Sustainable Manufacturing Series: How to Effectively Manage Robot Energy Consumption

Sustainability is a crucial consideration for manufacturers today. Taking environmental responsibility for industrial processes that typically involve heavy resource use — in energy, water, raw materials, and waste generation — is a necessary concern to sustain continued life on this planet. But the motivation is rarely that straightforward. A mixture of regulatory compliance, risk reduction, brand reputation, and more drive sustainability goals.

Although consumers are demanding more sustainability transparency from the companies they spend their money with, a manufacturer’s bottom line is often the primary impetus behind sustainability efforts. Cost savings can come in the form of energy efficiency, waste reduction, and the conservation of other resources. Sustainability often drives leaner, smarter operation, leading to fewer defects, less downtime, and lower maintenance costs.

While sustainability programs might require upfront investment, the payback is real — and often multiplies over time across cost, revenue, and risk reduction.

In this article, the first of a three-part series on sustainable manufacturing, we look specifically at the effects that robots have on your operation’s energy use. Though robots can use a significant amount of energy — particularly depending on payload and task — there are several methods you can pursue to reduce that energy footprint, including more energy-efficient motors, using the right task-appropriate robot, predictive maintenance, monitoring software, and more. Artificial intelligence (AI) is getting into the game as well, helping to optimize motion, scheduling, task planning, and more.

Innovations Enabling Lower Robot Energy Consumption

New technologies — along with the push to cut operating costs — will continue to move automation and robotics toward greater energy efficiency, notes Ed Volcic, chief regional technology officer for North America at KUKA Robotics. KUKA has been at the forefront of energy efficiency for industrial robotics, especially through smart engineering and software-driven optimization.

Some of the key drivers behind these energy savings include cutting-edge hardware design, the integration of AI, advancements in simulation platforms, the use of predictive maintenance systems, and the deployment of battery-powered autonomous mobile robots (AMRs), he adds.

“These innovations not only boost the performance of robots but also play a big role in reaching sustainability goals and lowering overall operational costs,” Volcic says. “Over the past decade, industrial robots have reduced the energy consumption of some specific models by around 60% compared to older-generation robots. This trend will continue into the future as new materials and control methods are used in robotic systems.”

Higher-Efficiency Motors, Drives, and Other Components Driving Energy Efficiency

Choosing more energy-efficient components plays a big role in reducing the overall energy consumption of industrial robots. The right components can reduce energy loss at every step — generation, transmission, and actuation — leading to big gains in overall system efficiency.

Using motors with better efficiency ratings ensures more of the electrical input power is converted into mechanical motion, rather than being lost as heat. Servo motors with high torque density allow for powerful motion with less energy use.

“In general, servo motors and amplifiers continue to get more efficient,” says Justin Garski, Americas OEM segment manager, packaging and converting, for Rockwell Automation. “Since robots are all driven by servos, this will continue to make them more efficient.”

New ArmorKinetix distributed servo drives from Rockwell Automation use amplifier technology based on silicon carbide (SiC) technology, which runs more efficiently than traditional insulated gate bipolar transistors (IGBTs), Garski says. “So, in delta robots, when we use these amplifiers, we see less power loss and less need for heat dissipation,” he adds.

Regenerative drives can capture kinetic energy when the robot slows down or reverses direction and feed it back into the system or grid. This is especially useful for high-speed pick-and-place robots or those lifting and lowering heavy objects.

High-efficiency harmonic or cycloidal drives transfer torque with minimal loss, which is especially useful for articulated arms and joints that require frequent motion under load.

Low-friction components like bearings and joints reduce the energy lost to friction. This not only lowers power consumption but also improves motion smoothness and lifespan. New lubrication systems or solid lubricants also reduce friction while minimizing maintenance and operating temperatures.

Smart actuators provide load-adaptive power use — sensing the load and adjusting power output accordingly, avoiding overconsumption during light tasks. Some actuators can enter a sleep or low-power mode when idle, and then quickly re-engage when motion resumes. Built-in sensors in actuators help optimize control loops, avoiding overcorrection or unnecessary micro-adjustments that waste energy.

“True power demand on an arm is highest when it needs to accelerate fast. If you can reduce or remove the need for these harsh motions, you can save watts,” Garski says. “Oftentimes, this comes into sensor placement and making better decisions in advance, so you aren’t working in a hard reactive mode. If you can do it, you won’t need to sacrifice performance.”

Improved sensors and controllers can reduce waste by ensuring the robot makes only those movements needed. This avoids overshooting, repeating motions, or applying excess force. Advanced controllers use real-time data to optimize paths and joint angles, reducing travel distance, collision avoidance effort, and time — all of which impact energy use. Some control systems actively monitor energy consumption and adjust robot behavior to stay within set limits.

Efficient power supplies and inverters reduce losses during voltage conversion, which is especially helpful for battery-operated or mobile robots. Modern inverters and rectifiers convert AC to DC (or vice versa) with minimal heat loss, improving the overall system efficiency. Some robots dynamically adjust voltage and current to match the task’s requirements, reducing excess draw from the power supply. In mobile robots, efficient battery systems and power management circuitry prevent energy loss during storage, charge, and discharge cycles.

Lightweight components reduce the energy the robot’s motors need to move. Lighter robot arms, frames, and joints require less force to move, especially over repetitive tasks, reducing the size and energy demand of the motors. Components made from aluminum alloys, carbon fiber composites, or high-strength plastics help cut weight without sacrificing durability or load capacity. Less mass leads to quicker acceleration and deceleration with lower energy spikes, increasing both efficiency and precision.

Each of these upgrades might seem small on their own, but combined they can reduce a robot’s total energy use significantly — often by 30% or more in optimized systems.

As KUKA continues to evolve and improve the design and function of its robots, some of those improvements contribute directly to energy efficiency. For example, slimmer and lighter-weight robot designs cut down on energy and material usage, Volcic notes.

“The new Fortec-2 KR 420 R3100-2 robot is 30% lighter than its predecessor,” he says. “This weight reduction means it takes significantly less energy to move the robot at the same speeds and accelerations.”

KUKA robots also save energy through the design and selection of energy-efficient components in the robot controller. “Thanks to improvements in the controller and software algorithms, there’s been a 20% reduction in energy consumption of the controller,” Volcic says.

Standby mode can save up to 95% of a robot system’s energy consumption, Volcic adds, providing the ability to flexibly adjust to production needs. “When in Hibernate state, the robot’s drives and controller are temporarily switched off, putting the robots into a reduced power state,” he says. “This means that during production-free times, the robots use significantly less power.”

User Success Story: Manufacturer Saves 35% Energy with Fleet Upgrade

Upgrading to the latest robot models, one KUKA manufacturing customer was able to save 35% of the energy used in its robot fleet. The move was prompted by the need to reduce operational costs and meet sustainability goals — two initiatives that, it’s worth noting, are not at odds with one another.

“Imagine you’re running a large-scale production environment with 1,000 robots working around the clock, three shifts a day, 24/7, all year long. The cost to power these robots can really add up over time,” Volcic says. “In the U.S., industrial electricity cost averaged about 8 cents per kilowatt-hour in 2024. Depending on the mix of robot motions, idle times, and stoppages, a 210 kg payload robot can be estimated to consume approximately 60,000 kWh over the lifecycle, which can translate to $5,000 per system. When you multiply that by a fleet of 1,000 robots, you’re looking at over $5 million in energy costs over the lifecycle in that example.”

How AI and Other Software Moves the Needle Forward

While hardware improvements cut down baseline energy use, AI and other software-based advances are making great contributions to how and when that energy is used, helping to optimize energy consumption.

KUKA’s iiQoT, for example, is an AI-driven platform that makes it possible to track and evaluate a robot fleet’s energy consumption, providing insights that can help optimize energy efficiency. The software serves as a self-help tool, offering each access to information about a robot fleet and helping with quick troubleshooting.

Software-based intelligent path planning can reduce energy costs by 5-10% for a robot fleet over several years by optimizing motion characteristics, Volcic says, pointing to KUKA’s ECO mode.

Rockwell is making similar advances around path planning. “There are things we are doing around optimized path planning which can smooth out motions and increase throughput,” Garski says. “While this may not always make a robot more efficient, it could reduce the overall demand on a line or factory.”

Simulation tools provide the ability to simulate the energy usage of production systems, making it possible to predict energy consumption when simulating and programming robots. “This allows you to test and optimize for energy efficiency even before installing the system into the field,” Volcic says.

Where AMRs Fit In

For AMRs, fleet management software plays a crucial role in intelligent control, real-time monitoring, and optimization of the traffic flow — all of which can contribute to reduced energy consumption.

AMR technology in itself is an energy saver — playing a significant role in reducing the reliance on propane-powered forklifts, Volcic points out. “AMRs are designed to be a highly energy-efficient way to transport materials in warehouses and manufacturing environments,” he says. “They utilize advanced battery management systems and energy-efficient motion and offer optimized path planning to minimize a fleet’s total energy consumption.”

AMRs are increasingly being adopted in warehouses and manufacturing environments to replace traditional forklifts — driven by the need to improve safety, reduce emissions, and lower operational costs, Volcic says. “AMRs can perform similar tasks to forklifts, such as transporting goods and materials, but with greater efficiency and flexibility,” he notes. “They also eliminate the need for propane fuel, which is both costly and environmentally harmful.”

A Look Ahead in Robot Energy Consumption

Not every robotic application will be a good fit for improving energy consumption, but in the right situation, the benefits can be significant. “Optimizing for energy efficiency might require reducing a robot’s speed and acceleration,” Volcic comments. “But when an application allows for this trade-off of speed for energy efficiency, operators can save on energy costs over the long term. Robots can easily be programmed to dynamically adjust during times of slower production throughput.”

Industry will continue to push forward, finding ways to make further improvements in robotic energy consumption — including developing more energy-efficient hardware, enhancing software for better optimization, and expanding the ability to use renewable energy sources in robot operations.

Volcic points to DC power as the future of energy for industrial robots. Unlike AC, where the electric charge changes direction, DC’s unidirectional flow has considerable advantages in terms of energy consumption, minimal losses, and easier energy storage. Plus, DC makes it simple to feed recovered braking energy back into the grid without a need for converters.

High initial costs for energy-efficient robotic technologies, along with the need for continual innovation, will be key challenges as energy consumption efforts continue to move forward. Integrating new systems with legacy infrastructure is always a challenge as well. “Overcoming these challenges requires a focused effort in research and development, as well as collaboration with industry partners,” Volcic says.