The popularity of cobots is ever increasing. They appear in all types of organizations and continue to ease the physically challenging work often associated with production lines. Because of their small footprint and their flexibility, cobots can be used in many ways. But what do we know of their performance? Do they perform the way we expect them to? Can their performance be measured, and in what areas can we optimize cobot performance? In this blog we will discuss the use of data logging and fact-based performance for cobots, and why it can be useful and advantageous for an organization.
The Internet of Things
The Internet of Things (IoT) is a technology finding its way within the consumer market. Small devices become smarter by collecting data and by using smart algorithms to convert this data to performance evaluations and predictions. The past years, consumer electronics and devices have become more and more advanced. People now receive text messages from their washing machine when the laundry is done, our thermostat knows when we arrive home and turns on the heating beforehand, or your bathroom mirror tells you about the weather and shows you notifications. All these devices display examples of data collection to make life easier and more comfortable.
If these devices can send you push-notifications, then why not have the cobots in your factory send a push-notification to your phone as soon as an error occurs? When looking at data collection for cobots, the industry is way behind, even though data collection and fact-based performance can be of great value. But what do data collection and fact-based performance contain? How can they be advantageous for an organization’s cobot system?
Advantages of fact-based performance
Fact-based performance basically means that through data collection, performance can be measured and traced back to its source. For cobot systems, this has several advantages:
- Through data collection, an organization can review data such as their system’s performance and the average cycle time per product. This way, the organization can optimize its production performance by eliminating frequent errors and issues.
- Smart algorithms can be used to predict when certain parts need maintenance or need to be replaced, to ensure the system’s optimal performance.
- If support is needed, the collected data provides the support team with information regarding the problem and pushes the team towards a certain direction, especially when camera images are involved. With camera images, the support team can analyze with great precision where problems are located, making it easier to solve them and to optimize the system.
The examples above show what fact-based performance entails. Real life situations often show that cobot operators usually have a feeling about where the problem lies, but cannot point it out exactly. By collecting the system’s data, you can show where the problem lies and come up with a targeted approach to solve it. The possibilities are endless!
Why has fact-based performance not gained foothold yet?
Since the possibilities are endless, it is a shame to see that the industry stays behind. We often see that technologies have already been available for years before they enter the market. What is the industry afraid of? The exact reason why data logging and fact-based performance has not gained foothold yet, is unknown. However, there are a few reasons why organizations are not yet ready to take the leap.
The main concern is data protection. The data collected by a cobot system can contain information traceable to a certain product, which can be valuable information for competitors. What if this information gets out in the open through a data leak? Therefore, it is of great importance that when the decision is made to collect data for performance optimization, this data is protected well and security measures are taken into account. This way, you can ensure that fact-based performance will be applied in the best way possible.
Fact-based performance is ready
The collection of data for fact-based performance is not new, but it is relatively unknown in the industry. That is regrettable, because it can optimize cobot systems to ensure that they perform in the best way possible. It helps optimizing cycle times, maintenance and it increases the organization’s satisfaction. Hence, data collection and fact-based performance are of great importance and it is time for the industry to use it. The technology is ready for it, now all we have to do is wait for the industry!