Abrasion Monitoring and Automatic Chatter Detection in Cylindrical Plunge Grinding

Ahrens, Markus; Fischer, Ruben; Dagen, Matthias; Denkena, Berend; Ortmaier, Tobias

doi:10.1016/j.procir.2013.06.119

Cited by 27 publications

(11 citation statements)

References 6 publications

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“…When analyzing dynamic behavior, the main problem to arise concerns the difficulty to position the accelerometers near to the grinding zone, which limits the possibility of achieving a highly accurate analysis, particularly when there is a need to analyze low amplitude vibratory phenomena. Several works can be found in the literature, particularly in relation to the avoidance of vibratory effects such as chatter [53][54][55][56] and the appearance of surface marks [56,57]. Accelerometers are still usually positioned relatively far away from the contact point between wheel and workpiece.…”

Section: Several Attempts Have Been Made To Analyze the Wear Of New Tmentioning

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: Several Attempts Have Been Made To Analyze the Wear Of New Tmentioning

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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“…Signal acquisition is usually achieved by the sensor. There are many kinds of sensors that can be used to acquire vibration signal in the machining operation, such as accelerometer [27], dynamometer [28], acoustic emission [29], displacement [30], and electrical power sensors [31]. In this study, the cutting force signals in the X and Y directions are selected to identify chatter, and are measured by a Kistler dynamometer 9257B mounted between the workpiece and the workbench.…”

Section: Signal Acquisition and Feature Extractionmentioning

confidence: 99%

A new method for the prediction of chatter stability lobes based on dynamic cutting force simulation model and support vector machine

Peng

Wang

Liao

2015

Journal of Sound and Vibration

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“…In grinding filter banks or the discrete wavelet transform [10] is effective for monitoring of chatter without additional knowledge of the process. As in [11], the discrete wavelet transform is used for calculation of the signal power in the frequency range of 600 to 1,200 Hz by Daubichies wavelet of order 10.…”

Section: Signal Processingmentioning

confidence: 99%

Monitoring of grinding wheel defects using recursive estimation

Denkena

Ortmaier

Ahrens

et al. 2014

Int J Adv Manuf Technol

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In production engineering, highest surface qualities and low tolerances are produced by grinding processes. Defects of the grinding wheel caused by unbalance, wrong dressing cycles, cavities, or waviness result in vibrations and damage of workpiece or spindle. Therefore, monitoring of the tool is important in practical use. In order to avoid scrap, small faults of the grinding wheel and very small amplitudes of the resulting vibrations are of major interest. This paper presents a new monitoring method, which estimates the defects recursively during the grinding process. Different sensors are analyzed using this method. Among sensors for academic purposes, typical sensors in grinding machines such as the displacement, acceleration, motor current, and acoustic emission are in use for monitoring. Compared to monitoring in the frequency domain and signal feature extraction by filtering, the recursive estimation can reduce noise. In cylindrical plunge grinding, wavy tool defects may result in unequal wear and self-exiting waviness of the wheel over a long period of grinding and start at very low amplitudes. This regenerative chatter is subject of monitoring of highest productivity of grinding processes and is therefore analyzed in this paper as well as the strongly depending selection of dressing cycles initiated by the monitoring algorithm.

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Abrasion Monitoring and Automatic Chatter Detection in Cylindrical Plunge Grinding

Cited by 27 publications

References 6 publications

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

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

A new method for the prediction of chatter stability lobes based on dynamic cutting force simulation model and support vector machine

Monitoring of grinding wheel defects using recursive estimation

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