Controlled intelligence

July 2019 Industrial (Industry), Integrated Solutions

The research that surrounds artificial intelligence (AI) is plentiful and varied. There are reports from Gartner that highlight how it is critical for an organisation to build foundations for AI and machine learning to ensure it is futureproofed. PwC’s research talks about the human factor and the jobs that these technologies will create or remove as they move into the manufacturing sector. Regardless of these reports, there is one fact that remains true – every industrial organisation should be preparing for the influx of AI and the emergent technologies that walk alongside it.

Henrique Vale
Henrique Vale

“Connected intelligence and 5G are set to profoundly impact how the industrial sector handles manufacturing and quality control processes,” says Henrique Vale, Software, GBC MEA, Nokia. “AI, machine learning, robot process automation (RPA), enhanced connectivity – each of these technologies are evolving and adapting to fit different use cases and industrial requirements. Their abilities and potential are constantly changing to meet market needs and demands.”

The industrial sector has long battled with legacy challenges around quality control. Not only is it an expensive process that’s time consuming and demanding, but it is one that’s prone to error. Human beings can only handle so much repetitive work before they lose focus and accuracy. AI-powered quality control systems, on the other hand, can keep on going 24/7 without getting bored or tired. Their ability to repeat, rinse and repeat, is what gives the industrial sector a much-needed edge in ensuring ongoing quality control.

“This doesn’t mean that the human factor should be removed,” says Vale. “On the contrary, people are critical to oversee, manage and maintain – taking on roles that demand far more than the repetitive quality control tasks of the past. A great example would be the Rubik’s cube – the system takes the cube and follows specific steps to achieve a specific pattern, the system tracks the patterns and alerts the operator if anything is incorrect, they then redress any issues in configuration to ensure that it doesn’t happen again. A perfect mix of man and machine.”

As quality control standards, compliance requirements, and regulatory demands become increasingly complex and challenging, intelligent systems can fundamentally change how the sector reacts to these changes. AI never sleeps, it can learn, it can adapt, and it can be controlled to deliver extraordinarily precise results within extremely precise boundaries. It is programmable, targeted and exact. All factors that play an increasingly important role in the long-term success of a business.

“Quality control is more than just a process, it’s a definitive competitive factor,” says Vale. “If a company’s quality control processes aren’t capable of reducing errors or can’t keep up with the proverbial Jones’s, then they are likely to lose customers to those that can. The same applies to its ability to measure quality and non-quality and thereby ensure that products are aligned with both internal and external compliance controls.”

In 2017, Infosys published a report entitled ‘Manufacturing sector transforming with AI, automation’ that showed how a significant portion of the manufacturing industry had automation down as their first priority. Most (61%) were investing into automation to reduce errors, while 59% wanted to reduce costs and 50% wanted to take people away from repetitive tasks and instead use them for roles that benefited from human interaction.

While the technology is still in the early stages of its potential, it still offers the industry a remarkably strong platform from which to build integrated and efficient quality control solutions. Ultimately, as connectivity improves and systems given increased capacity for connected communication and collaboration, AI and automation will transform process capability and efficiency.

“With AI and 5G, the industrial sector is on the cusp of a transformational change that will not just impact infrastructure but cost, quality control, and growth,” concludes Vale. “The time for deciding if the business should invest into AI and cutting-edge connectivity has passed, now it is about deciding where.”

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