Functional safety and modularity next trends in robots, says NEXCOM

Jenny Shern, General Manager of NexCOBOT, a subsidiary of NEXCOM Group, spoke to IoT Insider about AI being the “next trend”, the growth of mobile robots and functional safety, and offering modularisation in robotics, sharing insights into the pain points and challenges facing the robotics industry.

Trends in robots

Observing trends in robots – notably, the integration of AI, functional safety, and growth in mobile, moving robots – NexCOBOT has responded accordingly in creating different solutions or design packages that enable their customers to build robots easily.

“In terms of market demand, industrial robots are still the big focus,” Shern explained. “We notice that the demand for human collaborative robots is increasing while the whole industry is facing labour shortages. And when there are humans around, functional safety is crucial. We see collaborative robots as a trend booming, to add collaborative robots on top of mobile robots.” 

What this entails, Shern explained, is the user of the robot choosing the application – such as choosing a collaborative robot – as well as selecting the base unit, deciding if they want it to have wheels as a functionality so the robot can move around. “Mobility is also a very important factor,” she stressed.

Pick and place robots remain popular, but mobile robots suit more complex environments where they have to navigate around obstacles or enter and exit elevators. 

NexCOBOT are striving to make their solutions modularised, in which they offer their customers a robot controller solution which can be customised according to the type of processing power they need, whether they need an AI accelerator, functional safety, and so on. 

“Every type of robot will require some kind of customisation depending on the space, depending on the application,” said Shern.

Making IoT implementation successful 

Because there are usually several data silos within a factory, along with different controls, brands and communication protocols, retrieving data to glean valuable insights can be challenging.

“To help our customers resolve this issue or eliminate these different data silos, we provide what we call IoT connectivity for system integration,” Shern said. “We have a range of different gateways that we offer to our customers … so they can communicate with different protocols out in the field.” 

Subsequently, the support of the different protocols means the users can collect data from the different PLCs, controllers and other data sources, to bring it to the on-premise Edge.

“This is where the data integration comes together,” Shern added. “It’s a local on-premise data centre that aggregates and consolidates all this data and performs AI analytics. 

“Many users would ask for visualisation of the data. This is where Edge GPT or ChatGPT would come in. A user would ask the local data centre for information regarding their production line … and through the AI Edge GPT, the data centre would be able to reply within seconds.”

AI in manufacturing

For the step in which the data is analysed using AI integration, NEXCOM has developed its own solution, the Situation Room AI Assistant solution. It sees “data integrated into the AI server so that it can create different data models and generate the report through a live dashboard,” Shern explained. “You can ask this AI situation room questions and it will answer in real time.”

Data is becoming key for manufacturing environments who have recognised the value of using data to understand, for example, bottlenecks in the production line that can be addressed to create efficiency, or for predictive maintenance purposes. Factories that experience downtime for any reason result in loss of revenue.

“In a production line, for example, a user is looking at the yield rate trend for every month,” she detailed. “GPT will then show you the yield rate per production line. You can see a drop and ask, what’s wrong with this issue, what’s creating this issue? You can in real time find out the real problem … in the past you couldn’t do that in seconds.” 

The AI model was trained on NEXCOM’s own data. As Shern put it, “The beauty of using it in our own production line is that we have a lot of data sets within NEXCOM Group … we can perform training directly off of these data sets.” 

Open communications

One final topic of conversation centred on whether Shern saw the possibility of communication protocols opening up, to enable greater interoperability between equipment, particularly for factories who are operating lots of different equipment from different companies that have to rely on solutions like NexCOBOT’s gateways to collect data for analysis.

“For proprietary technologies, they’ll never open up … But I do see a trend towards open standards,” she said. “We’ve already adopted open standards in our systems and solutions.” 

With modularised solutions, functional safety, mobile robotics, integrating AI and the possibility of open standards on the horizon, there’s lots in store for the manufacturing sector.

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