The introduction of generative artificial intelligence in virtually every link of the supply chains of many industrial sectors, the replacement of synthetic fibres in the textile industry and its resulting impact on the reduction of microplastics, breakthroughs in automotive sensor technology and the push for the Internet of Things (IoT) and the potential of photovoltaic energy owing to the industrial scaling of new perovskite and silicon solar cells are some of the industrial trends which will shape 2024 says the Eurecat technology centre.
Research into new sensors “is continuing to yield results and sensors will emerge to measure new industrial parameters of interest while the capabilities of current sensors will be enhanced in lockstep,” says Ricard Jiménez, the scientific director of Eurecat’s Industrial Area.
The most buoyant sectors for progress in sensor technology will be the integration of the Internet of Things (IoT) and the automotive industry coupled with applications for environmental and sustainability monitoring.
As for perovskite/silicon tandem solar cells, they have demonstrated “stunning performance in the laboratory and last year their viability for industrialisation was confirmed,” points out Ricard Jiménez. “This means that in 2024 we will see the industrial scaling of this new technology to enable photovoltaic energy to take a fresh global qualitative and quantitative leap forward.”
Likewise, “the challenge of sustainability in the textile industry will be met by numerous attempts to replace synthetic fibres” against a backdrop in which “one of the most promising initiatives is developing cellulose fibres of forest origin.”
Alongside furnishing a sustainable material for the textile industry, this process will make a “significant contribution to the global reduction of microplastics and generate a new industry of materials manufacturers in synergy with forest management.”
Generative AI will gain ground in manufacturing
Generative AI will also gain ground in manufacturing and be part “of practically every link in the supply chains of many sectors with the primary goal of optimising them to enhance efficiency, increase quality, cut costs, speed up processes and reduce risks,” argues Ricard Jiménez.
He thinks that “this trend will embrace all sectors involving product design where generative design software will be able to dump large quantities of design proposals in compliance with the user’s pre-set requirements.”
“Machine learning algorithms will also be used in quality control and predictive maintenance and will be increasingly better trained to spot any data patterns which predict either a machine breakdown or a product defect.”
Likewise, he believes that “the mix of generative AI models and digital twins will also take production planning and logistics to the next level as it will be possible to simulate a large number of scenarios and forecast supply and demand and the availability of raw materials and all kinds of resources.”
Furthermore, “generative AI will also be a facilitator for expanding automation of industrial processes and in particular robotics, which will make huge strides and where one of the most disruptive applications will be in human-robot interaction.” This will prompt the emergence of the first robots in healthcare and customer service, as is the case of a prototype of a care robot for mental health applications which Eurecat is developing.
