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The BF no.8 expert system has five kinds of mathematical model as follows: (1) Data preprocessing model.
The data preprocessing model runs every 30 seconds
Basic Features of Expert System Models Data Preprocessing Model.
Data preprocessing is consisted of four aspects of content, i.e. 1) the validation of observed data, 2) inducing and calculating all kinds of eigenvalues (indices) for a single type or multi-type of data, 3) statistical analysis of data and 4) calculation of hourly averaged values for operational parameters.
Based on these data, the velocity reduction coefficient of coke and ores at all experimental angles were calculated backwards by using the burden distribution model, and then the regressive equations representing the relationship between the velocity reduction coefficient and the chute angle were established.

However, a lot of potential and valuable data are not been integrated, shared, used and analyzed.
The pretreatment of process data.
The data used for model building is from the actual production data of pharmaceutical factory.
In this paper, the rank of data matrix X is 3, so the number of effective components is 2.
Data source.

Determination of Bore Grinding Machine Parameters to Reduce Cycle Time Salakjitt Buddhachakaraa and Wipawee Tharmmaphornphilasb * Industrial Engineering Department, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand aboonsalakjitt@gmail.com, b * wipawee.t@eng.chula.ac.th Keywords: Design Of Experiment, Central Composite Design, Cycle Time Reduction Abstract.
With these settings the new cycle time is 2.76 second per piece or 7.38% reduction.
Boonsompong: Reduction of Tombstone Capacitor Problem by Six Sigma Technique: A Case Study of Printed Circuit Cable Assembly Line (2011 IEEE International Conference on Quality and Reliability, 2011)
Deeying: Determination of the Appropriate Laser Spot Welding Parameters to Reduce the Undercut Defect of the Suspension Using Split-Plot Design (The International Data Storage Technology Conference (DST-CON), 2011)

To collect relative data of energy consumption and emission which were produced in the stages of units operating, the resources obtaining and manufacturing, then the obtained data were arranged into inventory analysis table.
Data Sources.
Data sources for this study mainly include the datas of trade association, scientific literature, enterprise actually production running, national statistics and research reports etc
Meanwhile according to the data in table 5, the environmental impact potential of three projects was calculated and the results are shown in table 6.
Data normalization was to illustrate the relative size of potential effect.

It is described since the calibration steps until the application of this system to localize of the non-uniform thickness reduction point under biaxial fluid static expansion, to measure the bulge height time path and the thickness reduction, to analyze the FLD (Forming Limit Diagram) and the superplastic parameter strain rate.
The instrumentation parts related with pressure measurement are an electronic pressure regulator, a pressure transducer, a 12-channel Universal Input Output Module and a data acquisition system.
This curve was measured with acquisition data system, 10 Hz, through a pressure transducer.
Results and discussion For each image, the dome height, the thickness reduction and the FLD, have been analyzed and based on a non-uniform thickness reduction, it’s possible to localize the probably breaking point, as showed at Fig. 6 to 10.
Fig.6 - Non-uniform thickness reduction monitoring at stage 200, 400 and last stage 1040.

And this characteristic makes this class of mixed oxides have the excellent oxidation-reduction quality [4-7].
Sample respectively the full spectrum of 0~1200eV, and them sample each element’s narrow spectrum of related tracks, data analysis is done by narrow spectrum.
Samples have three O2 desorption peaks (α, α′ and β). α peak (~200°C) is the ordinary chemical desorption oxygen, α′ peak (~385°C) is the chemical desorption oxygen [12] of oxygen vacancies, which is released by Co3+ reduction 2Co3+ + O2- → 2Co2+ + Vo + 1/2 O2 β peak (~500-800°C) is lattice oxygen related with effect of Co ion oxidation reduction.
And nor is the reduction of O surface concentration.
The binding energy of F 1s is 684.5ev and known from standard spectral data, F is of -1 valence.

The perovskites reducibility was evaluated by temperature-programmed reduction (TPR) using methane as reduction agent.
Surface area data (SBET) of perovskites.
In Figure 3b only one reduction peak at high temperatures is observed and matches that observed in LaCeCo sample.
The global catalytic activity data for methane combustion was evaluated by the behavior of methane conversion as a function of the temperature and is showed in Figure 4.
In this case, the oxygen present in the gas phase can be adsorved and thus the reduction to Co2+ would take place in the reaction (suprafacial mechanism).

Results and Discussion Figure 1 shows the pressure distribution exerted on the die-wall for the solid cylinders in single-action pressings at 50.0% reduction in height (initial height to diameter, i.e.
The pressure build-up on the stationary punch is not significant until the compaction process reaches at 55% reduction in height.
Sometimes the consideration of average pressure is of interest since it simplifies both experimental techniques and the interpretation of the results. 166.7 204.7 195.4 274.0 221.6 216.9 357.8 279.2259.3 481.1359.1 293.0 636.8 468.6 167.6 143.3 108.1 120.8 120.4 82.2 91.2 111.8 69.1 82.3 92.1 60.666.284.6 48.0 56.2 �=0.05 �=0.10 �=0.15 �=0.20 �=0.25 136.9 232.3 161.9 224.0404.6 295.9 376.2 675.2 495.9 820.4 1565.8 1234.6 5.9 5.7 5.8 9.7 7.7 8.4 28.7 18.1 20.8 109.5 60.3 91.2 Fig. 1 The predicted pressure [MPa] distributions Fig. 2 The predicted pressure [MPa] along die and punches at 50.0% reduction in distributions along die and punches height with various friction coefficients at 25, 35, 45 and 55% reduction in (Init L/D=4.5) height with µ= 0.2 (Init L/D=8.0) The results of predicted
Experimental data by Duwez et al. [3] are compared to those from simulation (see Fig. 3(a)) and shows good agreement with the simulation results for available experimental data.
Vol. 185 (1949), p.561 100 200 300 400 500 600 700 0 5 10 15 20 25 Distance from Center [mm] Pressure on Moving Punch [MPa] µ=0.25 µ=0.20 µ=0.15 µ=0.10 µ=0.05 (a) Pressure on moving punch 0 20 40 60 80 100 120 140 160 0 5 10 15 20 25 Distance from Center [mm] Pressure on Fixed Punch [MPa] µ=0.25 µ=0.20 µ=0.15 µ=0.10 µ=0.05 (b) Pressure on fixed punch 0 50 100 150 200 250 300 350 400 450 500 0 10 20 30 40 50 Distance from Fixed Punch [mm] Pressure on Side Wall [MPa] at 551MPa at 482MPa at 413MPa µ=0.25 µ=0.20 µ=0.15 µ=0.10 µ=0.05 413MPa 482MPa 551MPa experiment [3] (c) Pressure on sidewall Fig. 3 Pressure exerted on the die and punches (50% reduction in height and Init L/D = 4.5)

Furthermore, according to Fig. 1 the standard reduction potential for Cu and Mn is–0.045VSHE and –1.18 VSHE, respectively [13].
The discharge potential of Cu2+ (about–0.045VSHE) is close to the calculated Cu2+ reduction equilibrium potential (–0.03 VSHE) based on the Nernst equation.
The addition of ammonium sulfate probably leads to shift in Cu2+cations discharging potential to a more negative levels and shifts Mn2+ reduction reactions to more positive potentials, indicating that reduction potentials of Cu and Mn get closer to each other.
These data are related to co-deposition of Cu and Mn.
The grain size of the coatings was calculated using Scherrer equation (Eq. 1) according to the data of major peak Mn (101) as follows: D=0.9λ/βcosθ (1) where l, b, and a are associated with the wave length of Cu ka1 (1.5406 Å), the integral width, and the diffraction angle of the XRD spectra, respectively.

However, in every case, it is fundamental to build a solid correlation between fatigue and the loading parameters based on limited experimental data.
Actually, fatigue test are time and money consuming and, consequently, there are not so many experimental data available.
Experimental data taken from [12] Fig. 2.
Experimental data taken from [12] In the present work, a model describing the fatigue behaviour of composite materials under spectrum loading is presented.
The model requires a limited set of fatigue data and, by fitting them through Eq. (1), it is possible to obtain the two parameters, α and β.