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The data obtained were statistically processed to more accurately portray the current image of the degree of concern for TPM and how the TPM is approached by companies who responded to the questionnaire.
TPM – The Total Productive Maintenance focuses on the equipment functioning without flaws, increased productivity and cost reduction.
The economic environment is becoming more competitive leading to accelerated product diversification and a reduction of their life cycle.

When the results obtained from RBMTF and statistical analyses of experimental data have been compared, it has been determined that the two groups of data are coherent, and that there is not a significant difference between them.
Comparison of experimental data with RBMTF for the variation time of voltage values Fig. 2.
Comparison of experimental data with RBMTF for the variation of time with CV of voltage values Fig. 3.
The comparison between experimental data and fuzzy logic is done using statistical methods such as the coefficient of multiple determination (R2) are defined as follows, where n is the number of data patterns, yp,m indicates the predicted, tm,m is the actual value of one data point m, and m,m is the mean value of all actual data points [11].
The comparison between fuzzy logic and experimental data is done using coefficient of multiple determination.

The data was analyzed using the Pyris™ software (PerkinElmer, USA), and the percent mass loss was calculated.
The morphological changes of shellac matrices were determined utilizing HSM while the accurate thermal parameters were obtained from DSC data.
Table 2 DSC data of native shellac and shellac matrices.
The tensile test data (Table 3) suggested that the shellac filament had a high tensile strength but a poor percentage elongation and modulus of elasticity.
Table 3 Tensile test data of shellac filament.

The spectral acquisition circuit, data processing and shortage circuit are designed.
The ADC and data storage module principle diagram is shown in Fig.5.
ADC and data storage module principle diagram C.
Software Design The system software, which includes initialization module, spectral acquisition and data storage module and data transmission module, is designed with modular method.
Spetral Acquisition and Data Storage Module Spectral acquisition and data storage module mainly generates following signals: CLK of CCD, ADCLK of ADC and of FIFO, and achieves spectral acquisition, analog-digital conversion and data storage synchronous.

Data Collection Procedures The experiments were conducted at UniMAP stadium.
EMG Data Processing The sEMG signal contained the original signal measured from the muscle and it was contaminated with unavoidable different types of noise, especially during dynamic movements.
Features Extraction Feature extraction is an important method to collect useful information from the signals and remove the unnecessary data [17].
Next, the Fast Fourier Transform (FFT) was utilized to transfer the filtered data from the time domain to frequency domain at each 100-meters to get the power spectrum density then calculate the median frequency (MDF) at each 100-meters.
Phinyomark, “Feature reduction and selection for EMG signal classification.

So, it is consistent with the XRF data.
Therefore, in this paper will introduce a qualitative data of local iron sand in Banda Aceh coastal area, includes the phase identification and the nano-crystallite size of natural magnetite.
Afterwards, to determine the elemental content, phase compostion, the samples were identified using X-rays diffractometer (XRD Shimadzu, D6000) and analyzed using search-match method by comparing to the International Crystallography Diffraction Data (ICDD) database.
Fe3O4 Fe3O4 Fe3O4 Fe3O4 Fe3O4 Fe3O4 Fe3O4 TiO2 Results and Discussion The X-ray Diffraction (XRD) data was conducted the phase identification analysis by observing the angle 2θ, lattice distance factor (d), intensity (I/IO), the phase and the crystall structure.
Referring to XRD data, it is known that the particle size has changed to nanocrystals.

A statistical analysis of the experimental data led to the deduction of the equations that express the variations of the flow rate in time.
The test bench for the evaluation of spraying uniformity is measuring the amount of liquid distributed through each nozzle; the data is transmitted via a wireless system to a computer and is then processed by the means of specialized software.
The steps for performing the tests are as follows: · A file which contains the general data about the test bench (type of spraying machine, power source etc.) is generated (Fig. 3.a); a b c d Fig.3.
The software of the HERBST ED-20-900.S test bench: a) file with general data; b) file containing the testing conditions; c) file with the amount of liquid collected from each nozzle; d) deviation of the quantity distributed by each nozzle from the reference measurement
· Each test is performed during 300 hours, at a specified operating pressure; the data for each nozzle is recorded every 20 hours and compared with the initial ones.

Subsequently, an investigation based on the CCA method for gearbox condition monitoring on experimental data measured from a two-stage reduction gearbox system is undertaken.
Fig. 2a plots the original input data represented with plus and dot respectively.
In total 90 feature data are obtained, and divided into three data sets: data set 1 consists of Fig. 4 Gearbox vibration signals under different working conditions: (a) normal, (b) with cracked tooth and (c) with broken tooth.
Subsequently the CCA method is used to identify gearbox conditions with data set 2.
Sammon: A nonlinear mapping algorithm for data structure analysis.

The five phases-Sensor attachment, Data transmission, Data acquisition unit, Back end data processing, and Evaluation - represent a dynamic, flexible guideline for building effective human motion analysis and movement performance detection support tools [2, 3].
Then, scatter plot was produced from data to dig up more information.
Then the data was post-processing for noise reduction before spectrogram was built.
This data would be working in parallel with accelerometer.
All data are process under the same platform without bias.

CART algorithm is simple, suitable, speed for large sample data calculation.
If the data set S divided into two parts S1 and S2 by attribute A, the Gini coefficient changes to： Ginis=S1S*GiniS1+S2S*GiniS2 Classify node data according to the smallest attribute of Gini coefficient.
Pruning process need balance and compromise between checking the error classification in data concentration and the number of decision points in the pruning trees to get the data model without the effect of noise in the training data.
Continuing this way, produce some continuous the trees with a reduction in the number of nodes until only one node of the tree.
The first is too rely on some key attributes, namely small Gini coefficient attributes can largely impact assessment results; The second is the demand high on integrity of coal mine enterprise data, Data noise processing not good enough or enterprise lack parts of important attribute data will seriously affect the evaluation results.