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Design for Residual Stress (DRS) on Gears Manufacturing: Industry 4.0 Approach


Gear are one of the mechanical components mostly influenced by residual stresses (RS) that come from the combination of a complex load stress state generated by the involute profile and a manufacturing chain with a wide range of processes. Incipient qualitative studies were conducted with the main goal of optimizing the manufacturing chain to achieve an ideal RS state at the end of the production. To expand the state-of-the-art towards a quantitative result, the objective of this project is to develop a predictive numerical method for the phenomenon of residual stress state interaction along the gears manufacturing chain. This oriented development of the manufacturing chain for a specific residual stress state consolidates the bases of the concept of Design of Residual Stress (DRS). The design method searches for an optimal residual stress state, considering the desired failure mode to be avoided and undesirable outcomes from previous manufacturing processes. This project proposes to approach the manufacturing chain by means of the interaction between shot peening and grinding processes. In order to quantify the RS interaction effect, the grinding process will be modeled through the hybrid FE method that replaces the tool-workpiece contact by the input of machining loads (mechanical and thermal). This project is an important step towards the development of the Industry 4.0 philosophy, providing a smart decision-making capability on real-time adjustment of manufacturing parameters. The proposal consolidates a research line of an academic international cooperation between ITA and WZL-RWTH Aachen, Germany. Moreover, the scope of this project was proven to represent an actual demand from the national industry, contributing to place Brazil in a global leadership position on this topic. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
DE FARIA, ALFREDO R.; ALHATIM, OMAIR; SANTIAGO MACIEL, HOMERO FONSECA. A Numerical Method to Solve Nonsymmetric Eigensystems Applied to Dynamics of Turbomachinery. INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS, v. 17, n. 9 NOV 2020. Web of Science Citations: 0.
ROCHA D' OLIVEIRA, ANDRE LUIZ; REGO, RONNIE RODRIGO; DE FARIA, ALFREDO ROCHA. Residual stresses prediction in machining: Hybrid FEM enhanced by assessment of plastic flow. Journal of Materials Processing Technology, v. 275, JAN 2020. Web of Science Citations: 0.

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