Assembly sequence planning using soft computing methods: A review

Deepak, B. B. V. L.; Murali, Gunji Bala; Bahubalendruni, M. V. A. Raju; Biswal, Bibhuti Bhusan

doi:10.1177/0954408918764459

Cited by 63 publications

(25 citation statements)

References 88 publications

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“…The raise in computational complexities is directly proportional to increase in the part count of the product and application of assembly predicates involvement in the method (Yu et al, 2013;Bahubalendruni et al, 2019). Artificial intelligent (AI) methods attracted most of the research interest because of its availability at the current stage and ease of solution development at reasonable computations (Mishra and Sankha, 2019;Deepak et al, 2019). Zhang developed a hybrid AI algorithm by immune algorithm and particle swarm optimization (PSO) on popular DeFazio and Whitney industrial model and inverter battery assembly to develop an assembly sequence plan from detected two-part SAs (Zhang et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A heuristic method with a novel stability concept to perform parallel assembly sequence planning by subassembly detection

Gulivindala¹,

Bahubalendruni²,

Varupala³

et al. 2020

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Purpose Parallel assembly sequence planning (PASP) reduces the overall assembly effort and time at the product development stage. Methodological difficulties at framework development and computational issues at their implementation made the PASP complex to achieve. This paper aims to propose a novel stability concept for subassembly detection to minimize the complexities in PASP. Design/methodology/approach In this research, a heuristic method is developed to identify, represent and implement the stability predicate to perform subassembly detection and assembly sequence planning (ASP) at the further stages. Stability is organized into static, dynamic, enriched and no stability between the mating assembly parts. The combination of parts that possesses higher fitness is promoted to formulate the final solution about PASP. Findings The results obtained by applying the proposed concept on complex configurations revealed that stability predicate plays a dominant role in valid subassembly detection and final sequence generation further. Originality/value The value of the presented study lies in the three types of stability conditions and effective integration to existed ASP method. Unlike the existed heuristics in subassembly detection, the proposed concept identifies the parallel subassemblies during ASP.

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Section: Introductionmentioning

confidence: 99%

A heuristic method with a novel stability concept to perform parallel assembly sequence planning by subassembly detection

Gulivindala¹,

Bahubalendruni²,

Varupala³

et al. 2020

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show abstract

“…To achieve an automated-product manufacturing line, assembly sequences must be generated rapidly. Studies have focused on using 3D computer-aided design (CAD) models at the product design stage for automatic assembly sequence generation [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Assembly Sequences Based on Multiple Criteria Against Products with Deformable Parts

Kiyokawa,

Takamatsu,

Ogasawara

2020

Preprint

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This study investigates assembly sequence generation by considering two tradeoff objectives: (1) insertion conditions and (2) degrees of constraints among assembled parts. A multiobjective genetic algorithm is used to balance these two objectives for planning robotic assembly. Furthermore, the method of extracting part relation matrices including interference-free, insertion, and degree of constraint matrices is extended for application to 3D computer-aided design (CAD) models, including deformable parts. The interference of deformable parts with other parts can be easily investigated by scaling models. A simulation experiment was conducted using the proposed method, and the results show the possibility of obtaining Pareto-optimal solutions of assembly sequences for a 3D CAD model with 33 parts including a deformable part. This approach can potentially be extended to handle various types of deformable parts and to explore graspable sequences during assembly operations.

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“…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]. Hence the current research work is aimed to develop an efficient computational method to address parallel assembly systems with stable sub-assembly identification by considering all the necessary assembly predicates.…”

Section: Introductionmentioning

confidence: 99%

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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Assembly sequence planning using soft computing methods: A review

Cited by 63 publications

References 88 publications

A heuristic method with a novel stability concept to perform parallel assembly sequence planning by subassembly detection

A heuristic method with a novel stability concept to perform parallel assembly sequence planning by subassembly detection

Assembly Sequences Based on Multiple Criteria Against Products with Deformable Parts

Optimal Assembly Sequence generation through computational approach

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