Elastic moduli of grinding wheel based on a simplified model.

Matsuno, Yosoo; Yamada, Hiroshi

doi:10.2109/jcersj1950.90.1042_320

Cited by 3 publications

(2 citation statements)

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“…This classic approach involves associating the hardness of the wheel with its Young's modulus [30]. However, classic studies suggest that this hypothesis is not completely correct [31] and using the same grade for different wheels can lead to variations in Young's modulus values. There is a lack of knowledge about this important issue in wheel modelling.…”

Section: Wheel Characterizationmentioning

confidence: 99%

Expectations and limitations of Cyber-Physical Systems (CPS) for Advanced Manufacturing: A View from the Grinding Industry

et al. 2020

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Grinding is a critical technology in the manufacturing of high added-value precision parts, accounting for approximately 20–25% of all machining costs in the industrialized world. It is a commonly used process in the finishing of parts in numerous key industrial sectors such as transport (including the aeronautical, automotive and railway industries), and energy or biomedical industries. As in the case of many other manufacturing technologies, grinding relies heavily on the experience and knowledge of the operatives. For this reason, considerable efforts have been devoted to generating a systematic and sustainable approach that reduces and eventually eliminates costly trial-and-error strategies. The main contribution of this work is that, for the first time, a complete digital twin (DT) for the grinding industry is presented. The required flow of information between numerical simulations, advanced mechanical testing and industrial practice has been defined, thus producing a virtual mirror of the real process. The structure of the DT comprises four layers, which integrate: (1) scientific knowledge of the process (advanced process modeling and numerical simulation); (2) characterization of materials through specialized mechanical testing; (3) advanced sensing techniques, to provide feedback for process models; and (4) knowledge integration in a configurable open-source industrial tool. To this end, intensive collaboration between all the involved agents (from university to industry) is essential. One of the most remarkable results is the development of new and more realistic models for predicting wheel wear, which currently can only be known in industry through costly trial-and-error strategies. Also, current work is focused on the development of an intelligent grinding wheel, which will provide on-line information about process variables such as temperature and forces. This is a critical issue in the advance towards a zero-defect grinding process.

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Section: Wheel Characterizationmentioning

confidence: 99%

Expectations and limitations of Cyber-Physical Systems (CPS) for Advanced Manufacturing: A View from the Grinding Industry

et al. 2020

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“…The wheel was silicon carbide grinding wheel (CG60K5V8) with modulus of elasticity 25 GPa and Poisson's ratio 0.22. 34 The size of the workpiece was 60 mm 3 60 mm 3 10 mm. The size of the wheel was 340 mm 3 50 mm 3 127 mm.…”

Section: Validationmentioning

confidence: 99%

A modified model for estimating the contact length in surface grinding

Setti

Ghosh

Rao

2015

Proceedings of the Institution of Mechanical Engineers, Part B:

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The real contact length during the grinding process is considered as an important subject for researchers, mainly because it reflects the intensity of the responses such as grinding forces and temperature generation. In order to measure and assess the real contact length, many experimental techniques and prediction models are available in the literature. Among all these models, the model developed by Rowe and Qi is being used widely by researchers because of its ability to make close predictions with real values. Rowe and Qi coined the term called roughness factor in their model. This factor varies with grinding environments and wheel-work material combinations. To decide it for a new environment, one has to do the laborious experimental work. In this article, the roughness factor has been analysed from the grinding temperature and the heat partition ratio point of view and expressed so that without experimental work prediction of the roughness factor can be done. For this, a new factor called as the thermal factor has been proposed based on the roughness factor modifications. Its good correlation with dimensionless temperature and heat partition ratio under different grinding environments have been presented and discussed in the current communication. It seems that the thermal factor can be helped in an easy and accurate prediction of the contact length during grinding operations.

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