Simulation of feed cycles for grinding between centres

Chen, Xun; Allanson, David; Thomas, Andrew R.; Moruzzi, J L; Rowe, W. Brian

doi:10.1016/0890-6955(94)90045-0

Cited by 14 publications

(12 citation statements)

References 10 publications

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“…Chen et al (1994) claims that where the amount of wheel wear during one grinding cycle is small in comparison to the radial penetration rate, the wheel wear can be neglected. Based on their assertion, equation (18) can be more simplified and the grinding ratio model can be decoupled from the infeed rate model and given by equation (19):…”

Section: Modelling Of Infeed and Infeed Ratementioning

confidence: 99%

Generalized Intelligent Grinding Advisory System

Choi

Shin

2007

International Journal of Production Research

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The paper presents the current development of the Generalized Intelligent Grinding Advisory System (GIGAS), which provides a systematic way of modelling complex grinding processes and finding optimal process conditions while meeting the general class of process requirements. GIGAS provides a way of incorporating three different types of knowledge, including analytical models, experimental data and heuristic knowledge from experts, to describe complex grinding processes. The developed optimization algorithm can handle various optimization problems including different grinding processes and optimization objectives. Case studies are presented for surface grinding and cylindrical plungegrinding with various optimization objectives to demonstrate its capability of performing optimization. The overall architecture and the developed software with the graphical user interface are described.

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Section: Modelling Of Infeed and Infeed Ratementioning

confidence: 99%

Generalized Intelligent Grinding Advisory System

Choi

Shin

2007

International Journal of Production Research

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“…A typical grinding cycle comprehends a fast initial feeding speed of the wheel against the workpiece for roughing and fast material removal, called spark-in, followed by lower speeds (semi-finishing) and a complete stop on feeding, called spark-out stage. The interaction between the grinding force and the machine compliance can lead to deflection that can be sometimes greater than the depth of cut, leading to size and roundness errors [2]. The elastic deflections on the contact wheel-workpiece, caused by their inherent elasticity, affect the process accuracy and also the amount of energy required to remove material [3].…”

Section: Introductionmentioning

confidence: 99%

Finding dimensional stability considering deflection effects in cylindrical plunge grinding

Silva

Coelho

et al. 2019

J Braz. Soc. Mech. Sci. Eng.

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In spite of the existence of several models to effectively design grinding cycles, they are not frequently adopted in production lines, due to the lack of knowledge, difficulties in determining some input parameters and discrepancies observed in the obtained results during the production of a batch of parts. This paper proposes a contribution to the modeling and simulation of cylindrical plunge grinding cycles in terms of dimensional stability of the process, prediction of the workpiece diameter along the grinding cycle and the minimum required spark-out time, incorporating into the model grinding tolerance limits according to the chosen capability scenario. The prediction of the part diameter and the spark-out time in a cylindrical plunge grinding operation is the key parameter to design optimized grinding cycles. The proposed model covers typical fast grinding cycles in industry, in which the spark-in time is not long enough to guarantee that at its end, the real workpiece radius reduction speed is very close to the programmed feed rate. In the proposed model, the remaining radial stock to be removed during the spark-out stage is designed to be equal to or lower than the tolerance limit for the grinding operation, but considering different scenarios of capability index: barely capable process (C p = 1); capable (C p = 1.3); and six-sigma quality level (C p = 2.0). The minimum spark-out time necessary to reduce the total radial stock to the specified capability limit is calculated by the simulation. Experimental plunge cylindrical grinding tests were performed in which the reduction in the workpiece diameter was measured using an in-process diameter gauge, varying the in-feed velocity and the spark-out time. As a result, a reasonable compromise between the proposed theoretical model and the experimental data was achieved. The dependency of the "time constant" and the in-feed speed was demonstrated for fast spark-in cycles. It was also observed that longer spark-out times will be needed to achieve tighter capability indexes for a given in-feed speed and "time constant" value.

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“…As the grinding wheel grinds the workpiece, deformation is induced between the wheel and the workpiece, causing a delay between the command signal for the position and the system response [15,16] .…”

Section: Internal Plunge Grinding Force Modelmentioning

confidence: 99%

“…As a key variable in the proposed GPSM, the time constant τ should be estimated exactly. Depending on the actual power signal changing characteristics, the semi-finishing stage ( n=2) power signal is selected to calculate the time constant τ using equation (15). To reduce the effect of measuring noise, the least-mean-squares (LMS) estimation method is applied to each power signal sample and is adjusted in real time.…”

Section: Prediction Of the Grinding Powermentioning

confidence: 99%

See 1 more Smart Citation

In-process monitoring and analysis of bearing outer race way grinding based on the power signal

Chi

Chen

2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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In production engineering, monitoring of the grinding process is critical for acquiring information on material removal, wheel performance, and workpiece quality. Here, a general model of the power signal and material removal rate is proposed to monitor the internal plunge grinding of a bearing outer race way product. Three continuous grinding cycles after dressing were used to analyse the roughing, semi-finishing, finishing and spark-out process under the same parameters.Based on the actual grinding process, a practical analysis method is applied to improve the general model to predict more accurately the power curve. Finally, estimations of grinding wheel performance and grind quality using the grinding power signal model (GPSM) coefficients are also presented. The experimental results showed that the improved power signal model is capable of solving the industrial problem of multi-stage in-feed grinding cycles and improving grind quality.

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Simulation of feed cycles for grinding between centres

Cited by 14 publications

References 10 publications

Generalized Intelligent Grinding Advisory System

Generalized Intelligent Grinding Advisory System

Finding dimensional stability considering deflection effects in cylindrical plunge grinding

In-process monitoring and analysis of bearing outer race way grinding based on the power signal

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