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Efficient robot-based manufacturing

27 August 2013

It takes more than variable speed drives and efficient motors to make a manufacturing system energy efficient. Robot mechanics and the materials chosen for its design will also have an effect on the energy efficiency of a system in motion.

When designing plant it is important to consider energy-saving opportunities, starting with the robotic components, continuing with planning and simulation and ending with the energy model of the overall system, says Kuka Roboter GmbH, a member of the German Manufacturing Federation’s (VDMA) blue competence initiative, which aims to find sustainable solutions for industry and manufacturing.

Depending on their payload class, industrial robots consume, on average, between 1 and 3 kw/hr. By carefully selecting the materials used in its robots KUKA has reduced the tare weight of its robot mechanics by more than 12%.

Gears with low friction losses and energy efficient motors are used to ensure that operating efficiency remains high. In addition, an energy-saving drive system, which automatically optimises the energy consumption profile of the AC drive and motor combination, now ensures that the robots operate at peak efficiency during all motion sequences. Depending on the application, these robots consume up to 30% less energy than their predecessors when in motion thanks to optimised trajectory planning and new, consumption-optimised run commands.

Robotic systems only add value to work for about 30% of the time. It is, therefore, important to be aware of waiting times during manufacturing and no-load consumption when the system is idle. By increasing the number of times in succession that braking is permissible, KUKA has reduced the total applied braking time, reducing energy consumption during brief standstill periods by up to 80%. When the manufacturing system is shut down the master PLC can switch the robot controller to energy-saving mode to minimise energy consumption. In the event of unexpected shutdowns, maintenance operators can manually activate this energy-saving mode for entire sections of the plant.

Energy optimisation

Not only are robots not adding value when they are idle, but they are also consuming energy. It is possible to boost the energy efficiency of a plant by designing the control system to minimise robot wait times. For example, to maximise the resource efficiency of a car body assembly line, the controls must prevent superfluous robot motion sequences and wait times using anticipatory sequencing algorithms.

Clearly structured, highly modular robot control programs with a flexible interface to PLCs can help. Often, executing the enabling and interlocking signals generated by a master PLC can lead to long wait times for robots, especially in systems with high robot density and asynchronous sequencing. If interlocking and enabling signals related to shared workspaces are processed within an intelligent, networked robot group, these energy consuming wait times can be reduced. Synchronising robotic motion sequences and manufacturing processes within a cooperating robot group can eliminate wait times, enabling the plant to operate at peak energy efficiency.

New material flow concepts can also reduce the amount of energy consumed at a plant. For example, when transferring a car body to the next cell, robots must wait at least ten seconds. Replacing the stop and go transport concept by a continuous material flow process will enable the robots to operate continuously throughout the entire cycle.

Energy efficient planning and simulation
Energy efficiency parameters must be taken into consideration early in the planning stage of a project. The energy consumed by the robotic application must be predicted as precisely as possible, preferably while doing the off-line programming.

To this end, KUKA will soon be able to offer simulation models that precisely simulate the motions and sequences in a robotic system and precisely calculate the energy consumed along the trajectory.

If every component is simulated, it can be modeled in the virtual world based on its total consumption profile. Designers will then be able to run various manufacturing scenarios and define manufacturing sequences to optimise consumption.

A detailed energy model of the entire system is also necessary. This should take into consideration the components used for manufacturing, the processes, logistics, and the energy consumed by the building.

Energy profiles at all levels of the factory provide the necessary transparency. Concepts to integrate energy as a variable resource will revolutionize manufacturing planning systems. Energy-efficient manufacturing plants that are flexible about peak consumption periods are the way of the future.



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