A Simplified Machine-Tool Power-Consumption Measurement Procedure and Methodology for Estimating Total Energy Consumption

2015 ◽  
Vol 138 (5) ◽  
Author(s):  
Jang-Yeob Lee ◽  
Yong-Jun Shin ◽  
Min-Soo Kim ◽  
Eun-Seob Kim ◽  
Hae-Sung Yoon ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Machine Tool ◽  
Total Energy ◽  
Machine Tools ◽  
Measurement Procedure ◽  
Single Model ◽  
Total Energy Consumption ◽  
Cutting Energy ◽  
Energy Consumption Model ◽  
Consumption Model

Various methods have been developed to describe the energy consumption of machine tools; however, it remains challenging to accommodate the wide variety of machine tools that exist using a single model. In this paper we propose a method to model the energy consumption of machine tools by decoupling the energy of the components of the machine tool from the cutting energy. A procedure is developed to describe the characteristics of the energy consumption of machine tools, which is applied to six different machines. The experimental results show that the cutting energy can be decoupled from the component energy. In this manner, a simplified energy consumption model is developed that can be applied to a wide variety of different machine tools.

scholarly journals Minimum Energy Trajectory Optimization for Driving Systems of Palletizing Robot Joints

2018 ◽  
Vol 2018 ◽  
pp. 1-26
Author(s):  
Ying He ◽  
Jiangping Mei ◽  
Zhiwei Fang ◽  
Fan Zhang ◽  
Yanqin Zhao
Keyword(s):  
Fourier Series ◽  
Energy Consumption ◽  
Total Energy ◽  
Dynamic Model ◽  
Trajectory Optimization ◽  
Joint Torque ◽  
Total Energy Consumption ◽  
Energy Consumption Model ◽  
Energy Consumption Optimization ◽  
Consumption Model

Palletizing robot is widely used in logistics operation. At present, people pay attention to not only the loading capacity and working efficiency of palletizing robots, but also the energy consumption in their working process. This paper takes MD1200-YJ palletizing robot as the research object and studies the problem of low energy consumption optimization of joint driving system from the perspective of trajectory optimization. Firstly, a multifactor dynamic model of palletizing robot is established based on the conventional inverse rigid body dynamic model of the robot, the Stribeck friction model and the spring balance torque model. And then based on joint torque, friction torque, motion parameter, and joule’s law, the useful work model, thermal loss model of joint motor, friction energy consumption model of joint system, and total energy consumption model of palletizing robot are established, and through simulation and experiment, the correctness of the multifactor dynamic model and energy consumption model is verified. Secondly, based on the Fourier series approximation method to construct the joint trajectory expression, the minimum total energy consumption as the optimization objective, with coefficients of Fourier series as optimization variables, the motion parameters of initial and final position, and running time constant as constraint conditions, the genetic algorithm is used to solve the optimization problem. Finally, through the simulation analysis the optimized Fourier series motion law and the 3-4-5 polynomial motion law are comprehensively evaluated to verify the effectiveness of the optimization method. Moreover, it provides the theoretical basis for the follow-up research and points out the direction of improvement.

Machine-Specific Estimation of Milling Energy Consumption in Detailed Design

2021 ◽  
pp. 1-24
Author(s):  
Till Boettjer ◽  
Johan Krogshave ◽  
Devarajan Ramanujan
Keyword(s):  
Energy Consumption ◽  
Machine Tool ◽  
Machine Tools ◽  
Design Stage ◽  
Total Energy Consumption ◽  
Estimation Errors ◽  
Workpiece Material ◽  
Detailed Design ◽  
Energy Estimation ◽  
Unit Process

Abstract Manufacturing is a significant contributor to global greenhouse gas emissions and there is an urgent need to reduce the energy consumption of production processes. An important step towards this goal is proactively estimating process energy consumption at the detailed design stage. This is a challenging task as variabilities in factors such as process specifications, machine tool architecture, and workpiece geometry can significantly reduce the accuracy of the estimated energy consumption. This paper discusses a methodology for machine-specific energy estimation in milling processes at the detailed design stage based on the unit process life cycle inventory (UPLCI) model. We develop an adjusted UPLCI model that includes adjustment factors for uncertainties in machine tool specifications and the specific cutting energy of a workpiece material. To validate the adjusted UPLCI model, we conducted a case study that measured the energy consumption for machining three parts made of Aluminum 6082 on two separate three-axis vertical milling machines, a Chevalier QP2040-L and a Leadwell MCV-OP. Results show that the UPLCI model consistently overestimated the total energy consumption for machining the three validation parts across both machine tools. We also found the adjusted UPLCI model significantly reduced the estimation errors for the same tests for both machine tools.

scholarly journals A Systematic Method of Optimization of Machining Parameters Considering Energy Consumption, Machining time and Surface Roughness with Experimental Analysis

2021 ◽  
Author(s):  
Chunhua Feng ◽  
Haohao Guo ◽  
Jingyang Zhang ◽  
Yugui Huang ◽  
Shi Huang
Keyword(s):  
Experimental Data ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Cutting Parameters ◽  
Multi Objective Optimization ◽  
Systematic Method ◽  
Machining Time ◽  
Cutting Energy ◽  
Energy Consumption Model ◽  
Consumption Model

Abstract For improving energy efficiency of machining process, extensive studies have focused on how to establish energy consumption model and optimize cutting parameters. However, the existing methods lack a systematic method to promote the widespread use of energy efficiency methods in the industry. This paper proposes a systematic method integrating energy model, experiment design, and multi-objective optimization model. Firstly, the energy model is established considering cutting energy and non-cutting energy. Then, the orthogonal experiment is designed with the three levels of four factors of spindle speed, feed speed, cutting depth, and cutting width in the X and Y cutting directions. The data of energy consumption, surface quality and machining time are obtained to study the effects of different cutting elements and cutting directions. Meanwhile, the standby, spindle idling, feed, SEC, material cutting and idling feed models of the CNC machine tools are established based on the experimental data. In addition, for verifying the accuracy of the established energy consumption model, five sets of experimental data are tested that show the prediction accuracy can reach 99.4%. Finally, a multi-objective optimization model for high efficiency and energy saving of processing process is establishes to optimize the cutting parameters from the three perspectives of energy consumption, processing time and surface quality. Combining the case of milling with constraints including machine tool performance, tool life, processing procedures, and processing requirements, the Pareto solution set is used to solve the Pareto of the target model. Through drawing a three-dimensional needle graph and two-dimensional histogram, the optimal cutting parameter combination for rough machining and semi-finish machining are provided, assisting in promoting the application of the sustainable techniques in the industry.

Energy savings potential of new aeration system: Full scale trials

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
A. Lazić ◽  
V. Larsson ◽  
Å. Nordenborg
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Total Energy ◽  
Energy Savings ◽  
Treatment Plant ◽  
Full Scale ◽  
Total Energy Consumption ◽  
Aeration System ◽  
Fine Bubble ◽  
Aeration Control

The objective of this work is to decrease energy consumption of the aeration system at a mid-size conventional wastewater treatment plant in the south of Sweden where aeration consumes 44% of the total energy consumption of the plant. By designing an energy optimised aeration system (with aeration grids, blowers, controlling valves) and then operating it with a new aeration control system (dissolved oxygen cascade control and most open valve logic) one can save energy. The concept has been tested in full scale by comparing two treatment lines: a reference line (consisting of old fine bubble tube diffusers, old lobe blowers, simple DO control) with a test line (consisting of new Sanitaire Silver Series Low Pressure fine bubble diffusers, a new screw blower and the Flygt aeration control system). Energy savings with the new aeration system measured as Aeration Efficiency was 65%. Furthermore, 13% of the total energy consumption of the whole plant, or 21 000 €/year, could be saved when the tested line was operated with the new aeration system.

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