Forthcoming articles

International Journal of Abrasive Technology

International Journal of Abrasive Technology (IJAT)

These articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Abrasive Technology (2 papers in press)

Regular Issues

  • Decision Support System for Principal Factors of Grinding Wheel Using Data-Mining Methodology   Order a copy of this article
    by Hiroyuki Kodama, Itaru Uotani, Kazuhito Ohashi 
    Abstract: The recommended grinding conditions are described in five factors (abrasive grain, grain size, grade, structure, and bonding material) of the three main elements (abrasive grain, bonding material, and pore) in the grinding wheel catalog data-set. As systematic arrangement is not made, grinding conditions (cutting speed, table feed, depth of cut) have to be decided on the basis of an experienced engineers information or experience. Moreover, although the setting of the five factors of the three elements of a grinding wheel is important parameter that affects the surface quality and grinding efficiency, it is difficult to determine the optimal combination of workpiece materials and grinding conditions. In this research, a support system for effectively deciding the desired grinding wheel was built by using a decision tree technique, which is one of the data-mining techniques. This system extracts a significant tendency of grinding wheel conditions from catalog data. As a result, a visualization process was proposed in correspondence to the action of the grinding wheel elements and their factors to the material characteristics of the workpiece material. In this report, we produced patterns to support selection of grinding wheels by visualizing the surface grinding wheel selection decision tendency from more amount of data, based on data mixed with JIS standard and maker's catalog data.
    Keywords: Data-mining; Decision tree; Grinding wheel; surface grinding.

  • In-process grinding wheel wear evaluation using digital image processing   Order a copy of this article
    by Bahman Azarhoushang, Sebastian Ludwig 
    Abstract: The microtopography of the grinding tool surface is essential for the result of the grinding process. Micro wear (the flattening of the abrasive grits) and loading (the adhesion of chips between or on the grits), lead to an increase in process forces and temperatures. Subsequently, poor surface qualities, dimensional and profile errors and thermal damage to the workpiece, such as grinding burn, could be induced by the grinding process. Hence, cleaning (dressing) of the grinding wheel is necessary to restore the grinding ability of the tool. Industrial processes usually have short dressing intervals to avoid scrap parts. However, short dressing intervals cause a high loss of the valuable abrasive layer of both grinding and dressing tools. A novel process-oriented measuring method is developed in this study to evaluate quickly and efficiently the surface topography of grinding tools. Images of the tool surface, after being recorded via a camera system, are evaluated by an innovative image processing software for characterizing grit flattening and loading. This article describes the developed technique and the results of the application during grinding processes. The results show a direct proportionality between the output values of the proposed method and the measured grinding forces. Hence, the developed measurement method can be used for the evaluation of the grinding ability and for an assessment of the tool life.
    Keywords: grinding; dressing; wheel wear; tool loading; tool life; image processing.