介绍了Kirk—Othmer Encyclopedia of Chemical Technology（化工技术百科全书）（第五版）电子图书网络版数据库，并对该数据库使用方法和检索途径作出了说明，且结合实例简单地介绍了该数据库的检索方法。

Kirk-Othmer Encyclopedia of Chemical Technology数据库介绍及实例

Taguchi S/N based optimization of machining parameters for surface roughness, tool wear and material removal rate in hard turning under MQL cutting condition

In this article, the effects of material hardness and high-pressure coolant jet over dry machining are evaluated in respect of surface roughness and cutting temperature using Taguchi L36 orthogonal array. The experimental data was analyzed using empirical cumulative distribution function and box plot with respect to material hardness and machining environment. Afterward, optimization of the quality responses is performed using signal-to-noise ratio. As part of Taguchi optimization, the “smaller is better” was adopted as optimization principle; the design of experiment was used for parameters orientation, and the analysis of variance was used for determining the effects of control factors. For the present experimental studies, three types of hardened steels (40 HRC, 48 HRC, and 56 HRC) were turned by coated carbide insert at industrial speed–feed combinations under both dry and high-pressure coolant jet. Depth of cut, being a less significant parameter, was kept fixed. The high-pressure coolant jet was found successful in reducing cutting temperature, surface roughness, and tool wear. The statistical analysis showed that work material hardness is the most significant factor for both cutting temperature and surface roughness. However, for surface roughness, other variables exerted somewhat similar contribution, while in determining the cutting temperature, the environment demonstrated crucial role. The confirmation tests showed 15.85 and 0.28 % error in predicting surface roughness and cutting temperature, respectively.

https://link.springer.com/content/pdf/10.1007%2Fs00170-016-8810-2.pdf

Optimization of surface roughness and cutting temperature in high-pressure coolant-assisted hard turning using Taguchi method

Investigation of progressive tool wear for determining of optimized machining parameters in turning

In this study, Taguchi method has been applied to evaluate the effect of cryogenically treated tools in turning of Hastelloy C22 super alloy on surface roughness. The optimum parameters (cryogenic treatment, cutting speed, and feed rate) of turning were determined by using the Taguchi experimental design method. In Taguchi method, L9 orthogonal array has been used to determine the signal noise (S/N) ratio. Analysis of ANOVA was carried out to identify the significant factors affecting surface roughness. The statistical analysis indicated that feed rate, with a contribution percentage as high as 87.64 %, had the most dominant effect on machining performance, followed by the cryo-treated tools treatment and cutting speed, respectively. The confirmation tests indicated that it is possible to improve surface roughness significantly by using the Taguchi method. Surface roughness was improved by 28.3 and 72.3 % by shallow (CT1) cryogenic treatment and deep cryogenic treatment (CT2) applied on cementite carbide tools (UT). It found that wear resistance of tungsten carbide insert was increased by shallow and deep cryogenic treatments.

The effects of cryogenic-treated carbide tools on tool wear and surface roughness of turning of Hastelloy C22 based on Taguchi method

Enhancing the performance of cutting tools is an important factor in reducing production costs. Cutting tools are subjected to processes such as heat treatment and coating in order to improve their performance. Cryogenic treatment, which is also known as sub-zero heat treatment, has made significant contributions to the improvement of wear resistance, tool life, dimensional integrity, and product quality of cutting tools. The mode of application of cryogenic treatment and the type of cutting tool both affect tool performance. Therefore, it is necessary to examine the way cryogenic treatment is applied to cutting tools and its effects on their performance. This study reviews the literature on the performance of cryo-treated cutting tools.

A review of cryogenic treatment on cutting tools

Brake pads are the most important component of an automobile braking system. In recent studies, brake pads have been produced by varying the constituents of existing compositions and by making new formulations with other friction materials. This study evaluated two sets of asbestos-free automotive brake pads produced from boron oxide (6%) and hazelnut shell (7%) dusts and seventeen other components. All ingredients were mixed and pressed to manufacture the sample eco-friendly brake pads in the same shape as commercial Clio pads. Hardness, porosity, compressibility, shear and wear tests were carried out on the samples, and the test results were compared with those of the commercial pad.

Determination of Friction-Wear Performance and Properties of Eco-Friendly Brake Pads Reinforced with Hazelnut Shell and Boron Dusts

This study focused on using the Taguchi technique to optimize the process parameters in drilling of AISI D2 steel with carbide drills to minimize the surface roughness (Ra) and thrust forces (Ff). The drilling experiments were conducted on a CNC vertical machining centre according to the L18 experimental design. Uncoated drills were classified into three groups: untreated (U), cryo-treated (CT) and cryo-treated and tempered (CTT). The experimental results showed that the CTT drills exhibited the best performance in terms of Ra and Ff due to the improved wear resistance of carbide drills after the cryogenic treatment and tempering. As a result of analysis of variance (ANOVA), it was found that the most influential parameter on both Ra and Ff was the feed rate, with percentage contributions of 66.97% and 80.07%, respectively. The results showed that the Taguchi technique is a powerful method to optimize the process parameters in drilling of tool steel.

/pdf/taguchi-optimization-of-machining-parameters-in-drilling-of-3uaou7cv0l.pdf

Taguchi optimization of machining parameters in drilling of AISI D2 steel using cryo-treated carbide drills

This paper focuses on artificial neural network (ANN)-based modeling of surface and hole quality in drilling of AISI D2 cold work tool steel with uncoated titanium nitride (TiN) and titanium aluminum nitride (TiAlN) monolayer- and TiAlN/TiN multilayer-coated-cemented carbide drills. A number of drilling experiments were conducted at all combinations of different cutting speeds (50, 55, 60, and 65 m/min) and feed rates (0.063 and 0.08 mm/rev) to obtain training and testing data. The experimental results showed that the surface roughness (Ra) and roundness error (Re) values were obtained with the TiN monolayer- and TiAlN/TiN multilayer-coated drills, respectively. Using some of the experimental data in training stage, an ANN model was developed. To evaluate the performance of the developed ANN model, ANN predictions were compared with the experimental results. It was found that the determination coefficient values are more than 0.99 for both training and test data. Root mean square error and mean error percentage values were very low. ANN results showed that ANN can be used as an effective modeling technique in accurate prediction of the Ra and Re.

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Papers

A review of cryogenic treatment on cutting tools

The effects of cryogenic-treated carbide tools on tool wear and surface roughness of turning of Hastelloy C22 based on Taguchi method

Determination of Friction-Wear Performance and Properties of Eco-Friendly Brake Pads Reinforced with Hazelnut Shell and Boron Dusts

Taguchi optimization of machining parameters in drilling of AISI D2 steel using cryo-treated carbide drills

ANN-based prediction of surface and hole quality in drilling of AISI D2 cold work tool steel