applying the framework to a Catalytic-Converter and Diesel Particulate Filter sub-system, belonging to an exhaust system from an industrial automotive supplier, is introduced to illustrate the efficiency of the proposed AOD methodology. The work described has not been submitted elsewhere for publication, in whole or in part, and all the authors listed have approved the manuscript that is enclosed. Cover Letter *Cover LetterAn Assembly-Oriented Design Framework for Product Structure Engineering and Assembly Sequence Planning _______________________________________________________________________________________________ Abstract:The paper describes a novel framework for an Assembly-Oriented Design (AOD) approach as a new functional part of the Product Lifecycle Management (PLM) strategy, by considering product design and assembly sequence planning phases concurrently. Integration issues of product lifecycle into the product development process have received much attention over the last two decades, especially at the detailed design stage. The main objective of the research is to define assembly sequence into preliminary design stages by introducing and applying assembly process knowledge in order to provide an assembly context for the product development process, particularly for product structuring. The proposed framework highlights a novel algorithm based on a mathematical model integrating boundary conditions related to DFA rules, engineering decisions for assembly sequence and the product structure definition. This framework has been implemented in a new system called PEGASUS considered as an AOD module for a PLM system. A case study of applying the framework to a Catalytic-Converter and Diesel Particulate Filter sub-system, belonging to an exhaust system from an industrial automotive supplier, is introduced to illustrate the efficiency of the proposed AOD methodology.

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Section: Assembly Sequence Planningmentioning

confidence: 99%

An assembly oriented design framework for product structure engineering and assembly sequence planning

Demoly¹,

Yan²,

Eynard³

et al. 2011

Robotics and Computer-Integrated Manufacturing

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“…Many GA-based approaches have been successful in the field of assembly planning [11,[21][22][23][24]. Based on results of the research, a GA is proved superior to traditional graph or matrix-based searching methods.…”

Section: Genetic Algorithm-based Assembly Planningmentioning

confidence: 99%

Tool Selection-Embedded Optimal Assembly Planning

Chung¹,

Peng²

2011

PCEEA

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“…The amount of effort required also increases dramatically with the number of parts in a product. The approaches can find high-quality solutions or even global-optimal solutions, but cannot find high-quality solutions quickly for complex products [6].…”

Section: Introductionmentioning

confidence: 99%

A novel ant colony algorithm for assembly sequence planning

Wang

Liu

Zhong

2004

Int J Adv Manuf Technol

162

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An ant colony algorithm-based approach to assembly sequence generation and optimization of mechanical products is presented in this article. For diverse assemblies, the approach generates different amount of ants cooperating to find optimal solutions with the least reorientations during assembly processes. Based on assembly by disassembly philosophy, a candidate list composed by feasible and reasonable disassembly operations that are derived from disassembly matrix guides sequences construction in the solution space expressed implicitly, and so guarantees the geometric feasibility of sequences. The state-transition rule and local-and global-updating rules are defined to ensure acquiring of the optimal solutions. Cases are given to show the effectiveness of the proposed approach, and the characteristics of the algorithm are discussed.

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An enhanced genetic algorithm for automated assembly planning

Cited by 88 publications

References 14 publications

An assembly oriented design framework for product structure engineering and assembly sequence planning

An assembly oriented design framework for product structure engineering and assembly sequence planning

Tool Selection-Embedded Optimal Assembly Planning

A novel ant colony algorithm for assembly sequence planning

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