Adaptive data-driven modular control approach to computer aided process planning for manufacturing spiral bevel and hypoid gears

Rong, Kaibin; Ding, Han; Tang, Jinyuan

doi:10.1177/0954405420956767

Cited by 6 publications

(4 citation statements)

References 41 publications

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“…Today, high-performance aerospace spiral bevel gears in the transmission systems of high-power helicopters are exercised to obtain a collaborative MOO design for the required loaded meshing transmission performance evaluations [ 50 , 52 , 53 , 54 ]. Moreover, the recent SLTCA based on economical software packages is used to verify the numerical results [ 43 ].…”

Section: Numerical Instancesmentioning

confidence: 99%

Data-Driven Multi-Objective Optimization Approach to Loaded Meshing Transmission Performances for Aerospace Spiral Bevel Gears

Zhou,

Shao,

Tang

2024

Materials

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Loaded meshing transmission performance optimization has been an increasingly significant target for the design and manufacturing of aerospace spiral bevel gears with low noise and high strength. An innovative data-driven multi-objective optimization (MOO) method is proposed for the loaded meshing transmission performances of aerospace spiral bevel gears. Data-driven tooth surface modeling is first used to obtain a curvature analysis of loaded contact points. An innovative numerical loaded tooth contact analysis (NLTCA) is applied to develop the data-driven relationships of machine tool settings with respect to loaded meshing transmission performance evaluations. Moreover, the MOO function is solved by using an achievement function approach to accurate machine tool settings output, satisfying the prescribed requirements. Finally, numerical examples are given to verify the proposed methodology. The presented approach can serve as a powerful tool to optimize the loaded meshing transmission performances with higher computational accuracy and efficiency than the conventional methods.

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Section: Numerical Instancesmentioning

confidence: 99%

Data-Driven Multi-Objective Optimization Approach to Loaded Meshing Transmission Performances for Aerospace Spiral Bevel Gears

Zhou,

Shao,

Tang

2024

Materials

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“…In numerical instance, a set of hypoid generator settings of the real face-milled spiral bevel and hypoid gears 61,62 is selected as the basic input signal to DFSS. The accurate hypoid generator settings are determined as a datadriven output response for the actual numerical control manufacturing.…”

Section: Basic Gear Designmentioning

confidence: 99%

Data-driven process control for manufacturing spiral bevel and hypoid gears by using design for six sigma (DFSS) considering numerical loaded tooth contact analysis (NLTCA)

Rong

Ding

Song

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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Data-driven process control considering both geometric and loaded contact performance evaluations has been an increasingly important stage in field of spiral bevel and hypoid gears. A new data-driven manufacturing process control strategy is proposed for a high performance spiral bevel and hypoid gears. Here, to distinguish with the conventional simulated loaded tooth contact analysis (SLTCA) using economical finite element software package, the numerical loaded tooth contact analysis (NLTCA) is of more flexibility and practicality. In light of the advantages of the improved design for six sigma (DFSS), it is integrated with NLTCA for establishing a novel data-driven process control of gear manufacturing. Firstly, in improved DFSS framework, quality function deployment (QFD) is used to determine four sub-objective high-performance evaluation items. Then, their data-driven relationships between machine settings are respectively determined by using NLTCA. In particular, the manufacturing process control is further converted into multi-objective optimization (MOO) modification of the hypoid generator settings. Finally, an interactive preference point approach is applied for data-driven control of its iterative step and it can obtain a robust solution from Pareto optimal front. A case study is provided to verify the proposed methodology.

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“…24 Artoni et al equivalent the gear deviation mapping to the pinion deviation and added it to the pinion itself to accumulate compensation by applying machine tool correction settings to the pinion. 25 Rong et al 26 proposed a data-driven operation and optimization method with adaptive high-order corrections for achieving accurate machining of tooth surfaces. Zhou 27 proposed a universal machine tool adjustment scheme with high-order motion coefficients for practical geometric error compensation.…”

Section: Introductionmentioning

confidence: 99%

Reverse-adjustment algorithm of tooth surface precision control design for spiral bevel gears

Chen

Wang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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As aerospace requirements for low noise and high strength spiral bevel gear transmission continue to increase, tooth surface precise control is becoming increasingly important in design and manufacture. The previous design depended significantly on ease off the tooth surface and using the tooth surface optimization approach. It’s a parameter design technique that goes from the design tooth surface to the target tooth surface without accounting for the reaction of the tooth surface to machine tool machining errors. This study proposes a new algorithm for reverse adjustment of tooth face accuracy control. A mathematical model of the tooth face is initially built using the local synthesis method to replicate the genuine machining process. Second, the machine setup settings are chosen as multi-objective optimization parameters, and the reverse adjustment model is constructed to investigate the machine’s machining error on the tooth surface, as well as the reverse adjustment model’s effects on contact and robustness characteristics. Finally, numerical calculations and comparisons with the findings of existing design approaches are used to verify the validity and effectiveness of the reverse adjustment algorithm in the design of tooth surface accuracy control of curved bevel gears.

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Adaptive data-driven modular control approach to computer aided process planning for manufacturing spiral bevel and hypoid gears

Cited by 6 publications

References 41 publications

Data-Driven Multi-Objective Optimization Approach to Loaded Meshing Transmission Performances for Aerospace Spiral Bevel Gears

Data-Driven Multi-Objective Optimization Approach to Loaded Meshing Transmission Performances for Aerospace Spiral Bevel Gears

Data-driven process control for manufacturing spiral bevel and hypoid gears by using design for six sigma (DFSS) considering numerical loaded tooth contact analysis (NLTCA)

Reverse-adjustment algorithm of tooth surface precision control design for spiral bevel gears

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