Whenever one thinks about robotics and the automation of manufacturing, artificial intelligence inevitably comes to mind. And even though robots and AI are most certainly connected, the gap between hardware and software is not quite bridged…yet.
Most manufacturing facilities are still powered by automation equipment that emerged during the early days of the Information Age, now referred to as the Third Industrial Revolution – in a somewhat modernized form, of course. But IR 4.0 is already in full swing, and many industries are undergoing rapid transformation as they embrace new tech and reevaluate their approaches to manufacturing efficiency.
So, let’s take a look at the innovative companies already bridging the software-hardware gap before analyzing all the benefits and limitations of new-generation robotics in today’s production lines.
Companies successfully using AI-powered robotics
Even though many companies across different industries are embracing new technologies, these enterprises were the pioneers of new-generation robotics. Today, their operations are already streamlined – to a degree technology development allows it, of course.
- Tesla: as one of the most innovative companies in the automotive industry, Tesla fully leverages all the benefits of manufacturing automation. It relies on huge casting machines that produce seamless (quite literally) underbodies and is improving its humanoid robot Optimus to complete not only repetitive but also dangerous or otherwise undesirable activities – from a human perspective.
- Amazon: as one of the tech leaders, Amazon uses robotics not only in software development but also in streamlining the supply chains for its retail network. Currently, three subsystems deserve the most attention: Sequoia is responsible for inventory management for faster order processing; Proteus, a fully autonomous robot, works side-by-side with human warehousing staff doing most of the heavy-lifting; and Robin is an AI-powered arm that sorts packages.
- DHL: another supply chain leader has an entire series of sorting robots, all equipped with powerful arms. In early 2024, DHL partnered up with Robust AI company to create a series of mobile robots to simplify warehousing operations. Besides, the company already has set up an AI routine to process orders and free employees from repetitive tasks.
- Boeing: the largest avionics company uses AI-powered robotics to reduce labor costs and production times – especially in manufacturing areas that require high precision. Boeing has been experimenting with using automation on its fuselage assemblies for years; not all experiments were successful, but it’s all about trial and effort. Now, the company is heavily invested in polishing up its autonomous system for uncrewed military missions, MQ-28 Ghost Bat.
- Siemens: another company that uses robotics for high-precision manufacturing and is actively investing in AI systems to further improve its operational efficiency, Siemens has achieved impressive results with its Simatic Robot Pick AI system that streamlines warehousing operations.
Applications in other industries
Besides automotive, electronics, and logistics, several other industries are actively exploring new technologies, i.e.,
- Food and beverage industry, with Nestle and Coca-Cola in the lead, relies on automated robotics not only for sorting and packaging but also for ensuring higher sanitary standards – starting from minimizing human contact to automating cleaning and sterilizing procedures.
- Healthcare, especially Pfizer and Novartis, implement AI precision tech in drug manufacturing and also rely on robotics to sterilize the environment. Besides, machine learning algorithms are very useful in testing and developing new drugs because they analyze a larger range of potential development routes, thus shortening the production cycles.
- Energy industry heavily relies on robotics to free people from repetitive or dangerous tasks, especially in the nuclear, gas, and mining sectors. The sustainable energy sector also benefits from machine learning algorithms to predict future needs and find optimal maintenance routines, like using robots to clean solar panels. General Electric, for example, actively uses robotics in many routine operations, from welding and assembly to tech inspection and maintenance.
- Textile is another example of an industry that uses robotics to speed up its production cycles by automating sewing and other routine material operations, and Adidas went as far as to introduce the Speedfactory system for automated 3D printing of custom footwear.
- Construction also uses 3D printing and robotics to reduce waste and optimize labor costs. Geographically, Dubai is the leader in using additive manufacturing in construction and a record-holder in the number of largest buildings made with 3D printers. But automation and robotics have more applications in the construction industry; Fastbrick Robotics, for example, has created an automated bricklaying technology that is already revolutionizing the industry and should eventually lead to a significant decline in construction timeframes.
Today’s limitations & possible solutions
Even though new-generation robotics is actively making its way into various industries, adopting AI-powered automation tech is not without its limitations. The purely technical concerns start with the high cost of initial investment but, sadly, do not end there. Other challenges include:
- Operational complexity because qualified personnel to operate, maintain, and enhance new-generation robotics are still lacking.
- Cybersecurity, which remains a persistent issue with both software and hardware. Growing industry dependence on robotics enhances the risks of cyber-attacks that could potentially disrupt operations and render entire manufacturing lines useless.
- Limited robotics capabilities with non-repetitive tasks, at least for now, make it impossible to fully automate production lines at the moment.
Besides the purely technical challenges of integrating AI robotics into production lines, a series of ethical and moral issues have arisen. First is the growing fear of job displacement from human employees. For low-skilled workers, industry automation means losing their jobs – a process that has already begun. While highly skilled professionals with an understanding of new technologies are lacking, many workers already face steadily diminishing job opportunities.
Eventually, this lack of skilled professionals and over-supply of workers without relevant skills should even out, of course. In the meantime, it is important to create new educational programs with the support from industry leaders. But even when the professional disbalance steadies up a little, many other questions to consider will remain. Right now, the community does not have a clear ethical understanding of how humanized robots and actual humans would work together, so one can only hope we’ll figure out the answer soon enough.
Long-term benefits of automated manufacturing
Despite the challenges of the 4IR transformation, the long-term benefits are undeniable. Robotics and automation are already reducing production costs and speeding up its cycles. In industries that require precision, from avionics to textile, automation also enhances product quality and minimizes human error. In industries associated with hazardous work, automation can literally be a lifesaver, minimizing risks to human safety.
Besides, even though the new automation tech is still in its early days, it’s already clear that AI systems are both scalable and flexible, which is why they can apply to various industries, regardless of their size or exact specifics.
Currently, most AI-powered technologies used in business, no matter if we’re talking about software or a combination of software and hardware, are aimed at boosting operational efficiency – and they have already proved their worth in this.
One more benefit solidifying the future of this technology is its huge potential to make businesses and even entire industries more sustainable.
Since machine learning algorithms operate on hard data and are ‘taught’ to search for optimal ways to reduce costs, waste, and other undesirable side effects of mass production, the new technologies have what it takes to lead us into a cleaner future. In a world where resource preservation gains ever more prominence, this functionality is something we could all benefit from in the long run.
