Advanced optimal tolerance design of machine elements using teaching-learning-based optimization algorithm

Rao, R. Venkata; More, Kiran C.

doi:10.1080/21693277.2014.892845

Cited by 23 publications

(12 citation statements)

References 33 publications

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“…In the entire population, the best solution is considered as the teacher. The flowchart of TLBO algorithm is shown in figure 4 [32]. The working of TLBO is divided into two parts, ''teacher phase'' and ''learner phase''.…”

Section: Teaching-learning-based Optimization Algorithmmentioning

confidence: 99%

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Optimal design of Stirling heat engine using an advanced optimization algorithm

Rao

Taler³

et al. 2016

Sādhanā

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The Stirling engine presents an excellent theoretical output equivalent to the output of Carnot engine and it is less pollutant and requires little maintenance. In this paper, Stirling heat engine is considered for optimization with multiple criteria. A recently developed advanced optimization algorithm namely ''teachinglearning-based optimization (TLBO) algorithm'' is used for maximization of output power, minimization of pressure losses and maximization of the thermal efficiency of the entire solar Stirling system. The comparisons of the proposed algorithm are made with those obtained by using the decision-making methods like linear programming technique for multi-dimensional analysis of preference (LINMAP), technique for order of preference by similarity to ideal solution (TOPSIS) and fuzzy Bellman-Zadeh method that have used the Pareto frontier gained through non-dominated sorting genetic algorithm-II (NSGA-II). The comparisons were also made with those obtained by the experimental results. It is found that the TLBO algorithm has produced comparatively better results than those given by the decision-making methods and the experimental results presented by the previous researchers.

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Section: Teaching-learning-based Optimization Algorithmmentioning

confidence: 99%

“…Flowchart of TLBO algorithm[32].implements the fuzzy non-dimensionalization, while the other methods (i.e. LINMAP and TOPSIS) used Euclidian non-dimensionalization.The proposed TLBO algorithm is now applied to the multiobjective optimization (containing three objectives) of power Stirling heat engine problem.…”

mentioning

confidence: 99%

Optimal design of Stirling heat engine using an advanced optimization algorithm

Rao

Taler³

et al. 2016

Sādhanā

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“…where ω 1 = ω 2 = ω 3 = ω 4 = ω 5 =0.2, ρ 1 = 1, ρ 2 = 1, ρ 3 = 1, ρ 4 = 100, and ρ 5 = 1 (Rao and More, 2014).…”

Section: Problem Descriptionmentioning

confidence: 99%

Least cost–tolerance allocation based on Lagrange multiplier

Kumar¹,

Padmanaban

Balamurugan

2016

Concurrent Engineering

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Industry-related competitiveness and reduction in manufacturing cost can be achieved by selection of ideal tolerance. Implementing non-traditional techniques for tolerance allocation to various parts in a mechanical assembly is an enervating procedure. Analytical methods are implemented to obtain creditable design. The main objective of this article is to minimize the manufacturing cost, quality loss, and TRSS (root sum square tolerance) for complex mechanical assemblies. The proposed methodology deals with the reciprocal exponential function. Hence, it is used to solve the problem for obtaining the closed-form solution by Lagrange multiplier method which integrates Lambert W function. The illustrations used in the research article demonstrate the feasibility and effectiveness of the traditional approaches. The results obtained also show that tolerance can be allocated economically and precisely. Here, non-traditional optimization methods are correlated and finally their performances are analyzed.

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“…Chen and Tang 5 formulated an optimization problem under tolerance conditions. Rao and More 6 used teaching-learning-based optimization for optimal selection of design and manufacturing tolerances. Hong and Chang 7 had a comprehensive review of tolerance research and Cao et al.…”

Section: Introductionmentioning

confidence: 99%

Generalized definition and application of tolerance

Hao

Youli

Wang

2019

Proceedings of the Institution of Mechanical Engineers, Part C:

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Tolerance with upper deviation less than lower deviation is defined as virtual tolerance; the dimension between two extreme values required with tolerance (virtual tolerance) is expressed by a set. The changed characteristics of the set range when the tolerance value is continuously reduced from positive to negative are explored. The nature of virtual tolerance is that the absolute value of virtual tolerance is the error compensation amount, and the dimension between two extreme values is the error compensation range. On the basis of the concept of positive and negative number, the theory of dimensional homogeneity, the existing conditions of the general formula of the dimensional chain, the accuracy of the calculation results of tolerance, and so on, the concept of virtual tolerance and its relationship of unity of opposites with tolerance are proposed. Based on the concept of virtual tolerance, analysis and calculation processes of various assembly dimensional chains are unified, and general formulation of calculating the range of false waste is established, and the method of determining the range of false waste by using probabilistic method in machining process is deduced.

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Advanced optimal tolerance design of machine elements using teaching-learning-based optimization algorithm

Cited by 23 publications

References 33 publications

Optimal design of Stirling heat engine using an advanced optimization algorithm

Optimal design of Stirling heat engine using an advanced optimization algorithm

Least cost–tolerance allocation based on Lagrange multiplier

Generalized definition and application of tolerance

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