Time-dependent reliability analysis of harmonic drive based on transient FEA and accelerated life test

Zhang, Xian; Jiang, Gedong; Zhang, Hao; Yun, Xialun; Mei, Xuesong

doi:10.1108/ec-10-2019-0466

Cited by 12 publications

(12 citation statements)

References 24 publications

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“…Besides, AMRDA is proposed to solve the specific deterministic model of TSPCD in this study. However, in real-world applications, stochastic scheduling problems in the cross-docking center should be considered, which should be studied in future works (Zhang et al , 2020). For instance, variables such as the number of trucks and dock doors, the capacity of the temporary storage and types of products could be considered in a stochastic programming model which serves further exploration (Atighehchian, 2019).…”

Section: Discussionmentioning

confidence: 99%

Adaptive memory red deer algorithm for cross-dock truck scheduling with products time window

Zhou

Zong

2021

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Purpose The cross-docking strategy has a significant influence on supply chain and logistics efficiency. This paper aims to investigate the most suitable and efficient way to schedule the transfer of logistics activities and present a meta-heuristic method of the truck scheduling problem in cross-docking logistics. A truck scheduling problem with products time window is investigated with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks. Design/methodology/approach This research proposed a meta-heuristic method for the truck scheduling problem with products time window. To solve the problem, a lower bound of the problem is built through a novel two-stage Lagrangian relaxation problem and on account of the NP-hard nature of the truck scheduling problem, the novel red deer algorithm with the mechanism of the heuristic oscillating local search algorithm, as well as adaptive memory programming was proposed to overcome the inferior capability of the original red deer algorithm in the aspect of local search and run time. Findings Theory analysis and simulation experiments on an industrial case of a cross-docking center with a product’s time window are conducted in this paper. Satisfactory results show that the performance of the red deer algorithm is enhanced due to the mechanism of heuristic oscillating local search algorithm and adaptive memory programming and the proposed method efficiently solves the real-world size case of truck scheduling problems in cross-docking with product time window. Research limitations/implications The consideration of products time window has very realistic significance in different logistics applications such as cold-chain logistics and pharmaceutical supply chain. Furthermore, the novel adaptive memory red deer algorithm could be modified and applied to other complex optimization scheduling problems such as scheduling problems considering energy-efficiency or other logistics strategies. Originality/value For the first time in the truck scheduling problem with the cross-docking strategy, the product’s time window is considered. Furthermore, a mathematical model with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks is developed. To solve the proposed problem, a novel adaptive memory red deer algorithm with the mechanism of heuristic oscillating local search algorithm was proposed to overcome the inferior capability of genetic algorithm in the aspect of local search and run time.

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Section: Discussionmentioning

confidence: 99%

Adaptive memory red deer algorithm for cross-dock truck scheduling with products time window

Zhou

Zong

2021

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“…The most critical components of a gearbox are the gears and bearings. The deterioration of a gear appears at the teeth [20,21], harmonic drive gears are damaged by fatigue fractures [22], and bearings are typically subjected to failures at the rolling elements or the inner or outer race [21]. The damage accumulates over time and is caused mainly by load (forces and velocity) [23,24], high temperature [25], bad lubrication [26], or manufacturing defects.…”

Section: The Concept Of Robot Wearmentioning

confidence: 99%

Method for Robot Manipulator Joint Wear Reduction by Finding the Optimal Robot Placement in a Robotic Cell

et al. 2021

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We describe a method for robotic cell optimization by changing the placement of the robot manipulator within the cell in applications with a fixed end-point trajectory. The goal is to reduce the overall robot joint wear and to prevent uneven joint wear when one or several joints are stressed more than the other joints. Joint wear is approximated by calculating the integral of the mechanical work of each joint during the whole trajectory, which depends on the joint angular velocity and torque. The method relies on using a dynamic simulation for the evaluation of the torques and velocities in robot joints for individual robot positions. Verification of the method was performed using CoppeliaSim and a laboratory robotic cell with the collaborative robot UR3. The results confirmed that, with proper robot base placement, the overall wear of the joints of a robotic arm could be reduced from 22% to 53% depending on the trajectory.

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“…Besides, some scholars began to evaluate the reliability of harmonic reducers focusing on the transmission performance related failures. Zhang et al [19] considered the dynamic stresses at the critical position of the flexspline and proposed a time-dependent reliability evaluation method to predict the time-to-failure of the harmonic reducer using accelerated life tests. Zhao et al [3] conducted a reliability testing on the hysteresis errors for a harmonic reducer and analyzed its dynamic reliability using a response surface method.…”

Section: A Literature Reviewmentioning

confidence: 99%

Performance Margin Modeling and Reliability Analysis for Harmonic Reducer Considering Multi-Source Uncertainties and Wear

Tong

Chen

et al. 2020

IEEE Access

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The harmonic reducer of the space drive mechanism is one of the critical components of the satellite remote sensing system and its reliability is always required strictly in practice. During the manufacturing and usage processes of the harmonic reducer, uncertainties are ubiquitous and performance degradation is inevitable, which is mainly caused by the wear between the meshed tooth surfaces. They influence the reliability of harmonic reducer. In this paper, a performance margin modeling and reliability analysis for harmonic reducer considering multi-source uncertainties and wear is proposed. Firstly, based on the functional principle and the influence of wear, the performance margin model is established using hysteresis and transmission errors as key performance parameters. Then multi-source uncertainties are analyzed and quantified, including manufacturing errors, uncertainties in operational and environmental conditions, and uncertainties in performance thresholds. Finally, the reliability model is constructed based on the performance margin. A case study of a harmonic reducer is applied and the reliability sensitivity analysis is implemented to show the practicability of the proposed method. The results show that the proposed method can provide some suggestions to the design and manufacturing phases of the harmonic reducer.

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Time-dependent reliability analysis of harmonic drive based on transient FEA and accelerated life test

Cited by 12 publications

References 24 publications

Adaptive memory red deer algorithm for cross-dock truck scheduling with products time window

Adaptive memory red deer algorithm for cross-dock truck scheduling with products time window

Method for Robot Manipulator Joint Wear Reduction by Finding the Optimal Robot Placement in a Robotic Cell

Performance Margin Modeling and Reliability Analysis for Harmonic Reducer Considering Multi-Source Uncertainties and Wear

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