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Robot Productivity: How Cobots Compare to Humans

Alex Owen-Hill
by Alex Owen-Hill. Last updated on Jan 21, 2022 12:29 PM
Posted on Jan 21, 2022 11:29 AM. 5 min read time

Productivity is an often debated question in robotics. Is robot productivity really better than the productivity of human workers?

Sometimes, the answer is not as clear-cut as you would first assume.

When you think of manufacturing robots, you probably visualize something like the super-fast delta robots doing pick and place on factory conveyors. Or perhaps you visualize the fast, highly-accurate welding robots in car factories.

In these examples, it can seem obvious that such fast-moving robots would increase the productivity of those tasks.

But, robot productivity is not always so clear-cut. The speed of the robot doesn't necessarily translate into a more productive process overall.

Collaborative robots (or cobots) are a perfect example of this. Cobots usually move more slowly than conventional industrial robots and can even move more slowly than human workers.

Does their slow speed mean that cobots are more productive? Not necessarily…

The definition of robot productivity

Robot productivity means the ratio of input to output in production that a robot cell can achieve. Like manufacturing productivity it is a measure of efficiency. The more a robot cell produces in a particular time period, the more productive it is.

However, the productivity of an individual robot cell is only one aspect of productivity. If you were to fixate on this measure of productivity, you would likely prioritize the speed of the robot. But, just because a robot cell works faster doesn't mean that your entire process will necessarily be more productive.

You also have to take into account how robots affect the overall productivity of your process.

Robots can be a key tool for increasing the productivity of your manufacturing operations. But, they can only do this if you place the robot at a bottleneck task. We have seen many examples of situations where robots have been used to ease pressure on a bottleneck task. This has led to an increase in productivity in the entire operation.

Human vs robot productivity: a complex question

When people see collaborative robots in action for the first time, they sometimes say "These robots move very slowly."

They compare the speed of the robot with the speed of their human workers or with other types of automation. They find it hard to picture how a slower-moving robot could help improve their productivity.

Let's take an example of a particular task: stacking boxes onto one of two wooden pallets.

Worker palletizing boxes manually in a manufacture

How a robot performs the task

Picture a robot performing the palletizing task.

A conveyor feeds the robot cell with boxes. The boxes arrive at irregular intervals as they are packaged by human workers previously in the line.

The robot waits patiently for a box to arrive. Whenever a box arrives, the robot reads its label. If the label is red, the robot immediately places it on the left pallet. If the label is green, the robot places it on the right pallet.

The robot operates constantly without breaks.

How a human performs the task

In this case, a human worker is tasked with palletizing the boxes. As the boxes do not arrive very quickly, this worker also has an unrelated inspection task that they perform at the same time.

The boxes queue up at the end of the conveyor. When enough of the boxes have queued up, the worker rushes over from their inspection task and starts palletizing the boxes.

They have to check the label of each box manually. They put the box on the correct pallet depending on the color of its label. Because the worker is moving quickly, they do not place the boxes as accurately on the pallet as the robot would.

Sometimes, a lot of boxes pile up on the conveyor when the worker hasn't got time to do the palletizing or is on a break.

The result is that palletizing is very inconsistent. The quality of the palletizing suffers and the worker is always rushing to try to catch up with the task even when they try to do the task quickly.

Which of these two systems seems more productive to you?

When do robots increase productivity in a facility?

As you can see in the example above, the speed of operation isn't the only aspect of productivity. Consistency also has a huge impact on how productive the task can be.

Robots increase productivity when they are used for tasks that humans struggle with in the first place.

In the example, palletizing is not a very suitable task for human workers. To palletize boxes efficiently, you need to work continuously at a consistent rate and accuracy. Robots are always consistent but humans are not.

Workers often see this potential themselves. One study found that 77% of people would welcome robotic assistance at work if it meant that the number of manual processes decreased. As humans, we excel at cognitive tasks but highly repetitive manual tasks are just not the best use of our skills.

When you apply a robot to a bottleneck task that is already not a good task for a human, this is often where productivity improvements are most clear.

Employee working beside a robot to accomplish palletizing tasks in a manufacture

Hear from companies that have used robot productivity the right way

You don't need to take our word for it that robots can improve your productivity.

We have a whole collection of case studies of various companies that have used robotics to boost productivity in their facility.

A great example of this in action is the case study of how French manufacturer Alliora increased its productivity with robotic palletizing. You can read about their experiences here.

Do you think robots can be more productive than humans? Tell us in the comments below or join the discussion on LinkedIn, Twitter, Facebook, or the DoF professional robotics community.

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Alex Owen-Hill
Written by Alex Owen-Hill
Alex Owen-Hill is a freelance writer and public speaker who blogs about a large range of topics, including science, presentation skills at, storytelling and (of course) robotics. He completed a PhD in Telerobotics from Universidad Politecnica de Madrid as part of the PURESAFE project, in collaboration with CERN. As a recovering academic, he maintains a firm foot in the robotics world by blogging about industrial robotics.
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