Fatigue life analysis based on six sigma robust optimization for pantograph collector head support

Li, Yong Hua; Hu, Mingguang; Feng, Wang

doi:10.1177/1687814016679314

Cited by 10 publications

(6 citation statements)

References 26 publications

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“…Due to the uncertainties of design parameters and loads, the stress of the structure will fluctuate around a certain average stress during the operation of the welding robots. Often such cyclic loadings with mean stress considerably influence the component damage accumulation process [21]. Because the stress spectrum can be expressed in terms of mean stress and stress amplitude.…”

Section: Fuzzy Design Optimization-based Fatigue Reliability Analymentioning

confidence: 99%

Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots

Zhi

Chen

et al. 2020

IEEE Access

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In this work, a fuzzy design optimization-based fatigue reliability analysis technique is addressed to obtain the optimal fatigue reliability of the structures with random parameters under the minimum fluctuation of fatigue life. The challenge of the problem lies in uncertainties involved from both structural parameters and loads, which renders the fatigue reliability becoming the primary problem to be considered in evaluating structural performance. In order to obtain the optimal fatigue reliability, the optimal mathematical models aiming at the mass and fatigue life of welding robots are constructed respectively, and the genetic particle swarm optimization algorithm and radial basis function neural network (GAPSO-RBFNN) based surrogate model is then presented. Moreover, fuzzy constraints are introduced into the optimization model, and the improved non-dominated sorting genetic algorithm (INSGA-III) optimization strategy is proposed to solve it, which can effectively reduce the workload by increasing the diversity of Pareto solutions during the iterative process. Finally, the optimized structure combined with numerical simulation method is adopted to analyze the fatigue reliability. After analysis steps are given in detail, a practical welding robot structure is presented to demonstrate the validity and reasonability of the developed methodology. INDEX TERMS Fuzzy design optimization, fatigue reliability, welding robots, surrogate model.

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Section: Fuzzy Design Optimization-based Fatigue Reliability Analymentioning

confidence: 99%

Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots

Zhi

Chen

et al. 2020

IEEE Access

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“…The methodology was designed and implemented to improve the company's performance using focused studies on the variability of production processes. 12,13 It is a disciplined management strategy, characterized by a systemic approach and intensive use of statistical thinking, which aims to dramatically reduce the variability of critical processes and increase profitability of businesses through the optimization of products and processes, seeking satisfaction of customers. 14,15 Although Motorola is the precursor of the Six Sigma methodology, it has gained popularity only in 1994, when the president of General Electric (GE) considered it critical to the pursuit of higher quality and profitability.…”

Section: Six Sigmamentioning

confidence: 99%

Six Sigma methodology advantages for small- and medium-sized enterprises: A case study in the plumbing industry in the United States

Takao

Woldt

Silva

2017

Advances in Mechanical Engineering

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The intense competitive manufacturing environment results in small-and medium-sized enterprises searching for strategies to drive cost reduction and increase quality. While these are goals all organizations strive for, small-and mediumsized enterprises must accomplish these continuous improvement objectives with limited resources. The integration of quality tools with the Six Sigma methodology is fundamentally important in this process. This article describes the application of the Six Sigma methodology in a North American plumbing products small-and medium-sized enterprise. In this study, a cross-functional team uses the Six Sigma tools and methodology to reduce cycle time and increase sales. This case study presents a roadmap for studying the production cycle using the DMAIC process (define, measure, analyze, improve, and control). Using a market research study, the team quantitatively defines the problem, measures the process, analyzes the supporting data, and implements a series of solutions resulting in increased customer satisfaction. In addition, strategies are implemented to control the process improvements. The results offer evidence of Six Sigma effectiveness for small-and medium-sized enterprises and offer direction for small-and medium-sized enterprises interested in implementing a similar approach.

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“…Chen et al [13] proposed a fatigue reliability analysis method that considers the uncertainty of parameters, draws a fatigue limit diagram without safety factor, and gives a more reasonable fatigue reliability analysis result, which is helpful for lightweight design of products. Li et al [14] established a robust optimization model based on Six Sigma to analyze the fatigue reliability of the pantograph collector head support. is method not only considers the influence of uncertain factors, but also improves the robustness of fatigue life prediction.…”

Section: Introductionmentioning

confidence: 99%

Fatigue Reliability Analysis of Motor Hanger for High‐Speed Train Based on Bayesian Updating and Subset Simulation

Zhi

Zhang

et al. 2020

Advances in Materials Science and Engineering

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In order to more accurately analyze the fatigue reliability of motor hanger for high-speed train and reduce the influence of uncertain factors, a Bayesian statistical method is introduced to propose a novel fatigue reliability analysis method based on Bayesian updating and subset simulation. First, considering the influence of various uncertain parameters on the first principal stress (FPS) of motor hanger, the ANSYS parametric design language (APDL) is used to establish the parametric model. e D-optimal design of experiment is carried out to calculate the FPS of the motor hanger. Second, the experimental data is fitted by the least square method to establish a polynomial response surface function which characterizes the FPS of the motor hanger, and analysis of variance (ANOVA) is carried out. On this basis, the variation trend of the FPS under parameter fluctuation is calculated, and its probability distribution characteristics are obtained. Based on the MATLAB platform, the Bayesian updating method is adopted to correct the probability and statistical characteristics of the FPS to improve the accuracy of prediction. Finally, the subset simulation (SS) method is used to calculate the fatigue failure probability of the motor hanger. e research results show that the proposed method helps to improve the accuracy and efficiency of fatigue reliability analysis.

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Fatigue life analysis based on six sigma robust optimization for pantograph collector head support

Cited by 10 publications

References 26 publications

Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots

Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots

Six Sigma methodology advantages for small- and medium-sized enterprises: A case study in the plumbing industry in the United States

Fatigue Reliability Analysis of Motor Hanger for High‐Speed Train Based on Bayesian Updating and Subset Simulation

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