Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries

2022 ◽  
Vol 105 ◽  
pp. 105748
Author(s):  
En-Ze Wang ◽  
Chien-Chiang Lee ◽  
Yaya Li
Keyword(s):  
Energy Intensity ◽  
Industrial Robots ◽  
The Impact

Three-Dimensional Decomposition Models for Chinese Manufacturing Subsector over 1996-2008

2013 ◽  
Vol 291-294 ◽  
pp. 3004-3013
Author(s):  
Ding Ma ◽  
Li Ning Wang ◽  
Wen Ying Chen
Keyword(s):  
Energy Intensity ◽  
Three Dimensional ◽  
Ghg Emissions ◽  
Carbon Intensity ◽  
Emissions Reduction ◽  
Country Level ◽  
Rapid Economic Growth ◽  
Decomposition Models ◽  
Energy And Climate Policy ◽  
The Impact

At a time of increased international concern and negotiation for GHG emissions reduction, country studies on the underlying effects of GHG growth gain importance. China experienced continuous, rapid economic growth over the past. At the same time, energy consumption and CO2 emissions increased rapidly while the energy intensity and carbon intensity showed a downward trend at country level. What factors were driving this change? What measures can be adopted to ensure the continual decrease of energy intensity and carbon intensity? The refined IDA method is employed in this paper to identify the impact of each factor. A year-by-year decomposition is carried out at sector level, and various interesting results on the underlying effects are found. The results yield important hints for the planning of energy and climate policy.

scholarly journals Structural Change and Its Impact on the Energy Intensity of Agricultural Sector in China

2018 ◽  
Vol 10 (12) ◽  
pp. 4591 ◽  
Author(s):  
Hongyun Han ◽  
Shu Wu
Keyword(s):  
Agricultural Production ◽  
Energy Intensity ◽  
Agricultural Sector ◽  
Scale Economy ◽  
Policy Implications ◽  
Vegetable Production ◽  
Regional Heterogeneity ◽  
Fuel Price ◽  
Agricultural Structure ◽  
The Impact

China’s agricultural structure has undergone significant changes for the past four decades, mainly presenting as the fall of sown proportion of grain crops and the rise of vegetables, as has its energy consumption. Employing the panel data on 30 provinces during 1991–2016, this paper empirically explores the impact of agricultural structure changes (ASC) on the energy intensity of agricultural production (EIAP), direct energy intensity of agricultural production (DEIAP) and indirect energy intensity of agricultural production (IEIAP) in China. Besides, the regional heterogeneity of such impact is examined. The results show that: (1) ASC increases EIAP and IEIAP significantly, while ASC decreases DEIAP, which is explained by the structural effect and different planting modes of different crops; (2) the impact in the three administrative regions is similar to national situation, except the impact of ASC on DEIAP in the West Region, which is explained by regional differences of vegetable mechanization; (3) the result of the six vegetable production regions reveals greater regional heterogeneity, and this is attributed to the scale economy effect and the incremental effect of vegetable mechanization; and (4) fuel price, income, agricultural labor, old dependency ratio, and fiscal expenditure have different but significant impacts on EIAP, DEIAP, and IEIAP. Finally, some policy implications are given.

scholarly journals EGM Toolbox—Interface for Controlling ABB Robots in Simulink

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7463
Author(s):  
Paweł Obal ◽  
Piotr Gierlak
Keyword(s):  
Industrial Robots ◽  
Control Algorithms ◽  
Industrial Robotics ◽  
Extensive Program ◽  
The Impact

The development of industrial robotics requires the use of increasingly sophisticated control algorithms. In modern tasks posed by industry, it is not sufficient for the manipulator to move along a programmed path, reaching individual points with the greatest accuracy. There is a need for solutions that can allow detection and avoidance of obstacles appearing on the robot’s path and that can compensate the path for low-repetitive workpieces, adjust the strength of the impact of manipulator tools on the workpiece or enable safe cooperation of manipulators with people. To support this development, this work proposes an interface for controlling industrial robots in the Simulink environment. With its use, we can easily test our control algorithms using an external controller without the need to write an extensive program in the RAPID language. The robot controller’s task is to control the drives to achieve the set trajectory.

The Response of Small Manufacturers to the Energy Environment — an Exploratory Study

1978 ◽  
Vol 3 (2) ◽  
pp. 16-27 ◽  
Author(s):  
Samuel I. Doctors ◽  
Liam Fahey ◽  
G. Richard Patton
Keyword(s):  
Energy Conservation ◽  
Exploratory Study ◽  
Energy Intensity ◽  
Energy Savings ◽  
Weather Conditions ◽  
Improve Energy Efficiency ◽  
Inhibiting Factors ◽  
Energy Environment ◽  
The Impact ◽  
Small Manufacturers

This research examines the impact of the severe energy/weather conditions during the Winter 1976–77 on smaller manufacturers in Western Pennsylvania. It was found that size of firm, energy intensity and extent of energy curtailment were not related (statistically) to the kind and extent of firms' energy conservation programs and/or the nature of the managerial response to the above mentioned conditions. The sample firms had made few major commitments to improve energy efficiency. Lack of capital resources and a perception that energy savings would not significantly affect profitability emerge as major inhibiting factors to investment in energy conservation.

scholarly journals Factors Affecting Energy-Related Carbon Emissions in Beijing-Tianjin-Hebei Region

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Jing-min Wang ◽  
Yu-fang Shi ◽  
Xue Zhao ◽  
Xue-ting Zhang
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Structure ◽  
Factors Affecting ◽  
Economic Output ◽  
Level Model ◽  
The Impact ◽  
The Relationship

Beijing-Tianjin-Hebei is a typical developed region in China. The development of economy has brought lots of carbon emissions. To explore an effective way to reduce carbon emissions, we applied the Logarithmic Mean Divisia Index (LMDI) model to find drivers behind carbon emission from 2003 to 2013. Results showed that, in Beijing, Tianjin, and Hebei, economic output was main contributor to carbon emissions. Then we utilized the decoupling model to comprehensively analyze the relationship between economic output and carbon emission. Based on the two-level model, results indicated the following: (1) Industry sector accounted for almost 80% of energy consumption in whole region. The reduced proportion of industrial GDP will directly reduce the carbon emissions. (2) The carbon factor for CO2/energy in whole region was higher than that of Beijing and Tianjin but lower than that of Hebei. The impact of energy structure on carbon emission depends largely on the proportion of coal in industry. (3) The energy intensity in whole region decreased from 0.79 in 2003 to 0.40 in 2013 (unit: tons of standard coal/ten thousand yuan), which was lower than national average. (4) The cumulative effects of industrial structure, energy structure, and energy intensity were negative, positive, and negative, respectively.

scholarly journals Energy Intensity Determinants Based on Structure-oriented Cointegration by Embedding a Knowledge Box in a Time Series Model: Evidence From Iran

2021 ◽  
Author(s):  
Parisa Esmaeili ◽  
Meysam Rafei
Keyword(s):  
Financial Development ◽  
Energy Intensity ◽  
Trade Openness ◽  
Decomposition Analysis ◽  
Directed Acyclic Graphs ◽  
Impulse Response Functions ◽  
Government Investment ◽  
Long Run ◽  
Oil Revenues ◽  
The Impact

Abstract Energy intensity reduction is an exigent issue for Iran, where energy consumption is so high. Therefore, finding effective policies to reduce energy intensity is important. With this in mind, the impact of financial development, government investment, oil revenues, and trade openness on energy intensity is assessed in this study. We combined Structural Vector Error Correction Model (SVECM) and Directed Acyclic Graphs (DAG) technique to examine the relationships between study variables. The results of DAG prove that financial development, government investment, oil revenues, and trade openness influence the intensity of energy. Besides, the significant and long-run relationships among variables allowed us to apply SVECM. Impulse response functions and variance decomposition analysis indicate that government investment, oil revenues, and trade openness are negatively associated with the intensity of energy. Also, financial development positively influences energy intensity. Meanwhile, the impact of government investment is greater than oil revenues, trade openness, and financial development impacts. So, Government investment is the most effective policy regarding optimizing the consumption of energy and reducing energy intensity. We also advise policymakers to use oil revenues to increase government investment, enhancing the level of trade openness, and tax to the private sector to improve the level of energy intensity.

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