The data emanating from manufacturing processes is a potential goldmine of opportunities to optimize production, boost quality and cut maintenance overheads, according to a new whitepaper from Fujitsu. Carlos Cordero, CTO at Fujitsu Spain takes a look.
The novelty and even shock of artificial intelligence (AI) are beginning to subside. If 2018 was the year the general public sat up and took notice of AI and its possible impacts on society, in 2019 we will move decisively away from “hey, look at me” AI applications towards a world in which it just happens to be a part of the solution. The results will still be amazing, but we won’t be so blinded by the novelty.
In manufacturing, in particular, the lights have turned to green for AI. This is now one of the places where AI deployment is going to happen faster, deeper and with more immediate benefits than elsewhere, due to a powerful combination of AI and smart analytics having a transformative effect.
Fujitsu has explored this in detail in a new whitepaper produced in association with research firm PAC, which argues that AI has the potential to bring many advantages to enterprise applications, including manufacturing.
What AI can bring to the business application
The whitepaper looks at the interaction between AI and data capture and data analytics, which together make it possible to gain deeper and more comprehensive insights into the manufacturing process than ever before. Through the use of data and AI, we can see inside the machines, gaining a holistic overview of a production process – and even predict when and how things might go wrong – allowing intervention and changing future outcomes.
The ability to collect and analyze data from production processes, in real time, is the starting point for any transformation on the factory floor. The more accurate and comprehensive, the greater the benefit of applying AI – and today, we are at the point where we can identify and eliminate potential bottlenecks even before they arise.
Together, AI and smart analytics are enabling three key fundaments of smart manufacturing: the optimization of production in real time, the realization of enormous improvements in quality of finished goods, and the introduction of combined predictive and prescriptive maintenance. All three have a dramatic effect on the bottom line and together they’re a compelling combination which delivers a huge competitive advantage.
Optimization is all about reducing downtime for production lines.
By reducing bottlenecks, which lead to forced delays, it’s possible to greatly increase the number of units produced in a single production run, therefore enabling a manufacturer to benefit from advantages of scale.
Realization of enormous improvements in quality of finished goods
Hand-in-hand with that is the issue of quality. Quite simply, the smoother your production process, the lower the chances of defects creeping in. If you want to raise the bar on quality, you need to use AI to help iron out the bottlenecks that can cause production lines to stop – as well as using machine learning and AI to verify the quality of finished goods.
The introduction of combined predictive and prescriptive maintenance
Behind the scenes, it’s not only about making sure that machinery is in good condition but also about reducing the overheads associated with keeping an expensive inventory of spare parts on hand just in case something goes wrong. The use of AI can help predict which parts are likely to fail – in good time, allowing prescriptive maintenance to take place.
The white paper outlines how AI is transforming industries including manufacturing – where the battleground today has moved far, far beyond predictive maintenance.
One last word
Even when the lights are green, successful transformation requires not only the buy-in from senior management but also for them to be deeply engaged in the process. For any senior executive who is still not convinced, our report should be a game changer.