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Abstract: The purpose of the present study is to apply data-mining methods to support the decision of reasonable cutting conditions. Although an enormous amount of information is listed in a catalog, it is not possible to know all of it. Seen from the viewpoint of the user, this enormous amount of information becomes a hindrance. For example, even if an expert worker does not look at a catalog, in end-mill processing, he can decide the appropriate processing condition efficiently from experience; however, this type of situation creates difficult problems for an unskilled worker or a skilled worker with little experience. The recommended cutting condition for every type of material is listed in a catalog together with the appropriate tool, but it takes much time and labor to search and examine the catalog to find the right tool, and this process is inefficient. The main subject of our research was to support the processing condition of the end-mill for each precision tool efficiently based on end-mill clusters. Our research applied the techniques of data mining, in particular, non-hierarchy clustering and hierarchy clustering, to catalog data. With these techniques, we applied multiple regression analysis and reached the following main conclusions. As a first step, we paid attention to the shape element of catalog data. In addition to using conventional mining processes, we grouped end-mills from the viewpoint of tool shape, which meant the ratio of dimensions, visually by applying the K-means method. We applied variable cluster analysis next to each cluster and extracted an predictor variable to represent each cluster, and we performed multiple regression analysis and derived a cutting condition decision formula. The cutting condition decision formula provided high accuracy. The accuracy was higher than the results achieved through mining of all data. A more highly precise processing condition decision formula was derived by doing mining again, excluding the peculiar data clusters such as small diameter end-mill. We understood what was effective for cutting condition decision to be factors related to blade length and the ratio of the full length, factors which have not been singled out through background knowledge or expert knowledge, but were noticed as an effect of catalog mining. [Copyright &y& Elsevier]

Regenerative chatter vibration is a typical machining problem during cutting. The frequency and phase shift of regenerative chatter can be used as indicators to suppress regenerative chatter. However, direct measurement of chatter vibration during cutting is difficult for end milling because the tool blade rotates. Therefore, chatter vibration is generally measured indirectly, for example, from cutting noise or vibration transmitted to the spindle. The type and position of the installed sensors must be appropriately selected to accurately measure chatter vibration with these methods. This selection must account for the machine tool structure, cutting conditions, and the position where the chatter vibration occurs, making the measurement methods not universally applicable. When chatter vibration occurs during cutting, a periodic pattern called a chatter mark is formed on the machined surface. The chatter mark is formed by vibration during cutting, i.e., vibration information during cutting is directly recorded. Therefore, this paper proposes a method to analyze the frequency and phase shift of chatter vibration using a two-dimensional discrete Fourier analysis of the chatter mark based on the modeled formation mechanism of chatter marks, and further validates the proposed method by elucidating the mechanism of chatter mark formed by chatter vibration. First, a cutting simulation was performed based on the vibration displacement of the tool during chatter cutting obtained experimentally. This simulation elucidates the mechanism by which the vibration information of chatter vibration can be analyzed from the chatter mark. Subsequently, the chatter vibration parameters were analyzed from the chatter mark using the proposed method. The parameters were consistent with those analyzed from the vibration displacement of the tool, confirming the effectiveness of the proposed method. • The formation mechanism of chatter marks was elucidated by simulation. • The waveform of chatter vibration during cutting cannot be analyzed from chatter mark. • A method was proposed to analyze the regenerative chatter vibration during cutting. • The proposed method enables direct analysis of regenerated chatter vibration. • The results of the proposed method and the conventional method are in good agreement. [ABSTRACT FROM AUTHOR]

Nanofibers are used in various fields and applications, such as medical care, environment protection, apparel, and agriculture; it is believed that they will continue to show substantial growth in the future. In this study, we focused on the filtration application of nanofibers. The filtration performances achieved polymeric nanofiber mass production by a melt-blowing method. First, the filtration performances of the fiber were experimentally tested with different thicknesses. Then, the computational fluid dynamics flow-analyzing software was used to simulate the pressure loss and flow resistivity of the trial-produced filter under the same conditions as those used in the experiment. Then, a three-directional physical model was proposed and used to calculate the fiber's gap size with different diameters under the same filling rate and the assumption that the fibers always exhibit uniform distribution. Consequently, it was confirmed that the trial-produced non-woven filter possessed excellent filtration abilities and that the investigated data can be used as a standard to manufacture non-woven fabric for producing high-performance filters and face masks. However, the manufacturing method of non-woven fabric filters must be investigated to satisfy both high particle filtration efficiency and low pressure loss in order to develop a high-performance filter. • The paper presents the relations among filling rate, fiber diameter, filtration efficiency and flow resistivity for high-performance filters and face masks. • Our experimental results show the relations between filter thickness and filtration efficiency. • Our proposed three-directional physical model for fiber aggregate can effectively estimate the fiber's gap size under the same filling rate and fiber diameter. • The CFD analysis and proposed flow resistivity theories are useful for accurately estimating the flow resistivity. • This paper shows a standard parameters for manufacturing high-performance filters and face masks in the future. [ABSTRACT FROM AUTHOR]