A Memetic Algorithm for multi-objective fixture layout optimization

Bai, Xue; Hu, Fei; He, Gaiyun; Ding, Bohui

doi:10.1177/0954406214565802

Cited by 4 publications

(2 citation statements)

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“…Xing 24 conducted the design and optimization of the sheet metal locating points based on the improved fruit fly optimization algorithm (IFOA). Bai et al 25 used the memetic algorithm to carry out the bi-objective fixture layout optimization to improve the location accuracy and stability of the workpiece. Xing et al 26 achieved the multi-objective optimization of fixture layout for auto-body compliant parts by combining the non-domination sorting social radiation algorithm (NSSRA) with FEA.…”

Section: Introductionmentioning

confidence: 99%

Optimization of fixture locating layout for sheet metal part by cuckoo search algorithm combined with finite element analysis

Yang

Wang

Yang

et al. 2017

Advances in Mechanical Engineering

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Fixture layout has a direct and influential impact on sheet metal manufacturing quality. Much attention has been paid to sheet metal fixture locating layout in the fields of academy, engineering, and industry in the past few years. However, how to obtain the optimal fixture locating layout so as to effectively reduce the sheet metal part deformation is still a complex and challenging task. To that end, this article proposes a new approach to optimizing the sheet metal fixture locating layout based on the ''N-2-1'' locating principle by coupling cuckoo search algorithm with finite element analysis. First, the optimization model of the sheet metal locating layout based on the ''N-2-1'' locating principle is constructed. Second, the cuckoo search algorithm is employed to search the optimum layout of the ''N'' fixture locators for the minimum deformation through iterative calls to the finite element analysis solver. Finally, two cases are respectively studied and conducted to verify the proposed method, and the comparison results with genetic algorithms and particle swarm optimization show that the cuckoo search algorithm outperforms the genetic algorithms and particle swarm optimization in terms of the quality of the solutions, robustness, and usability in the sheet metal fixture locating layout optimization.

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Section: Introductionmentioning

confidence: 99%

Optimization of fixture locating layout for sheet metal part by cuckoo search algorithm combined with finite element analysis

Yang

Wang

Yang

et al. 2017

Advances in Mechanical Engineering

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“…A FEA-based force-deformation model was developed to compute the node displacements under external forces. Bai et al [18] described an approach based on memetic algorithm to multi-objective fixture layout optimization, considering both location accuracy and stability. This approach used an entropy method to obtain the weights of each objective functions, and establishes a fitness function.…”

Section: Introductionmentioning

confidence: 99%

Intelligent design and optimization of machining fixtures

et al. 2016

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Original scientific paper This work presents an integral system for machining fixture layout design and optimization. The optimization module of this system allows determination of optimal positions of locating and clamping elements, which provides required accuracy and surface quality, while at the same time guarantees design of collision-free fixtures. The design module performs selection of required fixture elements based on a set of predefined production rules. Adequate criteria for the selection of fixture elements are defined for locating, clamping, tool guiding, and tool adjustment elements, as well as for fixture body elements, connecting elements and add-on elements. The system uses geometry and feature workpiece characteristics, as well as the additional machining, and process planning information. It has been developed to accommodate machining processes of turning, drilling, milling, and grinding of rotational and prismatic workpieces. A segment of output results is also shown. Finally, conclusions are presented with directions for future investigation. Keywords: artificial intelligence; fixture; process planningInteligentno projektiranje i optimizacija konstrukcija naprava za strojnu obradu Izvorni znanstveni rad U radu je predstavljen integralni sustav za projektiranje i optimizaciju konstrukcije naprava za strojnu obradu. Dio sustava za optimizaciju omogućuje, s jedne strane, određivanje optimalnih pozicija elemenata za baziranje i stezanje kako bi se postigla potrebna točnost i kvaliteta obrađene površine izratka, a s druge strane, generiranje konstrukcije naprava bez kolizija. Dio sustava za projektiranje osigurava izbor pojedinih elemenata naprava na osnovi prethodno definiranih produkcijskih pravila. Prilagođeni kriteriji izbora definirani su za elemente za baziranje, elemente za stezanje, elemente za vođenje alata, elemente za podešavanje položaja alata, elemente tijela naprava, elemente za povezivanje i nadogradne elemente. Sustav je baziran na geometrijskim karakteristikama i karakterističnim obilježjima djela, kao i dodatnim informacijama o obradi i informacijama iz tehnološkog procesa. Sustav je razvijan za operacije tokarenja, bušenja, glodanja i brušenja koje se izvode na rotacijskim i prizmatičnim radnim predmetima. U radu su djelomično prikazani izlazni rezultati razvijenog sustava. Na kraju rada dani su odgovarajući zaključci i istaknuti mogući pravci daljih istraživanja.

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