Investigation of Machining Parameters for Multiple Response Optimization in Microelectrodischarge Milling

This paper investigated the influence of three micro electrodischarge milling process parameters, which were feed rate, capacitance, and voltage. The response variables were average surface roughness (R a ), maximum peak-to-valley roughness height (R y ), tool wear ratio (TWR), and material removal rate (MRR). Statistical models of these output responses were developed using three-level full factorial design of experiment. The developed models were used for multiple-response optimization by desirability function approach to obtain minimum R a , R y , TWR, and maximum MRR. Maximum desirability was found to be 88%. The optimized values of R a , R y , TWR, and MRR were 0.04, 0.34 μm, 0.044, and 0.08 mg min−1, respectively for 4.79 μm s−1 feed rate, 0.1 nF capacitance, and 80 V voltage. Optimized machining parameters were used in verification experiments, where the responses were found very close to the predicted values.

Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRC)

In this study, 39 sets of hard turning (HT) experimental trials were performed on a Mori-Seiki SL-25Y (4-axis) computer numerical controlled (CNC) lathe to study the effect of cutting parameters in influencing the machined surface roughness. In all the trials, AISI 4340 steel workpiece (hardened up to 69 HRC) was machined with a commercially available CBN insert (Warren Tooling Limited, UK) under dry conditions. The surface topography of the machined samples was examined by using a white light interferometer and a reconfirmation of measurement was done using a Form Talysurf. The machining outcome was used as an input to develop various regression models to predict the average machined surface roughness on this material. Three regression models - Multiple regression, Random Forest, and Quantile regression were applied to the experimental outcomes. To the best of the authors’ knowledge, this paper is the first to apply Random Forest or Quantile regression techniques to the machining domain. The performance of these models was compared to each other to ascertain how feed, depth of cut, and spindle speed affect surface roughness and finally to obtain a mathematical equation correlating these variables. It was concluded that the random forest regression model is a superior choice over multiple regression models for prediction of surface roughness during machining of AISI 4340 steel (69 HRC).

Examination of the flow rheological and textural properties of polymer gels composed of poly(methylvinylether-co-maleic anhydride) and poly(vinylpyrrolidone): rheological and mathematical interpretation of textural parameters.

The purpose of this study was to mathematically characterize the effects of defined experimental parameters (probe speed and the ratio of the probe diameter to the diameter of sample container) on the textural/mechanical properties of model gel systems. In addition, this study examined the applicability of dimensional analysis for the rheological interpretation of textural data in terms of shear stress and rate of shear. Aqueous gels (pH 7) were prepared containing 15% w/w poly(methylvinylether-co-maleic anhydride) and poly(vinylpyrrolidone) (PVP) (0, 3, 6, or 9% w/w). Texture profile analysis (TPA) was performed using a Stable Micro Systems texture analyzer (model TA-XT 2; Surrey, UK) in which an analytical probe was twice compressed into each formulation to a defined depth (15 mm) and at defined rates (1, 3, 5, 8, and 10 mm s-1), allowing a delay period (15 s) between the end of the first and beginning of the second compressions. Flow rheograms were performed using a Carri-Med CSL2-100 rheometer (TA Instruments, Surrey, UK) with parallel plate geometry under controlled shearing stresses at 20.0°?±?0.1°C. All formulations exhibited pseudoplastic flow with no thixotropy. Increasing concentrations of PVP significantly increased formulation hardness, compressibility, adhesiveness, and consistency. Increased hardness, compressibility, and consistency were ascribed to enhanced polymeric entanglements, thereby increasing the resistance to deformation. Increasing probe speed increased formulation hardness in a linear manner, because of the effects of probe speed on probe displacement and surface area. The relationship between formulation hardness and probe displacement was linear and was dependent on probe speed. Furthermore, the proportionality constant (gel strength) increased as a function of PVP concentration. The relationship between formulation hardness and diameter ratio was biphasic and was statistically defined by two linear relationships relating to diameter ratios from 0 to 0.4 and from 0.4 to 0.563. The dramatically increased hardness, associated with diameter ratios in excess of 0.4, was accredited to boundary effects, that is, the effect of the container wall on product flow. Using dimensional analysis, the hardness and probe displacement in TPA were mathematically transformed into corresponding rheological parameters, namely shearing stress and rate of shear, thereby allowing the application of the power law (??=?k?n) to textural data. Importantly, the consistencies (k) of the formulations, calculated using transformed textural data, were statistically similar to those obtained using flow rheometry. In conclusion, this study has, firstly, characterized the relationships between textural data and two key instrumental parameters in TPA and, secondly, described a method by which rheological information may be derived using this technique. This will enable a greater application of TPA for the rheological characterization of pharmaceutical gels and, in addition, will enable efficient interpretation of textural data under different experimental parameters.

Influence of process parameters on fluidised hot-melt granulation and tablet pressing of pharmaceutical powders

This study investigates the influence of process parameters on the fluidised hot melt granulation of lactose and PEG 6000, and the subsequent tablet pressing of the granules. Granulation experiments were performed to assess the effect of granulation time and binder content of the feed on the resulting granule properties such as mass mean granule size, size distribution, granule fracture stress, and granule porosity. These data were correlated using the granule growth regime model. It was found that the dominant granule growth mechanisms in this melt granulation system were nucleation followed by steady growth (PEG 10–20% w/w). However, with binder contents greater than 20% w/w, the granulation mechanism moved to the “over-wet massing” regime in which discrete granule formation could not be obtained. The granules produced in the melt fluidised bed process were subsequently pressed into tablets using an industrial tablet press. The physical properties of the tablets: fracture stress, disintegration time and friability were assessed using industry standards. These analyses indicated that particle size and binder content of the initial granules influenced the mechanical properties of the tablets. It was noted that a decrease in initial granule size resulted in an increase in the fracture stress of the tablets formed.