COVENTRY, England, April 29, 2022 /CSRwire/ - An article published in WaterWorld magazine outlines how Rockwell Automation (NYSE: ROK) is among a group of global innovators exploring how the United Kingdom's second-largest water company, Severn Trent, can use artificial intelligence and other advanced technologies to improve the region's environmental well-being. The article notes, "The UK's water industry and its regulators agree that climate change, population growth, urban expansion, increasing water consumption, and changing customer behaviors mean that the industry needs solutions that are flexible and capable of adapting to what future demand will throw at them." As part of the endeavor, Rockwell teams specializing in network and cybersecurity, AI, and machine learning applications are providing guidance as well as counsel and support on other emerging technologies. Rockwell software and hardware will also be part of the solution. Rockwell's Mark Watson, account manager, water and wastewater solutions, says the project will demonstrate "how the adoption of AI and machine learning, in addition to access to both real time and historical data, can deliver an intelligent Connected Enterprise application that can be scalable and deployable within the UK water sector."

Using your noodle to think things through tends to make things go much more smoothly--even if you're just a high-speed food packaging machine wrapping instant noodles. That's an important lesson gained from machine learning technology used by systems integrator Tianjin FengYuLingKong of Tianjin, China. This form of artificial intelligence (AI) allowed the firm's engineers to develop a multivariable inspection model for one of China's largest producers of noodles. Relying on this model, the control system for the packaging lines can now deduce whether sachets containing spices and dried vegetables for flavoring were placed correctly on the precooked noodle blocks before each block is individually wrapped. This ability is an example of how machine learning and other forms of AI are moving beyond applications like robotics and analytics and into control applications.

As data accessibility and analysis capabilities have rapidly advanced in recent years, new digital platforms driven by artificial intelligence (AI) and machine learning (ML) are increasingly finding practical applications in industry. "Data are so readily available now. Several years ago, we didn't have the manipulation capability, the broad platform or cloud capacity to really work with large volumes of data. We've got that now, so that has been huge in making AI more practical," says Paige Morse, industry marketing director for chemicals at Aspen Technology, Inc. (Bedford, Mass.; www.aspentech.com). While AI and ML have been part of the digitalization discussion for many years, these technologies have not seen a great deal of practical application in the chemical process industries (CPI) until relatively recently, says Don Mack, global alliance manager at Siemens Industry, Inc. (Alpharetta, Ga.; www.industry.usa.siemens.com). "In order for AI to work correctly, it needs data. Control systems and historians in chemical plants have a lot of data available, but in many cases, those data have just been sitting dormant, not really being put to good use. However, new digitalization tools enable us to address some use cases for AI that until recently just weren't possible." This convergence of technologies, from smart sensors to high-performance computing and cloud storage, along with advances in data science, deep learning and access to free and open-source software, have enabled the field of industrial AI to move beyond pure research to practical applications with business benefits, says Samvith Rao, chemical and petroleum industry manager at MathWorks (Natick, Mass.; www.mathworks.com).

Editor's note: This viewpoint article was co-written by Blake Moret, chairman and CEO of Rockwell Automation and Carolyn Lee, executive director of The Manufacturing Institute. Barrels of e-ink have been spilled in recent months on the radical realignment of the workplace during COVID-19. The commentators' usually narrow focus on the work-from-home revolution, however, ignores the equally rapid shifts in onsite employment, work practices and technologies that will continue to transform how Americans do their jobs every day. The pandemic necessitated immediate, iterative adjustments to business operations, demanding agility and resilience from companies and workers. But change is intensifying across the U.S. economy, especially in modern manufacturing.

Elisabeth Skoda speaks to three industry leaders to find out more about how robotics and automation help tackle today's challenges. In the autumn of 2020, Japanese engineers presented a 18 metre-tall, 25-tonne heavy humanoid robot that could walk, wave its hand and even take the knee. This giant Gundam robot was inspired by a 1970s anime series that subsequently evolved into a multi-billion-dollar franchise. The technical challenges that had to be overcome to achieve this kind of movement were immense, given the weight and size of the robot. On a smaller scale, robots have been a key part of the packaging industry for decades, and while advances maybe have not been as spectacular as Gundam, they are just as impressive.

From food to cars to complex manufacturing machinery, quality is a top concern of manufacturers. Factors such as safety, efficiency, and reliability affect product quality and ultimately influence customer satisfaction. Sourcing, design, testing, and inspection all play a crucial role in ensuring products meet the bar when it comes to quality. Product inspections at early stages in the production cycle help reduce risks and cost. While inspections can be conducted at any point throughout the production process, the goal is to identify, contain and resolve issues as quickly as possible.

Rockwell Automation, Inc. and Microsoft Corp. announced a five-year partnership expansion to develop integrated, market-ready solutions that help industrial customers improve digital agility through cloud technology. By combining each company's expertise in the industrial and IT markets, respectively, teams can work together more seamlessly, enabling industrial organizations to save on infrastructure costs, speed time-to-value, and increase productivity. Microsoft and Rockwell are working to deliver innovative edge-to-cloud-based solutions that connect information between development, operations and maintenance teams through a singular, trusted data environment. This will allow development teams to digitally prototype, configure and collaborate without investing in costly physical equipment. This unified information environment also enables IT and OT teams to not only securely access and share data models across the organization, but with their ecosystem of partners as well.

At the recent LiveWorx event in Boston, PTC President and CEO Jim Heppelmann laid out the solutions that are available. The most interesting use cases for oil and gas are around connected workers, smart maintenance of refinery, connected refinery and remote asset monitoring with predictive maintenance capability that improves the uptime of the plant and refinery. Heppelmann talks of a convergence between the physical and digital worlds driven by technologies such as additive manufacturing, Internet of Things, machine learning, augmented reality, smart manufacturing and digital twins, which are creating new opportunities for innovation, for disrupting industries and even calling into question how we think about business strategy. "Today, it's no longer sufficient for companies or us as employees to think about some future state, some point B as our destination and then move methodically towards that place," he says. "That type of mindset allows everybody to close their mind, and to build up too much inertia along a point in time.

Artificial intelligence (AI) is all around us. Soon, AI will make decisions and take actions for you. The availability of production data gives the intelligence necessary to make it happen, but you often need to "work that data" to understand it. Fortunately, it's becoming easier to make it useful and actionable. Instead of manually mapping the data throughout the plant, software--such as Rockwell Automation's FactoryTalk Analytics for Applications--is available to automatically discover devices and locations, such as lines and even entire manufacturing plants.

One June day in Virginia last year, an airplane was grounded by an unlikely adversary: a large swarm of bees. The peculiar story made for great newspaper headlines and serves as a reminder that even with the best technology and planning, some things are truly unexpected. But fortunately, most aircraft delays are caused by far more predictable issues than an unwelcome swarm of bees nesting in a turbine. Airlines, like most asset-intensive businesses, are getting increasingly better at predicting failures and anticipating maintenance problems. Rather than keeping planes grounded for costly and annoying last-minute maintenance -- or, worse, exposing passengers to the risk of flying on a faulty aircraft -- airlines are investing in cutting-edge technology that detects potential problems before they arise.