Methodology for the immediate detection and treatment of wheel wear in contour grinding

Xu, Liming; Niu, Mu Qing; Zhao, Da; Xing, Nuobei; Fan, Fan

doi:10.1016/j.precisioneng.2019.09.006

Cited by 15 publications

(11 citation statements)

References 20 publications

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“…Although the information provided by this parameter is quite useful, again, additional information about the evolution of the grinding wheel surface characteristics is required for a full evaluation of the process performance. There have been considerable developments in recent years in optical devices and software analysis [47][48][49][50] for evaluating the evolution of wear flat, and usually the percentage of apparent wear flat area has been used as the wear parameter [23]. In [50] an example of an image analysis application for detecting abrasive grain wear flat was presented.…”

Section: Process Monitoringmentioning

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: Process Monitoringmentioning

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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“…Integral spiral end milling cutters are widely used in the contouring milling of a complex workpiece. Numerous direct machine vision methods have been proposed to detect the failure forms of various machined tools, including turning tools [ 28 ], broaching tools [ 29 ], drill bit [ 30 ], grinding wheels [ 31 ] and inserts for turning [ 32 ] and milling [ 19 , 20 , 33 ], etc. Whereas these methods could rarely be applied to detect the failure regions on integral spiral end milling cutters due to their complex structures.…”

Section: Introductionmentioning

confidence: 99%

Wear and Breakage Detection of Integral Spiral End Milling Cutters Based on Machine Vision

et al. 2021

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Tool wear and breakage detection technologies are of vital importance for the development of automatic machining systems and improvement in machining quality and efficiency. The monitoring of integral spiral end milling cutters, however, has rarely been investigated due to their complex structures. In this paper, an image acquisition system and image processing methods are developed for the wear and breakage detection of milling cutters based on machine vision. The image acquisition system is composed of three light sources and two cameras mounted on a moving frame, which renders the system applicable in cutters of different dimensions and shapes. The images captured by the acquisition system are then preprocessed with denoising and contrast enhancing operations. The failure regions on the rake face, flank face and tool tip of the cutter are extracted with the Otsu thresholding method and the Markov Random Field image segmentation method afterwards. Eventually, the feasibility of the proposed image acquisition system and image processing methods is demonstrated through an experiment of titanium alloy machining. The proposed image acquisition system and image processing methods not only provide high quality detection of the integral spiral end milling cutter but can also be easily converted to detect other cutting systems with complex structures.

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“…In direct way, vision system and an optical microscope are used to directly detect the contour of wheel. [14][15][16] Su proposed a method for measuring wheel contours using machine vision, simplifying wheel wear measuring procedures compared with the traditional methods. 15 Jurkovic et al 16 determined the wheel profile directly with the help of projected laser raster lines.…”

Section: Introductionmentioning

confidence: 99%

“…Liu et al 24 determined the wheel contact conditions based on the iterative algorithm for groove grinding compensation research. For smooth surface grinding track, Xu et al 14 compensated grinding error by comparing wear arc radius of wheel with contour curve radius of workpiece.…”

Section: Introductionmentioning

confidence: 99%

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A compensation algorithm of tool path for grinding wheel wear in solid cutting tool flank grinding

Jiang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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In finishing machining, the quality of workpiece is significantly influenced by the performance of solid cutting tool. Solid cutting tool flank is ground by CNC tool grinder in accordance with the tool path of grinding wheel. In actual grinding process, the grinding area of wheel will be gradually worn down, resulting in the decrease of geometric accuracy of flank and even wrong profile. In order to compensate the error, a compensation algorithm of tool path for solid cutting tool flank based on grinding wheel wear is proposed. Firstly, the coordinate systems are defined for the grinding process of flank, and the orientation and location calculation model of ideal wheel with the grinding process parameters is derived. Secondly, based on the profile description of wheel wear, flank errors are analyzed. Then, the compensation algorithm for anastomosis of cutting edge and relief angle is proposed. Finally, series of experiments of simulation and actual grinding are carried out. The comparison of the results shows that the algorithm can reduce the influence of wheel wear effectively, which can also improve the grinding quality stability and prolong the service life of grinding wheel.

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Methodology for the immediate detection and treatment of wheel wear in contour grinding

Cited by 15 publications

References 20 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

Wear and Breakage Detection of Integral Spiral End Milling Cutters Based on Machine Vision

A compensation algorithm of tool path for grinding wheel wear in solid cutting tool flank grinding

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