{"id":577885,"date":"2024-02-15T08:25:09","date_gmt":"2024-02-15T13:25:09","guid":{"rendered":"https:\/\/www.therobotreport.com\/?p=577885"},"modified":"2024-02-15T08:34:27","modified_gmt":"2024-02-15T13:34:27","slug":"top-5-robotics-trends-for-2024-according-to-the-ifr","status":"publish","type":"post","link":"https:\/\/www.therobotreport.com\/top-5-robotics-trends-for-2024-according-to-the-ifr\/","title":{"rendered":"Top 5 robotics trends for 2024, according to the IFR"},"content":{"rendered":"
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Source: IFR<\/p><\/div>\n

The International Federation of Robotics, or IFR, today listed its picks for the top five global robotics trends of this year. The Frankfurt, Germany-based organization attributed growing demand for automation to technological innovations.<\/p>\n

The IFR noted that the stock of operational robots around the world attained a new record<\/a> of about 3.9 million units in 2022. The average robot density, or number of robots per 10,000 human workers, rose to 151. In its latest release<\/a>, the federation<\/a> cited some different trends than it had for 2022<\/a> and 2023<\/a>.<\/p>\n

1. AI and machine learning to aid more robots<\/h2>\n

The trend of using artificial intelligence<\/a> in robotics and automation keeps growing, according to the IFR.<\/p>\n

In particular, the emergence of generative AI<\/a> opens new possibilities, it said. This subset of AI is specialized to create something new from things it has learned via training, and generative AI has been popularized by tools such as ChatGPT, explained the IFR.<\/p>\n

Robot manufacturers have started to develop generative AI-driven interfaces that allow users to program systems more intuitively by using natural language instead of code. Workers will no longer need specialized programming skills to select and adjust the robot\u00b4s actions, predict experts.<\/p>\n

Another example of the combination of technologies<\/a> is the use of predictive AI to analyze robot performance data and identify the future state of equipment, said the IFR. Predictive maintenance can save manufacturers machine downtime costs.<\/p>\n

In the automotive parts industry, each hour of unplanned downtime is estimated to cost $1.3 million (U.S.), reported<\/a> the Information Technology & Innovation Foundation. This indicates the cost-saving potential of predictive maintenance.<\/p>\n

Machine learning<\/a> algorithms can also analyze data from multiple robots performing the same process for optimization. In general, the more data a machine learning algorithm is given, the better it performs, said the IFR.<\/p>\n

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\"SITELearn from Agility Robotics, Amazon, Disney, Teradyne and many more.<\/a><\/p>\r\n\r\n\r\n

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2. Cobots expand to new applications, says IFR<\/h2>\n

Human-robot collaboration continues to be a major trend in robotics, stated the IFR. Rapid advances in sensors, vision technologies, and smart grippers allow robots to respond to changes in their environment in real time and thus work safely alongside human workers.<\/p>\n

Collaborative robot<\/a> applications offer a new tool for human workers, relieving and supporting them. Cobots<\/a> can assist with tasks that require heavy lifting, repetitive motion, or work in dangerous environments.<\/p>\n

The range of collaborative applications offered by robot manufacturers continues to expand. A recent market development is the increase of cobot welding<\/a> applications, driven by a shortage of skilled welders.<\/p>\n

“This demand shows that automation is not causing a labor shortage but rather offers a means to solve it,” said the IFR. “Collaborative robots will therefore complement \u2013 not replace \u2013 investments in traditional industrial robots, which operate at much faster speeds and will therefore remain important for improving productivity in response to tight product margins.”<\/p>\n

In addition, the IFR noted that new competitors are entering the market with a specific focus on collaborative robots. The combination of cobot arms and autonomous mobile robots (AMRs<\/a>) in mobile manipulators offers new use cases that could expand the demand for collaborative robots, it said.<\/p>\n