Data Mining Bisnis

Paryanto, Endri; Hafiz, Aliy

doi:10.31219/osf.io/54duz

Cited by 3 publications

(4 citation statements)

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“…As a function of the robot joint velocities and accelerations, Paes et al [9] proposed time and energy-optimal paths in a limited workspace. Paryanto and his research group [10] studied the energy profile and dynamic characteristics for a 6DOF robot with different speeds and payloads in an assembly system. The energy-optimal robot motion parameters inside the manufacturing work-cell of mechanical structure and control logics of industrial robots were modeled by Gadaleta et al [11,12].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Their study is limited to specific motion profiles that are not affected by manufacturing cycle times. Software-simulated power data were used in several studies to identify robot dynamics and predict energy-efficient robotic motion [8,16]. Pellicciari et al [17] suggested a numerical technique for lowering industrial robots' energy usage.…”

Section: Literature Reviewmentioning

confidence: 99%

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Energy-Efficient Robot Configuration and Motion Planning Using Genetic Algorithm and Particle Swarm Optimization

et al. 2022

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The implementation of Industry 5.0 necessitates a decrease in the energy consumption of industrial robots. This research investigates energy optimization for optimal motion planning for a dual-arm industrial robot. The objective function for the energy minimization problem is stated based on the execution time and total energy consumption of the robot arm configurations in its workspace for pick-and-place operation. Firstly, the PID controller is being used to achieve the optimal parameters. The parameters of PID are then fine-tuned using metaheuristic algorithms such as Genetic Algorithms and Particle Swarm Optimization methods to create a more precise robot motion trajectory, resulting in an energy-efficient robot configuration. The results for different robot configurations were compared with both motion planning algorithms, which shows better compatibility in terms of both execution time and energy efficiency. The feasibility of the algorithms is demonstrated by conducting experiments on a dual-arm robot, named as duAro. In terms of energy efficiency, the results show that dual-arm motions can save more energy than single-arm motions for an industrial robot. Furthermore, combining the robot configuration problem with metaheuristic approaches saves energy consumption and robot execution time when compared to motion planning with PID controllers alone.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Energy-Efficient Robot Configuration and Motion Planning Using Genetic Algorithm and Particle Swarm Optimization

et al. 2022

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“…The influence of ice slurry on the pump power is not a simple linear problem [15]. The optimal design of an ice slurry system should analyze and support a design process characterized by low energy consumption [16] through the optimal selection of power, e.g., pumps [17][18][19], drive unit [20][21][22], or control algorithm [23][24][25], depending on the conditions of use. Currently, most studies on ice slurry systems are based on experiments, and the microscopic characteristics of ice particles passing through different channels (vertical Slit channel [26], Rectangular Channel [27], etc.)…”

Section: Introductionmentioning

confidence: 99%

The Optimal Pumping Power under Different Ice Slurry Concentrations Using Evolutionary Strategy Algorithms

et al. 2021

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A suitable ice slurry fluid with a suitable ice concentration ratio can save operational costs. The design of the optimal ice slurry concentration focuses on finding an evolution strategy, which can further minimize the power consumption of the pump. A theoretical model was established to simulate the effect of different ice concentrations and flow rates on the performance of the pump. The data obtained were fitted by curve-fitting function. The process was modeled in the MATLAB evolutionary strategy algorithm to obtain the configuration scheme of the ice concentration and flow under different refrigeration capacities. The simulation results showed that when the required cooling capacity was 13.889 kWh, ice concentration was set to 19.68%, and flow rate was set to 2.1075 × 10−4 m3/s, the power consumption could be reduced by 23%.

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“…The ever-growing awareness of the negative consequences on the environment of the energy needs of manufacturing systems has led to the study and development of methodologies to reduce energy consumption. Industrial robots make up a significant part on the total electrical energy consumed in the manufacturing sector [1]. Studies to reduce the energy consumption of these systems have been recently reviewed by Carabin et al [2].…”

Section: Introductionmentioning

confidence: 99%

Minimization of the Energy Consumption in Industrial Robots through Regenerative Drives and Optimally Designed Compliant Elements

et al. 2020

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This paper describes a method for reducing the energy consumption of industrial robots and electrically actuated mechanisms performing cyclic tasks. The energy required by the system is reduced by outfitting it with additional devices able to store and recuperate energy, namely, compliant elements coupled in parallel with axles and regenerative motor drives. Starting from the electromechanical model of the modified system moving following a predefined periodic path, the relationship between the electrical energy and the stiffness and preload of the compliant elements is analyzed. The conditions for the compliant elements to be optimal are analytically derived. It is demonstrated that under these conditions the compliant elements are always beneficial for reducing the energy consumption. The effectiveness of the design method is verified by applying it to two test cases: a five-bar mechanism and a SCARA robot. The numerical validations show that the system energy consumption can be reduced up to the 77.8% while performing a high-speed, standard, not-optimized trajectory.

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Data Mining Bisnis

Cited by 3 publications

References 0 publications

Energy-Efficient Robot Configuration and Motion Planning Using Genetic Algorithm and Particle Swarm Optimization

Energy-Efficient Robot Configuration and Motion Planning Using Genetic Algorithm and Particle Swarm Optimization

The Optimal Pumping Power under Different Ice Slurry Concentrations Using Evolutionary Strategy Algorithms

Minimization of the Energy Consumption in Industrial Robots through Regenerative Drives and Optimally Designed Compliant Elements

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