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Operator as well as equipment efficiencies have to be validated and process waste has to be assessed with reliable and precise data on macro and micro levels.
First, it consolidates the current performance data and therefore determines the baseline for efficiency improvement.
Data-driven Approach.
The process is highly based on shop floor data, thus the quality of data input and its detail is of critical importance.
To ensure this quality, experience is required in performing time studies and observations as well as in deriving the data incorporated in the production index.

Introduction CAPP (Computer Aided Process Planning) is a manufacturing process technology that used the computer aided technology to design parts from rough to finished product, is a method that convert the data of design to the data of manufacture.
In CAPP, you can use RS theory, knowledge acquisition and optimization, the use of extracted data reduction rules, and use of these rules, the automatic selection of processing methods.
In the CAPP system, with fewer code bits to a more comprehensive description of part information, the processing data of parts used in this paper was constructed by the mixed encoding system that tree structure combined with chain structure. 20 bits was used to express this encoding.
Outstanding advantages of rough set method are without any human intervention, directly extract rules from sample data to improve knowledge of process design system reliability and objectivity.
Using filing function to make the filing process documents, take process data stored in a database.

Powder X-ray diffraction (XRD) data of samples were collected on a D/max 2200 PC diffractometer (Cu Kα radiation, λ= 1.54056Å, Rigaku, Japan) for the crystal structure analysis.
Furthermore, the little wandering of Pt, Fe and Sn atoms at 350 ℃ leads to the atomic reconstruction and structure stability of NPs.[25, 26] Table 1 Electrocatalytic data of the annealed FePtSn/C, the as-synthesized FePtSn/C and the commercial Pt/C.
Wang, Synthesis of highly active and dual-functional electrocatalysts for methanol oxidation and oxygen reduction reactions, Applied Surface Science, 389 (2016) 181-189
Sun, Core/Shell Pd/FePt Nanoparticles as an Active and Durable Catalyst for the Oxygen Reduction Reaction, Journal of the American Chemical Society, 132 (2010) 7848-7849
Bent, Active MnOxElectrocatalysts Prepared by Atomic Layer Deposition for Oxygen Evolution and Oxygen Reduction Reactions, Advanced Energy Materials, 2 (2012) 1269-1277

Due to the thermodynamic data (seen in table 4) [5], it can be known that the reaction 1 occurs easily, while the reaction 2,5,6 and 7 are difficult to occur in the experimental temperature in the standard state.
It is found that the reduction nitriding of perovskite is easier than that of TiO2 when the silicate phase presented in the reduction nitriding slag is CaO·SiO2 and CaO·Al2O3·2SiO2.
High alkalinity is disadvantageous to the reduction nitriding of perovskite.
The silicate phase should be CaO·SiO2 and CaO·Al2O3·2SiO2 as possible in order to make reduction nitriding reaction occur successfully.
(Chinese) [5] Liang Yingjiao and Che Yinchang, “Thermodynamic Data Notebook of Inorganic,” Shenyang: Northeast University, in Press, 1993.

The largest slump reduction presents at the mixture with single incorporation of PAF with reduction value of 77.5 mm.
Concrete crack resistance abilities Table 5 Experimental results of Concrete crack resistance (0.9kg) Experimental group Maximum crack width ωmax [mm] Total crack areas A [mm2] Cracks reduction factor η Crack resistance performance levels Blank 2.21 1645.6 -- -- PF 0.72 143.5 0.6742 A PAF 0.54 110.4 0.7557 A CF 0.46 97.2 0.7919 A VICK-M1 0.51 101.9 0.7692 A VICK-M2 0.50 74.6 0.7738 A VICK-M3 0.44 72.4 0.8009 A VICK-M4 0.79 105.4 0.6425 A VICK-M5 0.43 66.8 0.8054 A Based on the above experimental data and graphs, it can be seen that the fiber incorporation can effectively restrain the early concrete plastic shrinkage crack.
Crack width reduction coefficient and crack area reduction coefficient are influenced by fiber type, fiber volume fraction and the way of fiber incorporation.
From the crack area reduction coefficient data, the largest one can be up to 94.09%.
The maximum crack width reduction coefficient, crack area reduction coefficient is only 2.27%, 7.73% respectively.

To evaluate the thermal behavior and overall efficiency of the system, temperature data were continuously monitored at critical locations along the kiln using open-type thermocouples.
These sensors were connected to a Medi Logger GL820 data logger, set to record temperature readings every five seconds.
The collected temperature data was later used to assess heat distribution, calculate thermal losses, and determine the energy performance of the rotary kiln system throughout the torrefaction process.
Heat Loss Analysis of the Rotary Kiln - Temperature data from steady-state periods (post-reach of torrefaction temperatures at 230, 250, and 270°C) were used for analysis
These findings, supported by the data in Table 1, affirm that temperature control and effective insulation are critical for optimizing the performance of biomass torrefaction kilns.

This could be observed in both height reductions.
The microstructure is shown in Fig. 2 along with the corresponding discrete pole figures and the orientation distribution functions for the rotated data.
The entire process was calculated based on the real process data in order to gain information about the pool shape as a function of process duration.
Consequently, the solidification angle is available as field data for the whole ingot.
Since in bulk metal forming the flow stress generally is measured in compression tests, this data was not readily available.

Asama et al. proposed the Intelligent Data Carrier (IDC) with the aim of sharing knowledge among the robots [4]-[6].
In the simulation (Fig.6), 1000 of sample testing data for the simulation was generated by randomly using normal distribution under the condition of standard deviation 0.035 cm and average 1.00 cm.
The generated data indicate the index of the quality.
This is caused by the process of random data generation by the simulator.
Kurabayashi, H.Asama et.al;”Autonomous Knowledge Acquisition and Revision of Dynamic Environment by Intelligent Data Carriers”ROBMEC2000, 2PI-33-035.

With this analysis tool, real production and process data are compared with results from scientific cryogenic tests and research and examined with regards to their applicability.
In the course of the analysis it is therefore also possible to achieve more transparency by the collection of profound operation data.
Moreover, the transfer of the manufacturing data from the CAM software is currently not completely automated.
A standardized process to extract the data in an automated process with few interfaces has to be developed reducing the risk of transmission errors.
Especially in small and medium sized companies this data is not available in a short period of time.

SiC power module VTH data as a function of temperature.
Data represents the average of 4 modules (5 parallel 20A or 2 parallel 80 A die).
On the other hand, the data shown is representative of the nominal VTH observed.
Fig. 4 shows the average measured switch forward voltage module (Vf) data for ID=100 A.
The data reflects a significant reduction in on-state 100 A conduction losses of 41% and 38% at 25 and 150°C, respectively.