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Density Reduction and Electrical Conductivity Induction in Wood Plastic Composites Asaph Ooi Wei Ern1, Tan Chun Ming1and K.
[5] Moplen HP400L data sheet, LyondellBasell Polymers
[6] CELLCOM AC 1000F, AC5000F and AC9000F data sheets, IMCD Group

Changing to this technology, other advantages were possible as the reduction in the number or parts (rivets and other fasteners to join the stiffeners to the skin), an expected reduction in the maintenance costs in 30%, the increase of the passenger comfort and leaner manufacturing processes, [10].
From these data it is concluded that the structural design can be done for a pre-estimated number of cycles, depending on the design goal of the aircraft and its maintenance procedures.
For the credible impact energy level used in the certification of composite components, 50J, experimental data [18], shows that the damage area is approximately 3000mm2.
The adoption of new materials in aeronautical primary structures can lead to higher structural efficiency in terms of weight and cost reduction.
Taking into account the assumptions presented, with CFRP a reduction in weight is achieved, of varying magnitude depending on the design goal (number of cycles) and maintenance procedures.

The sheet was cold rolled to give a 60% reduction in thickness, down to the final thickness of 0.4 mm, while about 58% of α´-martensite was formed.
The data in Fig. 3 suggests that in addition to athermal formation of martensite, new martensite is formed isothermally, the fraction being dependent on annealing temperature and duration, exactly as expected for a diffusion-controlled process.
At 550 °C and 585 °C, the martensite fraction reaches a maximum followed by continuous reduction.
After 60% reduction of cold rolling, the average microhardness of α´-martensite is 821 HV0.01 and that of austenite 684 HV0.01.
The data reveal that the tempering starts even at a Pn value as low as 13.5.

.: Cooking temperature Extruder responses Toque, die pressure and production temperature were recorded by workstation on-line automatically each second when the extruder operated steadily after 20 min, then collected data for 3 min.
Statistical analysis All data were reported as the mean±standard deviation(mean±SD).
A reduction in dough viscosity is thought to be the cause in a reduction in die pressure and percentage of torque[1].The soybean residue, feed moisture, and cooking temperature could have possibly reduced the dough viscosity.
Research showed that the viscosity generally decreased with the rising of temperature reduction[15,16], it is the main reason why the die pressure decreased while the cooking temperature increased.
A reduction of viscosity causing less friction and a lower torque, which would result in a lower product temperature, however, product temperature did not follow the trend when cooking temperature increased.

The difficulties are worsened by the uncertainty about material characteristics and lack of technical data, specifications, quality control and quality assurance procedures [9] [14].
Geographic Information System (GIS), Building Information Modelling (BIM), 3D Printing or geo-spatial data analysis [10]) are evolving in different sectors, but they are not still present in CDW management.
It is essential to develop collaborative tools, digital apps and diverse range of automated systems, as shown in Figure 3, for efficient facilitation of waste minimization/reduction and maximization of waste recovery rates towards the ultimate goal of circular economy.
The bottom-up approaches to be developed are expected to achieve reduction in waste production and CO2 emissions (mainly contributing to embodied carbon reduction).
Tam, "A system dynamics-based environmental performance simulation of construction waste reduction management in China," Waste Management, vol. 51, pp. 130-141, 2016

The functional dependence of thermal and stress-strain properties were taken according to the data presented in research papers [20 - 22].
Experimental data showed that the porosity of the initial structure was P = 12%.
After HEH HFC re-melting there was a significant reduction in roughness (Ra = 6 ± 2 μm) and improved homogeneity of the profile (PV = 4 ... 10 μm) (Fig. 3b).
Particularly, a high heating temperature can lead to changes in chemical and phase compositions as well as to the growth of residual stresses in coatings resulting in the reduction of operating properties of machine parts.
It was proved by the porosity reduction (12% of the initial structure to 1% after plasma spraying), by the absence of unmelted particles and a high-quality border between the coating and the substrate.

Input data and the scheme of simulation The formulated tasks in the present paper decided with the help of the models made on the basis of algorithms FEM.
Input data of model are presented in table 2.
Input data at simulation of the status is intense - deformed of equipment.
Analyzing obtained data, we came to a conclusion, that in this instant there was a radial flow of a material of the preform.
It has allowed to render concrete data conditions ECAE a task of a choice of the sizes of a matrix.

Instrument and Experimental Data The experiment used a particle counting contamination level tester based on covering method to monitor the oil contamination level of left adjustable pitch propeller hydraulic oil of two ships in different wear stages (A ship in stable wear stage, B ship in extension run-in stage).
The technique involves data reduction, as it attempts to represent a set of variables by a smaller number.
Data Analysis and Discussion Taking the particle diameter as the object of study, we use the MATLAB software to analysis the data of two chosen common factors that based on the factor analysis of the hydraulic oil particles of two adjustable propellers.
Conclusion (1)Factor analysis allows getting the feature extraction of Hydraulic oil particle counting data and obtaining the condensed information, as well as providing a basis for the character level information fusion
Ferrography and Spectrum Data Process of TBM Oil.

The first-hand data would pay significant utility for scientific management and sustainable utilization of the CGWCP.
Field water samples were collected by the portable filter 0.45 micron pore size of glass fiber filter paper after pressure filter, using 6P instrument (United States Myron l company) field to measure the the conductivity of water (Cond), total dissolved solids (TDS), oxidation reduction potential (ORP), water temperature and pH values.
At the same time, sampling water level data measured in the observation station in order to calculate the flow according to the function relation between the water level and flow.We used the above samples to measure water temperature, conductivity (Cond), total dissolved solids (TDS), oxidation reduction potential (ORP) and the pH value of water quality data, combined with the ion concentration characteristics in karst areas.On electrical conductivity and total dissolved solids content of analysis, as a result, the total dissolved solids (Y) and conductivity (X) linear relationship is very significant: Y=0.7168X-19.766 (R2=0.9985).
Referencing the daily flow and its water level data published by hydrologic station at 8:00, the function of the stage-discharge relation was established to calculate the siting sampling flow on the basis of the water level data, and other quotidian flows are calculated on the basis of daily flow at 8:00 published by the hydrological station administrator.
According to the riverine element fluxes formula: W=∑(Qi×Cj), ussing the concentrations of the month (Cj) and monthly averaged flow (Qi),the amounts of the section total dissolved solids and dissolved inorganic carbon output fluxes in the month ,as well as its intensity modulus is calculated on the basis of river basin area, Finally, according to the monthly data the quarterly statistics data were carried out.The calculated results were shown in table 1.

From the data, the cost of part reject and downtime demonstrates a large deduction after improvement.
Table 2 Comparison of data collection before and after improvement cost of reject parts.
Table 3 Comparison of data collection before and after improvement of manpower cost for sorting and rework process.
Table 4 Comparison of data collection before and after improvement of cycle time.
By accumulating all the cost between before and after improvement, the data collected demonstrate a significant number of total cost reduction.