Something to Think About – Artificial Intelligence in Manufacturing
Jeff Immelt, previous CEO of manufacturing giant GE recently stated about Artificial Intelligence, “Companies need to become digital to survive – We must turn information into insights and insights into outcomes.”
That implies we have something to think about:
Manufacturing is changing, which isn’t a bad thing. But technology will become difficult to keep up with if we don’t keep an open mind. Though we embrace new technology in some parts of our shop, one trend in particular should be on our radar:
It will dramatically change our industry. However, coming to terms with that fact can be intimidating. This is often due to a lack of awareness, or a fundamental misunderstanding of AI.
Simply put, artificial intelligence is the reasoning and processing capabilities of certain machines. In essence, these machines are built to mimic the cognitive process of humans through the implementation of AI processes. But they’re not here to replace us.
In fact, artificial intelligence is rooted in the idea of creating machines that are as efficient as possible for organizations like us. It’s created as a means to assist us in learning and problem solving, while in turn learning and solving problems. It grows just as we do. And at its best, artificial intelligence allows us and our businesses to achieve our full potential.
Just take a look at what some businesses have already done.
Unscheduled downtime is a term used to describe a time period in which a company is not producing. This is different than routine maintenance because there isn’t any planning involved. Most disruptions are very costly, and affect delivery schedules. P&G, however, may not have to put too much concern into it anymore.
P&G has decreased their unscheduled manufacturing downtime for personal care products (diapers, toilet paper, etc.) by 20 percent through the implementation of software primarily rooted in artificial intelligence and intrinsically driven to facilitate efficiency. The programs enhance analytics, as well as the ability to optimally connect all phases of the business units.
A global leader in many facets of manufacturing, Siemens actively searches for ways to maintain their standing in the industry. In fact, for the past 30 years, the company has been researching ways to do it. And the answer they’ve found? Conveniently, artificial intelligence.
Specifically, Mind Sphere, their custom AI system. It has the ability to not only analyze industrial facilities, but also to be applied widespread throughout the majority of Siemens’ departments.
According to their website, and in the context of Siemens’ energy research, Mind Sphere also “significantly reduces the emission of toxic nitrogen oxides without affecting the performance of the turbine or shortening its service life.”
At Hitachi, the manufacturers’ primary objective is to instill knowledge. So much so, that their use of artificial intelligence involves the notion of instilling knowledge in more than just their people. Specifically, this is seen in their understanding and application of deep learning. And their robots.
Deep learning is the implementation of neural networks to both simple and complex machines. As Hitachi grows in their understanding of it, their goal of allowing machines to do the same does too. Just take a look at their Swing Robot.
Designed with working neural networks, it first analyzed an immense amount of data. From there, it took about 5 minutes, without human intelligence, to figure out how to swing effectively. It sounds like its right out of a movie, but it’s true. AI is beginning to teach itself, which will be beneficial to us all.
