“disassembly plan approach based on subassembly concept”

Trigui, Mœz; Belhadj, Imen; Benamara, Abdelmajid

doi:10.1007/s00170-016-9363-0

Cited by 36 publications

(20 citation statements)

References 20 publications

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“…The optimal solution for the four-part product is shown in figure 6. The EPCM results in 2 parallel possible subassemblies compared to the solution listed in the past literature [26][27][28].…”

Section: Resultsmentioning

confidence: 99%

“…A comparative assessment has been made for the proposed EPCM with existing methods on the Reduction Gear Box assembly with 17-parts is shown in figure 7 [10,28].…”

Section: Comparative Assessmentmentioning

confidence: 99%

“…Although AI based techniques were only developed and using to address this problem, the completeness to solve all assembly configurations is questionable due to non-consideration of all the necessary assembly predicates [26]. The existing sub-assembly identifications methods, identify the parallel possible sets and then perform linear assembly sequence planning [10,[27][28][29][30][31]. Even these studies lack completeness in generating the optimal solution and burdens high computational time [32].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Assembly Sequence generation through computational approach

Bahubalendruni¹,

Gulivindala²,

Varupala³

et al. 2019

Sādhanā

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Optimal assembly sequence (OAS) is always an interesting aspect for an industrial engineer to minimize assembly time and cost, which gives number of assembly levels and sequence of assembly operations. An assembly sequence with more number of parallel possible stable sub-assemblies significantly reduces the overall assembly time for large scale products. Finding such optimal sequences from huge set of all assembly sequences (SAAS) is challenging due to involvement of multiple assembly feasibility validation criteria namely; assembly coherence, geometric feasibility, part stability and mechanical feasibility. In this paper, an efficient computational method is proposed to generate optimal assembly sequences. The method considers extended assembly stability relations to identify stable sub-assemblies for parallel execution. The method is proven in generating optimal solutions for any given product effectively. The method is well discussed and compared with prominent computational methods with suitable product illustrations.

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Section: Resultsmentioning

confidence: 99%

“…A comparative assessment has been made for the proposed EPCM with existing methods on the Reduction Gear Box assembly with 17-parts is shown in figure 7 [10,28].…”

Section: Comparative Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Assembly Sequence generation through computational approach

Bahubalendruni¹,

Gulivindala²,

Varupala³

et al. 2019

Sādhanā

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show abstract

“…Belhadj et al [10] identify parts with many connections, large surface area, and large volume as candidates to support nearby parts in a sub-assembly. They build on this work in [6] by requiring that parts assigned to the subassembly have a stronger connection to the subassembly than to the remainder of the assembly. Lee et al [13] focus on the forces required to separate a subassembly and define subassemblies as the grouping that relieves the most disassembly forces at once, found by max-flow min-cut [14].…”

Section: Related Work a Subassembly Identificationmentioning

confidence: 99%

“…Subassemblies accrue neighbors by evaluating their connecting surfaces. They continue this work with [6] with a different collection of assembly problems. This method was chosen because it is representative of state of the art methods that use the connectivity and geometric relationships between parts to identify subassemblies.…”

Section: Subassembly Generation From Cad Belhadj 2017mentioning

confidence: 99%

Assembly Planning by Subassembly Decomposition Using Blocking Reduction

Watson

Hermans

2019

IEEE Robot. Autom. Lett.

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The sequence in which a complex product is assembled directly impacts the ease and efficiency of the assembly process, whether executed by a human or a robot. A sequence that gives the assembler the greatest freedom of movement is therefore desirable. Our main contribution is an expression of obstruction relationships between parts as a disassembly interference graph (DIG). We validate this heuristic by developing a disassembly sequence planner that partitions assemblies in a way that prioritizes access to parts, resulting in plans that are comparable in efficiency to two state-of-the-art assembly methods in terms of total plan length. Using DIG, our method generates successive subassembly decompositions, yielding a tree structure that makes parallization opportunities apparent. Our planner generates viable disassembly plans by minimizing our part blockage measure, and thereby demonstrates that this measure is a valuable addition to the Assembly Sequence Planning toolkit.

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