Analysis of the Energy Consumption of a Novel DC Power Supplied Industrial Robot

The energy consumption and electrical characteristics of a novel direct current (DC) power supplied industrial robot prototype are compared and analyzed with a state of the art alternating current (AC) supplied industrial robot. An extensive set of experiments shows an important reduction of the total energy consumption for different electrical power profiles measured in various robot trajectories with specific working temperatures. The recuperated energy is also analyzed in the different scenarios. Experimental results show that a DC type robot can be up to 12.5% more energy-efficient than an equivalent AC type robot

analysis of the energy consumption of a novel dc power supplied industrial robot

Abstract The energy consumption and electrical characteristics of a novel direct current (DC) power supplied industrial robot prototype are compared and analyzed with a state of the art alternating current (AC) supplied industrial robot. An extensive set of experiments shows an important reduction of the total energy consumption for different electrical power profiles measured in various robot trajectories with specific working temperatures. The recuperated energy is also analyzed in the different scenarios. Experimental results show that a DC type robot can be up to 12.5% more energy-efficient than an equivalent AC type robot

Specifying and Synthesizing Energy-Efficient Production System Controllers that Exploit Braking Energy Recuperation

Reducing the energy consumption is a major concern in industrial production systems. One approach is recuperating the braking energy of robot axes. Ideally, their acceleration and deceleration phases should be synchronized so that the braking energy of one axis can be reused directly to accelerate another. This requires a detailed alignment of the axes' trajectories, but also a careful design of the overall discrete control. Finding an optimal control strategy manually, however, is difficult, as also many functional and safety requirements must be considered. We therefore propose an automated methodology that consists of three parts: (1) A scenario-based language to flexibly specify the discrete production system behavior, (2) an automated procedure to synthesize optimal control strategies from such specifications, including PLC code generation, and (3) a procedure for the detailed trajectory optimization. We describe the methodology, focusing on parts (1) and (2) in this paper, and present tool support and evaluation results

Increasing the Energy Efficiency of Multi-robot Production Lines in the Automotive Industry

This paper quantitatively reports bout potential energy savings on robotic assembly lines for the automotive industry. The key aspect of the proposed approach is that both cell production rate and robot hardware limitations are consideredasstrictconstraints,sothatnoplantrevisionis needed. The methodology relies on: a)calculationofenergy- optimal trajectories, by means of time scaling, concerning the robots’ motion from the last process point to the home positions; b)reduction o f the energy consumption vi aearlier release of the actuator brake whentherobotsarekeptstationary. Simulation results arepresented,whicharebasedontheproductiontiming characteristicsmeasuredonarealplant

AREUS \u2013 Innovative Hardware and Software for Sustainable Industrial Robotics

Abstract\u2014 Industrial Robotics (IR) may be envisaged as the key technology to keep the manufacturing industry at the leading edge. Unfortunately, at the current state-of-the-art, IR is intrinsically energy intensive, thus compromising factories sustainability in terms of ecological footprint and economic costs. Within this scenario, this paper presents a new framework called AREUS, focusing on eco-design, eco-programming and Life Cycle Assessment (LCA) of robotized factories. The objective is to overcome current IR energetic limitations by providing a set of integrated technologies and engineering platforms. In particular, novel energy-saving hardware is firstly introduced, which aim at exchanging/storing/recovering energy at factory level. In parallel, innovative engineering methods and software tools for energy-focused simulation are developed, as well as energy-optimal scheduling of multi-robot stations. At last, LCA methods are briefly described, which are capable to assess both environmental and economic costs, linked to the flows of Material, Energy and Waste (MEW). A selected list of industrially-driven demonstration case studies is finally presented, along with future directions of improvement

Energy model for motion planning of 2D-belt press line tending robots

A current trend in production is to reduce energy consumption where possible not only to lower the cost but also to be a more energy efficient entity. This paper presents an energy model to estimate the electrical energy consumption of 2D-belt robots used for material handling in multi-stage sheet metal press lines. An estimation of the energy consumption is computed by the proposed energy model based on the robot components’ specifications, the robot path and trajectory. The proposed model can predict the energy consumption offline by simulation, and thus, before installation, avoiding the need for physical experiments. It is demonstrated that it can be used for predicting potential energy reductions achieved by optimising the motion planning. Additionally, it is also shown how to investigate the energy saving achieved by using mechanical brakes when the robot is idle. This effectively illustrates the usefulness of the proposed energy model

Advanced-to-Revolutionary Space Technology Options - The Responsibly Imaginable

Paper summarizes a spectrum of low TRL, high risk technologies and systems approaches which could massively change the cost and safety of space exploration/exploitation/industrialization. These technologies and approaches could be studied in a triage fashion, the method of evaluation wherein several prospective solutions are investigated in parallel to address the innate risk of each, with resources concentrated on the more successful as more is learned. Technology areas addressed include Fabrication, Materials, Energetics, Communications, Propulsion, Radiation Protection, ISRU and LEO access. Overall and conceptually it should be possible with serious research to enable human space exploration beyond LEO both safe and affordable with a design process having sizable positive margins. Revolutionary goals require, generally, revolutionary technologies. By far, Revolutionary Energetics is the most important, has the most leverage, of any advanced technology for space exploration applications

Energy Reduction of Robot Stations with Uncertainties

This thesis aims to present a practical approach to reducing the energy use of industrial robot stations. The starting point of this work is different types of robot stations and production systems found in the automotive industry, such as welding stations and human-robot collaborative stations, and the aim is to find and verify methods of reducing the energy use in such systems. Practical challenges with this include limited information about the systems, such as energy models of the robots; limited access to the stations, which complicates experiment and data collection; limitations in the robot control system; and a general reluctance by companies to make drastic changes to already tested and approved production systems. Another practical constraint is to reduce energy use without slowing down production. This is especially challenging when a robot station contains stochastic variations, which is the case in many practical applications. Motivated by these challenges, this thesis presents an offline method of reducing the energy use of a production line of welding stations in an automotive factory. The robot stations contain stochastic uncertainties in the form of variations in the robot execution times, and the energy use is reduced by limiting the robot velocities. The method involves collecting data, modeling the system, formulating and solving a nonlinear and stochastic optimization problem, and applying the results to the real robot station. Tests on real stations show that, with only small modifications, the energy use can be reduced significantly, up to 24 percent.The thesis also contains an online method of controlling a collaborative human-robot bin picking station in a robust and energy-optimal way. The problem is partly a scheduling problem to determine in which orders the operations should be executed, and a timing problem to determine the velocities of the robots. A particular challenge is that some model parameters are unknown and have to be estimated online. A multi-layered control algorithm is presented that continuously updates the operation order and tunes the robot velocities as new orders arrive in the system. Simultaneously, a reinforcement learning algorithm is used to update estimates of the unknown parameters to be used in the optimization algorithms

Small business innovation research. Abstracts of completed 1987 phase 1 projects

Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

Novel System Architectures by Individual Drives

Measures of individualization and integration offer a great potential for further development and optimization in hydraulic drive technology. Advantages are seen especially for energy efficiency and functionality. These potentials motivate current research activities for displacement controlled systems and for valve controlled structures. For the latter, the focus lies on strategies of independent metering. Furthermore, expected challenges for the future are discussed