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It is reasonable to anticipate that the reduction of the crystallite size down to nanometric dimensions can significantly improve the diffusion of hydrogen atoms.
The value of the average coherent crystallite size (D) obtained for the Mg2Ni compound phase characterizing the HEBM powder (D=15 nm) and the as-pressed billet (D=18) nm is in line with literature data [21] (Fig. 3a).
The evolution of the average crystallite size during the ECAP process, on the other hand, is less complex, i.e. only a moderate crystallite size reduction is noticed in Fig. 3b (D=13 nm for ECAP 6x).
Convolutional whole profile fitting analysis of the X-ray diffractograms revealed that ECAP deformation of the powders results in a moderate crystallite size reduction (D=13 nm), while CR results in an intermediate recrystallization (up to D=37 nm) followed by subsequent nanocrystallization.

To validate the developed model, real data is collected and the model is run using Lingo software.
In the third section, the simulation of the proposed model using real data from the company is presented.
· Input variable: Input data that consists of marketing plan and procurement data (price of material in the market).
These data usually changes over time.
And in data set 2, not all CR’s sales plan can be met to get the maximum profit.

Studies of electrochemical data indicate that, TCPE reduces MS corrosion through adsorption using a mixed inhibition mechanism.
The iron atoms oxidation and the reduction of H+ ions are both retarded down by an increase in the Rct value [38], where an increase also follows the increase in Rct in the value of inhibition efficiency and a lower capacitance with an upgrade in the concentration of extract [3, 39].
Parameter Electrochemical Concentration (%) 0.0 0.5 1.0 1.5 2.0 2.5 Rs (Ω) 34.0 23.0 23.3 22.2 32.4 18.1 Rct (Ωm2) 505 850 1680 2435 3259 3552 Cdl (µFcm2) 0.63 0.31 0.16 0.093 0.081 0.075 IE (%) 0.0 40.9 69.94 79.29 84.50 85.78 Water molecules on the steel surface are swapped out for TCPE molecules as a result of the reduction in capacitance value [40].
Adsorption Isotherm Analysis Using formula Eq. 1, the surface degree cover data from the weight loss data acquired from the initial experiment were used to characterize TCPE adsorption on the MS surface [14].
The adsorption data indicates the amount of metal coated by the corrosion inhibitor molecule rises with the quantity of the additional inhibitor.

Here we emphasize that data flow should be integrated as following section - Methodology.
A reduction in Severity Ranking index can be effected only through a design change.
Contact A Contact B N/O Contact Parameter changed Conducted failure 1.92 F Forming failure 1.2 3D Geometry Drawing & Checking 0.024 0.055 Robust schemed design rule→Design Guide RD Engineer 11/18/’09 Design Guide 1.92 0.027 0.024 0.001 Conducted unstably 1.92 F Forming failure 1.44 3D Geometry Drawing & Checking 0.024 0.066 Robust schemed design rule→Design Guide RD Engineer 11/18/’09 Design Guide 1.92 0.36 0.024 0.017 Outline Deformation Conducted unstably 1.92 F Forming failure 1.44 Trial run 0.024 0.066 PFMEA ME / QC Engineer 11/18/’09 SOP SIP 1.92 0.36 0.024 0.017 Arcing stick 1.92 F Forming failure 1.2 Trial run 0.024 0.055 PFMEA ME / QC Engineer 11/18/’09 SOP SIP 1.92 0.27 0.024 0.012 Ingredient degraded Conducted unstably 1.92 F Material defect 0.36 XRF data 0.346 0.239 Approval process RD Engineer 11/18/’09 ICP data 1.92 0.18 0.346 0.120 Contact wear out 1.92 F Material defect 1.2 XRF data 0.346 0.797 Approval process RD Engineer 11/18/’09 ICP data 1.92 0.27
Armature Parameter changed Conducted failure 1.92 F Material defect 1.2 Measuring 0.024 0.055 Approval process RD Engineer 11/18/’09 Cpk data 1.92 0.27 0.024 0.012 Conducted unstably 1.92 F Material defect 1.44 Measuring 0.024 0.066 Approval process RD Engineer 11/18/’09 Cpk data 1.92 0.36 0.024 0.017 Outline deformation Conducted failure 1.92 F Material defect 1.2 Measuring 0.024 0.055 PFMEA ME / QC Engineer 11/18/’09 SOP SIP 1.92 0.27 0.024 0.012 Conducted unstably 1.92 F Material defect 1.44 Measuring 0.024 0.066 PFMEA ME / QC Engineer 11/18/’09 SOP SIP 1.92 0.36 0.024 0.017 9.
Most of FMEA will be generated during design stage is limited to specific stage without on-going and on-site data collection, despite to be concerned by usefully feedback way - 8D Report practically.

The experimental and theoretical data processing in through-diffusion methods have been described previously [16].
The measured (round) data at low concentration boundary are in agreement with the predicted (line) data from the through diffusion experiment, whereas the measured data (square) are systematically higher than predicted data at high concentration boundary.
The measured data is not agreement with predicted one.
GMZ bentonite experiments data were solid symbol (I[20], Tc[4, 22] Se[this work] and Re[15])and Kunigel-F bentonite experiments data were hollow symbol (Se[13], I[12] and Tc[12]).
Out-diffusion results of Re(VII) and Se(IV) showed a discrepancy between measured data and predicted data due to the heterogeneous porosity distribution in clay boundaries and species changed when the diffusion occurred in GMZ bentonite.

Experimental data show that for the complexes of cell-THPC-thiourea-ADP with Ca2+, the activation energies and thermal decomposition temperatures are higher than those of cell-THPC-thiourea-ADP, which shows these metal ions can increase the thermal stability of cell-THPC-thiourea-ADP.
Heat release is distributed between two broad peaks covering a wide area, resulting in a major reduction in rate of heat release and flammable products which fuel the flaming combustion reaction.
Table 2 Thermal degradation and analytical data of samples 1-3 No.

Extraction of Diffusion Correlation Information from Tracer, Interdiffusion and Ionic Conductivity Data I.V.
In terms of tracer correlation factors and atom-vacancy exchange frequencies we have the following reduction for the vacancy-wind factor: B ABBA B ABBA B A BAAB A BAAB A w)ww(cf w)ww(cf)f/f( w)ww(cf w)ww(cf)f/f( S −− −− = −− −− = 0 0 (6) There are also closely related expressions relating the two intrinsic diffusion coefficients D I A and DI B and the corresponding tracer diffusion coefficients: * * 1)( AA A A B A ABAAA I A DrD f cfcf D j j =        − = − ; * * 1)( BB B B A B ABBBB I B DrD f cfcf D j j =        − = − (7) where the r factors are also loosely described as vacancy-wind factors.
While it is tempting to apply Eq. 16 to glasses where much data have been measured, it is nonetheless much more appropriate to apply it to crystalline systems such as alkali earth silicates.

Structural analysis is performed by X Rays Diffraction and the data are treated using the RIETVELD method.
The applied current causes the reduction of H2O2 which results in a strong decrease of dihydrogen emission from the cathode. [10].
The X-ray data are collected for 2θ ranging from 10° to 60° using a monochromatic CuKα radiation with the step of 0.06° every 60s.

The data presented are useful for the analysis of the structural modifications that occur and develop during the operation of a screw compressor, with the possibility to predict a failure.
The screw compressors with oil injected screw have many advantages, such as: the rotor is directly coupled to the driving motor, which means costs reduction, oil injection ensures a tight seal between rotors and housing, namely protection against corrosion, diminution of noises, robustness and high reliability, exhaust temperature control, thus avoiding the problems caused by the dew point, tolerance to liquid particles, low vibrations.
To maintain the compressor in running condition, the following operations must be monitored, performed and entered in the register: checking of tightness, testing of oil acidity,recording of pressure, temperatures, operation electric power and voltage, check the operation of the equipment/ comparison of the operating conditions against the original data of commissioning and the Instructions Book, checking the oil condition by means of the microscope at 1000 hours, 4000 hours, 5000 hours, 7000 hours, with the associated decisions of maintenance [2,12].

Equation 2 was independently fit to tensile stress-strain data from each test.
These descriptions of the stress-strain data were used to create the strain-dependent (SDTD) model [15], and are used here to create a time-dependent tensile data (TDTD) material model.
These curves agree well with the experimental data.
The simulation results agree well with the tensile experimental data.
No tensile data are available for ε < 10-4 s-1.