FEA compliant parametric tolerance allocation of mechanical assembly using neural network and differential evolution algorithm

Jayaprakash, G.; Sivakumar, K.; Thilak, M.

doi:10.1080/0951192x.2012.665184

Cited by 11 publications

(7 citation statements)

References 20 publications

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“…33,34 Meanwhile, the combination of the FEA with kinematic formulations also supports the dimensional tolerance, error, and variation analyses for compliant assemblies. [35][36][37] Furthermore, the above dimensional analysis is supporting the researches on fixture layout optimization over decades. 38 Meanwhile, the FEA promotes the fruits that open out the dimensional error caused by joint deformations.…”

Section: Assembly Dimensional Analysismentioning

confidence: 78%

Assembly sequence optimization for minimizing the riveting path and overall dimensional error

Tang

Mao

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part B:

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Due to the complexities of calculations based on different representations of constituent parts in an assembly, the combined improvement of efficiency and precision for the riveting has seldom been studied by the sequence planning or dimensional engineering. This article develops an assembly sequence optimization method that simultaneously minimizes the path length and overall dimensional error for the solid riveting. The sequence is denoted by the order of classifications for the nodes around the rivet holes in the finite element model for the assembly. Ant colony algorithm is applied on the optimization by integrating two calculations, that is, the length calculation of riveting path and the calculation of the dimensional error related to rivet upsetting directions and assembly sequence. Results for three assemblies are presented which show a good degree of optimization in performance for different scales of assemblies with different numbers of rivets that share the same solid riveting process.

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Section: Assembly Dimensional Analysismentioning

confidence: 78%

Assembly sequence optimization for minimizing the riveting path and overall dimensional error

Tang

Mao

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Jayaprakash et al. 24 introduce an integration of statistical tolerance design method with finite element analysis. This method assured that the optimal tolerance values of various assembly component parts, obtained as end product of the tolerance design will remain within tolerance variation.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimum tolerance synthesis of simple assemblies with nominal dimension selection using genetic algorithm

Kumar¹,

Ravindran²,

Kumar³

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part C:

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Optimum tolerance allocation plays a vital role in minimization of the direct manufacturing cost, and it is sensitive to tolerances related to variations in manufacturing processes. However, optimal adjustment of both nominal dimensions and selection of tolerances may further reduce assembly manufacturing cost and wastage of materials during processing. Most studies in existing literature focus on optimum tolerance allocation for the assemblies without considering nominal dimension selection. The method proposed in this work uses genetic algorithm techniques to allocate tolerances to assembly components, thereby minimizing costs. The component alternate nominal dimensions are predicted based on critical dimensions and its tolerances. The effectiveness of the developed algorithms demonstrated using randomly generated problems as well as sample problems taken from the literature. Test results are compared with those obtained using the Lagrange multiplier method. It is shown that by adjusting the nominal dimensions, the proposed method yields considerable savings in manufacturing costs.

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“…It has successfully been applied to diverse domain of science and engineering (Su and Wang 2011, Jayaprakash et al 2012, Kim et al 2012. As for scheduling problems, DE has been applied in permutation flow shop scheduling (Onwubolu and Davendra 2006), no-wait permutation flow shop scheduling (Qian et al 2009), etc.…”

Section: Introductionmentioning

confidence: 99%

A hybrid discrete differential evolution algorithm to minimise total tardiness on identical parallel machines

Deng

Zhang

2013

International Journal of Computer Integrated Manufacturing

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This paper presents a hybrid discrete differential evolution (HDDE) algorithm to solve the Pm// P T j problem. The coding and decoding scheme based on job permutation is applied in the algorithm. The algorithm employs several efficient heuristics in the initialisation phase and incorporates an insertion-based local search. To validate the proposed algorithm, computational experiments are conducted on a benchmark problem set from the literature. Computational results show that the HDDE algorithm outperforms the existing state-of-the-art algorithms for the Pm// P T j problem.

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FEA compliant parametric tolerance allocation of mechanical assembly using neural network and differential evolution algorithm

Cited by 11 publications

References 20 publications

Assembly sequence optimization for minimizing the riveting path and overall dimensional error

Assembly sequence optimization for minimizing the riveting path and overall dimensional error

Optimum tolerance synthesis of simple assemblies with nominal dimension selection using genetic algorithm

A hybrid discrete differential evolution algorithm to minimise total tardiness on identical parallel machines

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