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Journal articles on the topic 'Process consumption'

Author: Grafiati

Published: 28 June 2021

Last updated: 14 February 2022

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1

Melicharová, A. "Decision-making process of households on food consumption ." Agricultural Economics (Zemědělská ekonomika) 52, No. 7 (February 17, 2012): 328–34. http://dx.doi.org/10.17221/5030-agricecon.

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Decision-making process of households on food consumption is discussed in the post-Keynesian theory of household choice. Since the core assumption of uncertainty is employed, the set of consumption alternatives is restricted to the subset of the known ones. When searching for these alternatives, the consumer faces the search costs expressed by time of search. The sample of Czech households was investigated to ascertain the volume of the search and 57% of households do not seek for any information that are relevant for decision-making on foodstuff purchase. To overcome this activity, the households more likely rely on prices and the range of goods of the closest sellers to them. Searching for information on product is replaced by reliance on habits and recommendations of the others. On the contrary, the uncertainty of real purchase power is of lower significance in food consumption, because the foodstuffs meet the basic physiological needs and dispose of constrained stability in storage. Thus, households cannot always postpone (or bring forward) their consumption. In order to deal with the lack of money, households from lower income levels reduce their expenditures for foodstuffs more often than those from the higher income levels. Consequently, the relationship between the level of income and needs satiation is outlined. 

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2

Rabczak, S., D. Proszak-Miąsik, and K. Nowak. "Energy consumption in humidification process." IOP Conference Series: Earth and Environmental Science 214 (January 23, 2019): 012129. http://dx.doi.org/10.1088/1755-1315/214/1/012129.

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3

Todorova, Zdravka. "Consumption as a Social Process." Journal of Economic Issues 48, no. 3 (September 2014): 663–78. http://dx.doi.org/10.2753/jei0021-3624480304.

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4

Mikaeil, Reza, Babak Sohrabian, and Mohammad Ataei. "THE STUDY OF ENERGY CONSUMPTION IN THE DIMENSION STONE CUTTING PROCESS." Rudarsko-geološko-naftni zbornik 33, no. 4 (September 2018): 65–71. http://dx.doi.org/10.17794/rgn.2018.4.6.

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5

Stávková, J., and J. Turčínková. "Consumer choice process when purchasing the staple food." Agricultural Economics (Zemědělská ekonomika) 51, No. 9 (February 20, 2012): 389–94. http://dx.doi.org/10.17221/5125-agricecon.

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After 1989, there were significant changes in food consumption, both in volumes and structure. These changes happened due to various factors. The most important factors with influence on demand and food consumption were: development of income levels of Czech inhabitants, development of consumer prices of food and non-food products and services, offer and availability of products on the market, advertising and promotion, health education, joining the EU. Besides the above mentioned factors, an impact on consumption also have such factors as quality development, extent of self-provision with food products, or the degree to which the needs are satisfied. The fundamental influence on consumption has the development of consumer prices of food and capital goods and services in relations to development of incomes, thus buying power. In the last few years, there was a visible tendency to decreasing influence of prices on food consumption. The paper focuses on the development of consumption and changes in consumption patterns, motivation and attitudes. Presented data are based on the marketing research conducted by the Department of Marketing and Trade, Mendel University in Brno, in fall 2004.

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6

Ustyugov, Nikita V., and Oleg M. Protalinsky. "Managing the Enterprise Power Consumption Process." Vestnik MEI 3, no. 3 (2021): 96–102. http://dx.doi.org/10.24160/1993-6982-2021-3-96-102.

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Decisions made adopted in an enterprise power system in managing the electric energy consumption are analyzed. The urgency of the subject matter is stemming from the global-wide growth in the demand for electric energy and a systemic increase in the cost of energy resources. The study was carried out at an operating enterprise considered as an organizational and technical system. The subject area boundaries and the types of power engineering structures are determined at the enterprise. The system was decomposed into subsystems with identifying the applied organizational and technical managing/control actions. The power consumption management problem is formulated taking into account the minimization of financial costs, and its solution is found for one element. An algorithm for determining the optimal measure to be taken in the system is proposed, which offers a solution taking into account the specified criterion (financial expenditures for consumed electricity) and constraints (prototype functionality and energy payment budget). The algorithm checks the control actions in the course of system operation, which is the system lifecycle longest part. The structure of the decision making support system for managing the power consumption of an element is developed. The structure determines the sequence of measures to be taken in applying control actions with subsequently verifying the decisions made. Experimental studies were carried out on a system element, which that have demonstrated the practical applicability and financial savings, thereby testifying the possibility of further application of the study results in the power systems of enterprises belonging to all levels.

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7

Kondo, Yasuo, Yuko Itoh, Mitsugu Yamaguchi, Satoshi Sakamoto, and Kenji Yamaguchi. "Prediction Model of Power Consumption for Variable Material Removal Rate Machining Process." International Journal of Materials, Mechanics and Manufacturing 7, no. 2 (April 2019): 68–71. http://dx.doi.org/10.18178/ijmmm.2019.7.2.432.

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8

Elezaj, Shaqir. "MANUFACTURING PROCESS MANAGEMENT." Knowledge International Journal 26, no. 6 (March 18, 2019): 1571–76. http://dx.doi.org/10.35120/kij26061571e.

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Production is aimed at the production of certain products in order to meet the requirements of the consumer, then the company as and society, under certain organizational conditions of the market. In other words, consumption is a constant process, and the process of production must be a continuous process. Repetition of the production process is a complex system consisting of elimination subsystems, that is, practically from four phases that are interconnected in terms of the impact of each other, but the entire production system must be manifested as one harmonious system. Production in this system is the first stage when the products are produced, which are then distributed and exchanged through the free market, so that in the end they are subject to the process of consumption in the appropriate form, but depending on the nature of the product. In such a system, the stages of production and consumption are the most important stages of the production process, while the role of other phases in terms of mediating the mentioned phases in a deterministic sense. As it is produced for consumers-in terms of consumption, then the process of production in society is dictated by the consumption itself. This practically means that consumption is always the basis and goal of production.

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9

Alotaibi, Sorour, Osama Ibrahim, Yu Wang, and Tengfei Luo. "Exergy Analysis of Directional Solvent Extraction Desalination Process." Entropy 21, no. 3 (March 25, 2019): 321. http://dx.doi.org/10.3390/e21030321.

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This paper presents an exergy analysis to evaluate the performance of a continuous directional solvent extraction (DSE) desalination process using octanoic acid. The flow of exergy was calculated for each thermodynamic state and balanced for different components of the system to quantify the inefficiencies in the process. A parametric study was performed to evaluate the impact of three critical design variables on exergy consumption. The parametric study reveals that the total exergy input decreases significantly with an increase in heat exchanger effectiveness. The results also indicate that the heat exchangers account for the highest exergy destruction. The total exergy consumption, however, has a slightly declining trend as the recovery-ratio increases. There is a small variation in the total exergy consumption, within the uncertainty of the calculation, as the highest process temperature increases. When compared to conventional desalination processes, the exergy consumption of the DSE, with heat recovery of 90%, is comparable to those of multi-stage flashing (MSF), but much higher than reverse osmosis (RO). Octanoic acid, which has low product water yield, is identified as the primary factor negatively impacting the exergy consumptions. To exploit the low-grade and low-temperature heat source feature of the DSE process, directional solvents with higher yield should be identified or designed to enable its full implementation.

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10

Oda, Yohei, Yoshikazu Kawamura, and Makoto Fujishima. "Energy Consumption Reduction by Machining Process Improvement." Procedia CIRP 4 (2012): 120–24. http://dx.doi.org/10.1016/j.procir.2012.10.022.

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11

Silva, F. J. G., F. Ferreira, M. C. S. Ribeiro, Ana C. M. Castro, M. R. A. Castro, M. L. Dinis, and A. Fiúza. "Optimising the energy consumption on pultrusion process." Composites Part B: Engineering 57 (February 2014): 13–20. http://dx.doi.org/10.1016/j.compositesb.2013.09.035.

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12

Marrocco, V., F. Modica, I. Fassi, and G. Bianchi. "Energetic consumption modeling of micro-EDM process." International Journal of Advanced Manufacturing Technology 93, no. 5-8 (June 22, 2017): 1843–52. http://dx.doi.org/10.1007/s00170-017-0606-5.

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13

Chirkov, V. K. "Study of random process traction electric consumption." Вестник Ростовского государственного университета путей сообщения, no. 1 (2021): 169–73. http://dx.doi.org/10.46973/0201-727x_2021_1_169.

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14

Triyanto, Agus. "Energy Consumption Analysis to Detect Process Failure in Rubber Compound Mixing Process." ACMIT Proceedings 5, no. 1 (March 19, 2019): 92–98. http://dx.doi.org/10.33555/acmit.v5i1.79.

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There are many ways to detect the abnormality of rubber mixing process regardless of the availability of indicator system of the abnormality. One way is to detect the problem after the result of rubber production tested by laboratory teams. Abnormality will be late to be anticipated because the result of the test will appear after 8 to 10 batch afterward. The abnormality in the mixing process will be detected if the results of the testing compound are out of the specification. The energy consumption will be measured for every batch by using the internal current sensor in the AC motor main drive. By reading the figure of measurement, energy consumption character will be identified and the specification standard of energy consumption can be defined. The process will follow the specification standard of energy consumption and abnormality condition will be corrected immediately.

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15

Cao, Yan Cui, Feng Gao, Zhi Hong Wang, Xian Zheng Gong, and Xiao Qing Li. "Analysis on Influence Factors of Greenhouse Gas Emissions of Magnesium Production Process." Materials Science Forum 847 (March 2016): 321–27. http://dx.doi.org/10.4028/www.scientific.net/msf.847.321.

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Magnesium is a promising lightweight and green metallic engineering material, but the environmental impact of primary magnesium production stage, especially greenhouse gas (GHG) emissions cannot be ignored. In this study, the life cycle energy consumption and GHG emissions caused by the production of primary magnesium in the years of 2003-2013 in China were calculated; the factor decomposition was conducted to analyze the GHG emissions of magnesium production process by using logarithmic mean Divisia index method (LMDI), including energy GHG emission factors, energy structure, energy consumption per ton of primary magnesium, production, emissions per unit of dolomite and ferrosilicon, and dolomite and ferrosilicon consumptions per ton of primary magnesium. The results showed that GHG emissions of primary magnesium production increased 260.29*104 t CO2eq in total from 2003 to 2013. The variety magnesium production contributed the biggest part of GHG emissions, accounting for 418.17%. The energy structure took second place on the contribution of GHG emissions, accounting for-161.49%. The nest part was energy consumption per ton of primary magnesium, accounting for-138.97%. While, the contribution of energy GHG emission factors, emissions per unit of dolomite and ferrosilicon, and dolomite and ferrosilicon consumptions per ton of primary magnesium was relatively small, which were 0.88%, 0.00% -2.72% -4.73% and-11.13%, respectively. Thus, it is the key methods to reduce GHG emissions by optimizing the energy structure and decreasing the energy consumption.

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16

Bianchi, B., and P. Catalano. "Power consumption and quality features in the hammer crushing process for olive oil production." Grasas y Aceites 47, no. 3 (June 30, 1996): 136–41. http://dx.doi.org/10.3989/gya.1996.v47.i3.853.

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17

Prasetyaningrum, Aji, Dessy Ariyanti, Widayat Widayat, and Bakti Jos. "Copper and Lead Ions Removal by Electrocoagulation: Process Performance and Implications for Energy Consumption." International Journal of Renewable Energy Development 10, no. 3 (January 20, 2021): 415–24. http://dx.doi.org/10.14710/ijred.2021.31665.

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Electroplating wastewater contains high amount of heavy metals that can cause serious problems to humans and the environment. Therefore, it is necessary to remove heavy metals from electroplating wastewater. The aim of this research was to examine the electrocoagulation (EC) process for removing the copper (Cu) and lead (Pb) ions from wastewater using aluminum electrodes. It also analyzes the removal efficiency and energy requirement rate of the EC method for heavy metals removal from wastewater. Regarding this matter, the operational parameters of the EC process were varied, including time (20−40 min), current density (40−80 A/m2), pH (3−11), and initial concentration of heavy metals. The concentration of heavy metals ions was analyzed using the atomic absorption spectroscopy (AAS) method. The results showed that the concentration of lead and copper ions decreased with the increase in EC time. The current density was observed as a notable parameter. High current density has an effect on increasing energy consumption. On the other hand, the performance of the electrocoagulation process decreased at low pH. The higher initial concentration of heavy metals resulted in higher removal efficiency than the lower concentration. The removal efficiency of copper and lead ions was 89.88% and 98.76%, respectively, at 40 min with electrocoagulation treatment of 80 A/m2 current density and pH 9. At this condition, the speciﬁc amounts of dissolved electrodes were 0.2201 kg/m3, and the energy consumption was 21.6 kWh/m3. The kinetic study showed that the removal of the ions follows the first-order model.

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18

Zhang, Gao Bo, Shuan Shi Fan, Xue Mei Lang, and Yan Hong Wang. "Process Simulation Research of CH4/N2 Separation." Advanced Materials Research 403-408 (November 2011): 585–92. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.585.

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The separation energy consumption of methane and nitrogen mixture of 3 kinds of typical method, Cryogenic (DC), Pressure Swing Absorption (PSA) and Membrane (MEM), was calculated by Aspen Plus in this paper. The result shows that at 35°C, the ratio of methane and nitrogen is 1, the separation energy consumption of 3 methods are 5.2, 3.6 and 2.6×104kJ/kmol, respectively. The ratio of calculated energy consumption to theoretical consumption is 2.3, 1.6 and 1.2, the energy consumption of DC is the highest, then PSA, MEM is lowest. This work is to give some reference for the selection of CH4/N2 separation.

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19

Vigants, Edgars, Girts Vigants, Ivars Veidenbergs, Dace Lauka, Krista Klavina, and Dagnija Blumberga. "Analysis of Energy Consumption for Biomass Drying Process." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (June 17, 2015): 317. http://dx.doi.org/10.17770/etr2015vol2.625.

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<p class="R-AbstractKeywords"><em><span lang="EN-US">This study is dedicated to the analysis of the drying process energy consumption. In order to evaluate the main energetic processes that consume the most energy, the energy consumption of each individual drying process with and without air recirculation was modelled. The model shows that drying agent (air) recirculation is not an energy-saving operation, since it increases the total electricity and heat consumption. Recirculation of the drying agent increases the moisture content of the drying agent at the dryer entrance, which increases the need for fresh air in the dryer so that it can absorb the evaporating moisture from the dried material. An increased flow of the drying agent in the dryer increases the heat and electricity consumption.</span></em></p>

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20

Huang, Xiaoqi, Honggui Han, and Junfei Qiao. "Energy consumption model for wastewater treatment process control." Water Science and Technology 67, no. 3 (February 1, 2013): 667–74. http://dx.doi.org/10.2166/wst.2012.563.

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Wastewater treatment must satisfy discharge requirements under specified constraints and have minimal operating costs (OC). The operating results of wastewater treatment processes (WWTPs) have significantly focused on both the energy consumption (EC) and effluent quality (EQ). To reflect the relationship between the EC and EQ of WWTPs directly, an extended Elman neural network-based energy consumption model (EENN-ECM) was studied for WWTP control in this paper. The proposed EENN-ECM was capable of predicting EC values in the treatment process. Moreover, the self-adaptive characteristic of the EENN ensured the modeling accuracy. A performance demonstration was carried out through a comparison of the EC between the benchmark simulation model No.1 (BSM1) and the EENN-ECM. The experimental results demonstrate that this EENN-ECM is more effective to model the EC of WWTPs.

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21

González, Matı́as, and Carmelo J. León. "Consumption process and multiple valuation of landscape attributes." Ecological Economics 45, no. 2 (June 2003): 159–69. http://dx.doi.org/10.1016/s0921-8009(02)00279-3.

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22

Xiao-Ping, Jia, Wang Fang, Xiang Shu-Guang, Tan Xin-Sun, and Han Fang-Yu. "Minimum energy consumption process synthesis for energy saving." Resources, Conservation and Recycling 52, no. 7 (May 2008): 1000–1005. http://dx.doi.org/10.1016/j.resconrec.2008.03.005.

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23

Takase, Chikako. "Changing consumption and production patterns - the Marrakech process." Natural Resources Forum 29, no. 4 (November 2005): 404–7. http://dx.doi.org/10.1111/j.1477-8947.2005.00150.x.

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24

Yuan, Jun, and Victor Nian. "Ship Energy Consumption Prediction with Gaussian Process Metamodel." Energy Procedia 152 (October 2018): 655–60. http://dx.doi.org/10.1016/j.egypro.2018.09.226.

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25

Samukawa, Tetsuo, Kazuki Shimomoto, and Haruhiko Suwa. "Estimation of In-Process Power Consumption in Face Milling by Specific Energy Consumption Models." International Journal of Automation Technology 14, no. 6 (November 5, 2020): 951–58. http://dx.doi.org/10.20965/ijat.2020.p0951.

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Prediction of energy consumption in the entire production system is crucial for managing production and pursuing environmentally friendly manufacturing. One critical issue that must be addressed to realize green manufacturing is to construct a method for predicting the electric power consumed by each manufacturing device. To address this problem, we have proposed a regression-based power consumption model to predict in-process power consumption based on the strong correlation between MRR and SEC. This study is an extension of our previous work, and here, we conducted face milling experiments by utilizing ten different materials to demonstrate the applicability and generalization capability of the model. We focused on the face milling process and measured the power consumption of the machine tool during the milling process. We also determined the characteristics of the in-process power consumption in face milling from the viewpoint of SEC and MRR and the influence of the work material on SEC. The prediction accuracy of the proposed model is demonstrated by comparison with a conventional model. It was revealed that the proposed model can describe the influence of the entire machine tool on power consumption depending on the characteristics of the work materials.

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26

Deng, Zhaohui, Hua Zhang, Yahui Fu, Linlin Wan, and Wei Liu. "Optimization of process parameters for minimum energy consumption based on cutting specific energy consumption." Journal of Cleaner Production 166 (November 2017): 1407–14. http://dx.doi.org/10.1016/j.jclepro.2017.08.022.

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27

Kováč, J., J. Krilek, and M. Mikleš. "Energy consumption of chipper coupled to a universal wheel skidder in the process of chipping wood." Journal of Forest Science 57, No. 1 (January 25, 2011): 34–40. http://dx.doi.org/10.17221/27/2010-jfs.

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The chipper for chips is an energy consuming machine. Many factors influence the result of chipping which influence the whole process. The paper deals with the process of wood chipping by a chipper in order to determine its energy consumption. The main purpose was the determination of input power and comparison of revolution frequency on the outlet shaft of a skidder regarding the dimension of the torque depending on variable parameters which characterize the process of wood chipping during the measurement and the analysis of energy consumption of a chipping machine was carried out.

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28

Kiswanto, Gandjar, Poly Poly, and Yolanda Rudy Johan. "Toolpath strategies and management to optimize energy consumption on 3-axis CNC milling machine." E3S Web of Conferences 67 (2018): 02054. http://dx.doi.org/10.1051/e3sconf/20186702054.

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CNC milling machine is a production machine which widely used to manufacture many kinds of products. In the process of milling machining, the time needed to produce a component must be as minimum as possible to minimize the costs and its impacts on the environment. One of energy consumptions used in CNC milling machines is to supply electric motors for each axis of motions. Cutting energy consumption can be minimized by optimizing the cutting parameters, such as the cutting toolpath. Modelling and comparing the total energy consumption of the cutting process from different cutting toolpaths and strategies are important in selecting the right toolpath that has the smallest energy consumption. To achieve this goal, this study models the energy consumption during the cutting process. The model is then used to evaluate and compare different cutting toolpaths from different cutting strategies. Three prismatic and one sculptured part were used to examine the model of cutting energy consumption. A Graphical User Interface is also developed to simplify the comparison and evaluation process. Through this process it will be possible to predict energy consumption in the cutting toolpath and hence enable the selection of the right toolpath to reduce energy consumption in machining.

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29

Ballester, Pedro Peñas, and Francisco Javier Abad Garrido. "Process of desalination of low energy consumption. Energy + magnetohydrodynamics (E + MHD) desalination process." Desalination and Water Treatment 48, no. 1-3 (October 2012): 360–69. http://dx.doi.org/10.1080/19443994.2012.714093.

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30

Gu, Wenbin, Zhuo Li, Zeyu Chen, and Yuxin Li. "An energy-consumption model for establishing an integrated energy-consumption process in a machining system." Mathematical and Computer Modelling of Dynamical Systems 26, no. 6 (November 1, 2020): 534–61. http://dx.doi.org/10.1080/13873954.2020.1833045.

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31

Ciancarini, Paolo, Shokhista Ergasheva, Zamira Kholmatova, Artem Kruglov, Giancarlo Succi, Xavier Vasquez, and Evgeniy Zuev. "Analysis of Energy Consumption of Software Development Process Entities." Electronics 9, no. 10 (October 14, 2020): 1678. http://dx.doi.org/10.3390/electronics9101678.

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With the growing need for software-driven devices in modern life, the pervasive necessity of energy efficiency is also rising dramatically. Considering the importance of energy-efficient software in the IT-sphere, many companies started to search and uncover ways for minimizing energy loss. We study the software development process in terms of energy consumption. This depends on various factors that have to be monitored continuously. In this paper, we propose the Innometrics framework for monitoring the software development process and analyzing the profiles of energy consumption by user devices. The motivating idea of the project is to provide crucial insights and to clarify which development activities are the main drivers behind the energy consumption.

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32

Lv, Jing Xiang, Ren Zhong Tang, and Shun Jia. "Methodology for Calculating Energy Consumption of a Machining Process." Advanced Materials Research 472-475 (February 2012): 2736–43. http://dx.doi.org/10.4028/www.scientific.net/amr.472-475.2736.

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Due to significant environmental impact and constantly rising prices, energy consumption gets more and more attention by governments and companies. Understanding and calculating the total energy requirements as well as detailed energy breakdown of a machining process are essential tasks as machining is responsible for a large amount of energy consumption in manufacturing industry. The aim of the work reported in this paper is to develop a methodology to estimate and analyze energy consumption of a machining process. This methodology is based on the representation of a machining process as a series of activities. The energy consumption of activities is calculated combined with the energy behavior of machine tool components, and formulas for calculating total as well as detailed breakdown of energy consumption for a machining process are given. The application of the methodology is demonstrated on the turning of a simple shaft.

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33

Klocke, F., R. Schmitt, K. Arntz, M. Grosse Böckmann, A. Gasser, M. Alkhayat, J. Kerkhoff, N. Klingbeil, T. Vollmer, and M. Wegener. "Investigation and Assessment of Resource Consumption of Process Chains." Procedia CIRP 38 (2015): 234–38. http://dx.doi.org/10.1016/j.procir.2015.08.018.

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34

Herglotz, Christian, Dominic Springer, Marc Reichenbach, Benno Stabernack, and Andre Kaup. "Modeling the Energy Consumption of the HEVC Decoding Process." IEEE Transactions on Circuits and Systems for Video Technology 28, no. 1 (January 2018): 217–29. http://dx.doi.org/10.1109/tcsvt.2016.2598705.

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35

Stanislaw Slupek, Andrzej Buczek, A. "Minimization of Energy Consumption in the Blast Furnace Process." Energy Sources 22, no. 7 (August 2000): 603–9. http://dx.doi.org/10.1080/00908310050045555.

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36

Ribeiro, Inês, Paulo Peças, and Elsa Henriques. "Modelling the energy consumption in the injection moulding process." International Journal of Sustainable Manufacturing 3, no. 4 (2015): 289. http://dx.doi.org/10.1504/ijsm.2015.073815.

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37

Zhou, Wenji, Bing Zhu, Dingjiang Chen, Charla Griffy-Brown, Yaoyao Ma, and Weiyang Fei. "Energy consumption patterns in the process of China’s urbanization." Population and Environment 33, no. 2-3 (March 30, 2011): 202–20. http://dx.doi.org/10.1007/s11111-011-0133-5.

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38

Haines, Pamela S., Barry M. Popkin, and David K. Guilkey. "Modeling Food Consumption Decisions as a Two‐Step Process." American Journal of Agricultural Economics 70, no. 3 (August 1988): 543–52. http://dx.doi.org/10.2307/1241492.

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39

González-Ramírez, J. E., D. Leducq, M. Arellano, and G. Alvarez. "Energy consumption optimization of a continuous ice cream process." Energy Conversion and Management 70 (June 2013): 230–38. http://dx.doi.org/10.1016/j.enconman.2013.03.015.

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40

Wen, Jin-Song, Chen-Huan Yin, Shun-Cheng Jiang, and Gang Jin. "Study of Energy Consumption in the Injection Molding Process." Journal of Macromolecular Science, Part B 56, no. 8 (July 5, 2017): 553–67. http://dx.doi.org/10.1080/00222348.2017.1342967.

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41

Rahman Hemdi, Abdul, Umi Fatihah Md Ali, Rizal Mohamed Noor, Mohamad Irwan Yahaya, M. M. Mahadzir, Ahmad Faiz Zubair, Muhamad Othman, Melfa Yola, Muhamad Zameri Mat Saman, and Safian Sharif. "Cutting Path-associated Energy Consumption of Milling Machining Process." IOP Conference Series: Materials Science and Engineering 1003 (December 29, 2020): 012071. http://dx.doi.org/10.1088/1757-899x/1003/1/012071.

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42

Salnikov, S., and G. Karandaev. "ABOUT REDUCING ENERGY CONSUMPTION DURING THE SANDS CONCENTRATION PROCESS." Bulletin of South Ural State University series "Construction Engineering and Architecture" 16, no. 3 (2016): 47–55. http://dx.doi.org/10.14529/build160306.

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The article analyzes the results of the production study of the effect of sand-size segregation in the conical screen underflow pipeline. These results lead to the identifying of the main requirements to the construction of tapering chute. The work gives the results of the laboratory study of the tapering chute model. The results prove the possibility of sand benefication without using additional energy. The schematic diagram of sands enrichment technology in tapering chutes in the gravity hydrotransport process with the expected quality indicators is offered.

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Xia, Dehong, Yingchun Shang, Ling Ren, and Yifan Li. "Theoretical energy consumption analytical method for metal separation process." Journal of Thermal Science 19, no. 4 (July 11, 2010): 377–82. http://dx.doi.org/10.1007/s11630-010-0397-6.

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Kara, S., and W. Li. "Unit process energy consumption models for material removal processes." CIRP Annals 60, no. 1 (2011): 37–40. http://dx.doi.org/10.1016/j.cirp.2011.03.018.

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Hameed, Saqib, Hernán A. González Rojas, Antonio J. Sánchez Egea, and Amelia Napoles Alberro. "Electroplastic cutting influence on power consumption during drilling process." International Journal of Advanced Manufacturing Technology 87, no. 5-8 (March 12, 2016): 1835–41. http://dx.doi.org/10.1007/s00170-016-8562-z.

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Slováčková, Tereza, Naďa Birčiaková, and Jana Stávková. "Forecasting Alcohol Consumption in the Czech Republic." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 64, no. 6 (2016): 2133–40. http://dx.doi.org/10.11118/actaun201664062133.

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The paper deals with a forecast of developments in alcohol consumption based on current alcohol consumption per capita (expressed in litres of pure alcohol), and time series extrapolations. Alcohol consumption is to be considered from the vantage point of knowing the specifics of the product and the consequences of its excessive consumption. The predictive methodology makes use of the Box‑Jenkins method; the ARIMA model, taking into account the autocorrelation and partial autocorrelation process, which is a prerequisite for the successful identification of a time series model; model parameter estimation; appropriate transformations of time series; determining the order of differentiation and subsequent verification of the model. The chosen methodology for future trends in alcohol consumptions is a prerequisite for the proposed optional measures to control alcohol consumption in the Czech Republic. Due to the long term nature of the process to draw up and implement alcohol consumption regulation measures, the forecast covers the forthcoming 10 years.

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He, Ya Qun, Ji Jun Li, Tao Wang, and Sheng Li Hou. "The Determination of Low Consumption Repairable Air Materiel Consumption Quota." Applied Mechanics and Materials 644-650 (September 2014): 4840–43. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.4840.

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Aiming the problem of low consumption air materiel repairable parts consumption quota, the paper creates a calculation model, gives the methods and processes solving the model, and explain the solving process with examples specifically, for the development of air material consumption quota provides an effective approach for air force air materiel system.

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He, Ren Chu, and Xiao Jing Gu. "Study of Advanced Process Control Technology and its Application for Ammonia-Based Flue Gas Desulfurization Process." Advanced Materials Research 1039 (October 2014): 338–44. http://dx.doi.org/10.4028/www.scientific.net/amr.1039.338.

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As a new environmental-protection technology, large-scale ammonia-based Flue Gas Desulfurization (FGD) requires high control and process technology. The process of FGD almost includes all the operation units in chemical industry. In order to make the equipment adapt to some complex changes of original flue gas and operate on better work conditions like low energy consumption, optimum liquid/gas ratio, minimum water consumption, completely nitrites oxidization, the multivariable predictive control and soft sensor based on mechanism model are studied in this paper. And the results show that these problems of variables correlation, large delay and variables coupling of FGD are resolved. In addition, ammonia consumption is lower, by-products quality is improved, Besides, the process operation is more smooth and safe, so the equipment can run effectively and economically after carrying on advanced process control.

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Syaifudin, Noor. "Roadmap of Excise on Cigarette Policy Package in Indonesia: an Analytical Hierarchy Process Approach." Journal of Social and Development Sciences 4, no. 11 (November 30, 2013): 514–25. http://dx.doi.org/10.22610/jsds.v4i11.792.

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On national budget, the revenue from excise is keeping to increase as the consumption level of cigarette tends to increase as well. The need of high revenue to satisfy the expenditure will tend to force the government to keep this industry to be existed. However, the potential loss of the state revenue caused by the illicit products is threatening. This study attempts to address this policy problem by providing policy recommendations based on in-depth analysis and evaluation of the policy alternatives. The Analytical Hierarchy Process employed to obtain quantitative measurement of the analysis. As the need of the state revenue to satisfy the national budget, thus the high excise revenue will be required, whilst on the other side the consumption of cigarette needs to be controlled. This confirms that the increase in excise rate will affect in curbing the cigarette consumptions. As several stakeholders will be impacted in the reduction its economic output to the overall economy, thus the Government of Indonesia need to shift this impacted industries to other sectors which will obtain a better output. Finally, this paper recommends an integrated roadmap of excise policy package for controlling the cigarette consumptions in order to satisfy and ensure the national budget, curbing the cigarette consumption and managing the cigarette industries. The proposal comprises of: increasing the excise tariff, encountering the illicit cigarette, simplifying the cigarette industry structure, non tariff policy, introducing new potential excised objects, and shifting the impacted sectors.

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Jiang, Sheng-Long, Xinyue Shen, and Zhong Zheng. "Gaussian Process-Based Hybrid Model for Predicting Oxygen Consumption in the Converter Steelmaking Process." Processes 7, no. 6 (June 8, 2019): 352. http://dx.doi.org/10.3390/pr7060352.

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Oxygen is one of the most important energies used in converter steelmaking processes of integrated iron and steel works. Precisely forecasting oxygen consumption before processing can benefit process control and energy optimization. This paper assumes there is a linear relationship between the oxygen consumption and input materials, and random noises are caused by other unmeasurable materials and unobserved reactions. Then, a novel hybrid prediction model integrating multiple linear regression (MLR) and Gaussian process regression (GPR) is introduced. In the hybrid model, the MLR method is developed to figure the global trend of the oxygen consumption, and the GPR method is applied to explore the local fluctuation caused by noise. Additionally, to accelerate the computational speed on the practical data set, a K-means clustering method is devised to respectively train a number of GPR models. The proposed hybrid model is validated with the actual data collected from an integrated iron and steel work in China, and compared with benchmark prediction models including MLR, artificial neural network, support vector machine and standard GPR. The forecasting results indicate that the suggested model is able to not only produce satisfactory point forecasts, but also estimate accurate probabilistic intervals.

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