The Complexity and Strategy for Establishing Product Energy Consumption Allowance in Discrete Manufacturing Industry

2015 ◽  
Vol 51 (19) ◽  
pp. 138 ◽  
Author(s):  
Fei LIU
Keyword(s):  
Energy Consumption ◽  
Manufacturing Industry ◽  
Discrete Manufacturing

scholarly journals Mechanisms of Environmental Regulation’s Impact on Green Technological Progress—Evidence from China’s Manufacturing Sector

2021 ◽  
Vol 13 (4) ◽  
pp. 1600
Author(s):  
Weijiang Liu ◽  
Mingze Du ◽  
Yuxin Bai
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Technological Change ◽  
Environmental Protection ◽  
Technological Progress ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
The Sustainable Development ◽  
Biased Technological Change ◽  
Chinese Manufacturing Industry

As the world’s largest developing country, and as the home to many of the world’s factories, China plays a crucial role in the sustainable development of the world economy regarding environmental protection, energy conservation, and emission reduction issues. Based on the data from 2003–2015, this paper examined the green total factor productivity and the technological progress in the Chinese manufacturing industry. A slack-based measure (SBM) Malmquist productivity index was used to measure the bias of technological change (BTC), input-biased technological change (IBTC), and output-biased technological change (OBTC) by decomposing the technological progress. It also investigated the mechanism of environmental regulation, property right structure, enterprise-scale, energy consumption structure, and other factors on China’s technological progress bias. The empirical results showed the following: (1) there was a bias of technological progress in the Chinese manufacturing industry during the research period; (2) although China’s manufacturing industry’s output tended to become greener, it was still characterized by a preference for overall CO2 output; and (3) the impact of environmental regulations on the Chinese manufacturing industry’s technological progress had a significant threshold effect. The flexible control of environmental regulatory strength will benefit the Chinese manufacturing industry’s technological development. (4) R&D investment, export delivery value, and structure of energy consumption significantly contributed to promoting technological progress. This study provides further insight into the sustainable development of China’s manufacturing sector to promote green-biased technological progress and to achieve the dual goal of environmental protection and healthy economic growth.

scholarly journals Pulp and Paper Industry: Decarbonisation Technology Assessment to Reach CO2 Neutral Emissions—An Austrian Case Study

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1161
Author(s):  
Maedeh Rahnama Mobarakeh ◽  
Miguel Santos Silva ◽  
Thomas Kienberger
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Manufacturing Industry ◽  
Paper Industry ◽  
Heat Pumps ◽  
Pulp And Paper ◽  
Low Carbon ◽  
Co2 Emission Reduction

The pulp and paper (P&P) sector is a dynamic manufacturing industry and plays an essential role in the Austrian economy. However, the sector, which consumes about 20 TWh of final energy, is responsible for 7% of Austria’s industrial CO2 emissions. This study, intending to assess the potential for improving energy efficiency and reducing emissions in the Austrian context in the P&P sector, uses a bottom-up approach model. The model is applied to analyze the energy consumption (heat and electricity) and CO2 emissions in the main processes, related to the P&P production from virgin or recycled fibers. Afterward, technological options to reduce energy consumption and fossil CO2 emissions for P&P production are investigated, and various low-carbon technologies are applied to the model. For each of the selected technologies, the potential of emission reduction and energy savings up to 2050 is estimated. Finally, a series of low-carbon technology-based scenarios are developed and evaluated. These scenarios’ content is based on the improvement potential associated with the various processes of different paper grades. The results reveal that the investigated technologies applied in the production process (chemical pulping and paper drying) have a minor impact on CO2 emission reduction (maximum 10% due to applying an impulse dryer). In contrast, steam supply electrification, by replacing fossil fuel boilers with direct heat supply (such as commercial electric boilers or heat pumps), enables reducing emissions by up to 75%. This means that the goal of 100% CO2 emission reduction by 2050 cannot be reached with one method alone. Consequently, a combination of technologies, particularly with the electrification of the steam supply, along with the use of carbon-free electricity generated by renewable energy, appears to be essential.

scholarly journals Research on machine learning Algorithm optimization based on 0-1 coding

2021 ◽  
Vol 2083 (4) ◽  
pp. 042086
Author(s):  
Yuqi Qin
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Manufacturing Industry ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Algorithm Optimization ◽  
The Core ◽  
Coding Method ◽  
Discrete Manufacturing

Abstract Machine learning algorithm is the core of artificial intelligence, is the fundamental way to make computer intelligent, its application in all fields of artificial intelligence. Aiming at the problems of the existing algorithms in the discrete manufacturing industry, this paper proposes a new 0-1 coding method to optimize the learning algorithm, and finally proposes a learning algorithm of “IG type learning only from the best”.

Fine energy consumption allowance of workpieces in the mechanical manufacturing industry

Energy ◽  
2016 ◽  
Vol 114 ◽  
pp. 623-633 ◽  
Author(s):  
Wei Cai ◽  
Fei Liu ◽  
XiaoNa Zhou ◽  
Jun Xie
Keyword(s):  
Energy Consumption ◽  
Manufacturing Industry

scholarly journals An Entropy-Based Formulation for the Support of Sustainable Mass Customization 4.0

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
César Martínez-Olvera
Keyword(s):  
Energy Consumption ◽  
Mass Customization ◽  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Discrete Event ◽  
Energy Productivity ◽  
Event Simulation ◽  
Managerial Implications ◽  
Optimal Resource ◽  
Information And Communication

Industry 4.0, an information and communication umbrella of terms that includes the Internet of Things (IoT) and cyber-physical systems, aims to ensure the future of the manufacturing industry competing in a proper environment of mass customization: demand for short delivery time, high quality, and small-lot products. Within this context of an Industry 4.0 mass customization environment, success depends on its sustainability, where the latter can only be achieved by the manufacturing efficiency of the smart factory-based Industry 4.0 transforming processes. Even though Industry 4.0 is associated with an optimal resource and energy productivity/efficiency, it becomes necessary to answer if the integration of Industry 4.0 elements (like CPS) has a favorable sustainability payoff. This requires performing energy consumption what-if analyses. The original contribution of this paper is the use of the entropy-based formulation as an alternative way of performing the initial steps of the energy consumption what-if analyses. The usefulness of the proposed approach is demonstrated by comparing the results of a discrete-event simulation model of mass customization 4.0 environment and the values obtained by using the entropy-based formulation. The obtained results suggest that the entropy-based formulation acts as a fairly good trend indicator of the system’s performance parameters increase/decrease. The managerial implications of these findings are presented at the end of this document.

Analysis of Embodied Energy Consumption and Greenhouse Gas (GHG) Emissions in Chinese Manufacturing Industry

2012 ◽  
Vol 616-618 ◽  
pp. 1148-1153
Author(s):  
Dong Sun ◽  
Chu Xia Tong
Keyword(s):  
Energy Consumption ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Manufacturing Industry ◽  
Ghg Emissions ◽  
Calculation Model ◽  
Embodied Energy ◽  
Gas Emissions ◽  
Electric Equipment ◽  
Chinese Manufacturing Industry

This paper attempts to discuss the embodied energy consumption and embodied greenhouse gas emissions in manufacturing industry. Based the on input-output theory, this paper establishes the calculation model, which gives the calculation of embodied energy consumption and embodied greenhouse gas emissions of 2002 and 2007 respectively. By comparison, it draws the conclusion that the total direct energy consumption of 2007 is much more than the year of 2002, while the total embodied energy consumption is less than the year of 2002. However, Non-metallic mineral products, Metal smelting and pressing and Electric equipment and machinery perform otherwise. The reason accounting for the calculation results is that the embodied energy intensity is greatly decreased.

Energy-Flow Methodology for Thermodynamic Analysis of Manufacturing Processes: A Case Study of Welding Processes

2012 ◽  
Vol 326-328 ◽  
pp. 366-371 ◽  
Author(s):  
D. Zambrana ◽  
A. Aranda ◽  
G. Ferreira ◽  
F. Barrio
Keyword(s):  
Energy Consumption ◽  
Production Line ◽  
Energy Flow ◽  
Manufacturing Industry ◽  
High Energy ◽  
Manufacturing Processes ◽  
High Quality ◽  
Energy Unit ◽  
Welding Processes

Manufacturing processes involve the input of high quality energy and/or dissipation of low quality energy to manipulate a material; similarly the input of high quality material usually leads to the generation of low quality materials. A useful output involves the operation of conventional processes including a wide variety of functions such as lubrication, air compression, cooling, heating, pumping, etc., which have, on the one hand, high energy and material consumption and, on the other hand, losses due to an inherent departure from reversible processes. This paper presents an energy-flow methodology to determine the ratio between the additional energy required per useful energy unit for the manufacturing processes. As an application of the method proposed in this work, an assembly and welding production line is shown as a case study. This process is a common technique used in the manufacturing industry and its energy consumption depends on several parameters e.g. heat and electrical input. As a result of this study, the energy consumption of the production line has been reduced by approximately 30% from the 645.94 Wh of total energy consumption, where the consumption of real useful energy is 4% of this total.

scholarly journals Rebound Effect and Technical Learning of Energy-environmental Evaluation in Manufacturing Industry

2019 ◽  
Author(s):  
Jiang Wang ◽  
Kunyue Wang ◽  
Lijuan Wang
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Environmental Effect ◽  
Manufacturing Industry ◽  
Rebound Effect ◽  
Learning By Doing ◽  
Learning Curves ◽  
Production Environment ◽  
Environmental Evaluation ◽  
Technical Learning

We introduce a total energy and environmental evaluation method in the manufacturing industry. The method gives us a series of descriptive indexes to assess the overall environmental effect level on materials, energy, wastes and products in the life cycle process. Meanwhile, the method uses partial indexes, environmental effect factors, and correction offsets into the quantitative model to analyze the learning process and rebound effect on the energy and environment at each procedure. In this work, we choose S-shaped learning curves to describe how to decrease energy consumption and improve the technical learning by doing for recent 30 years. Also, we draw the different rebound effect curves of the total energy-environmental evaluation with technical learning method, which use the annual industrial production growth rate to show that it's significant to estimate its effect on technology changes. The ideas about the interaction of energy and production environment from material flows to energy consumption, direct us to build an example to estimate quantitatively the results with different condition factors, and realize the process improvement and develop new products.

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