Inside the Mind of a General Electric Company Chief Manufacturing Scientist

Henry Ford once said that "nothing was particularly hard if you divided it into small jobs," a philosophy that gave birth to the assembly line. Today, General Electric (NYSE: GE  ) is applying that same philosophy to the 21st century factory, under an initiative it's calling the "Brilliant Factory."

On a high level, General Electric's vision of the Brilliant Factory combines software, data, analytics, sensors, and the cloud, where designers, suppliers, and production engineers can collaborate over crowdsourcing platforms, design goods, and virtually test production without touching materials or machines. According to General Electric's Christine Furstoss, engineers can then "download the process to intelligent machines on the factory floor when they are ready," and added, "When production starts, they [engineers] will be able to make real-time adjustments based on what's happening to optimize efficiency."

In the following video, 3-D printing specialist Steve Heller asks Stephan Biller, chief manufacturing scientist at General Electric, to give an overview of what it means to be a chief manufacturing scientist, and how it relates to General Electrics' concept of the "Brilliant Factory." Because the concept of the Brilliant Factory is still within its infancy, General Electric investors should watch how the vision slowly comes to life, and see how it could improve the company's competitive manufacturing advantage.

A full transcript follows the video.

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Steve Heller: Hey Fools, Steve Heller here. I'm joined today with Stephan Biller. He is Chief Manufacturing Scientist at General Electric. Thank you so much for being here, Stephan.

Stephan Biller: Hi, Steve.

Heller: We really appreciate your time here today.

Biller: No problem.

Heller: Jumping right in, as a Chief Manufacturing Scientist, what do you do, exactly, for GE?

Biller: I do a couple of things. First of all, I try to help define the advanced manufacturing strategy for General Electric, working with all of our businesses, looking for synergies between different research topics, so that we don't do work just for one of our businesses, but try to leverage that across multiple businesses, thereby reducing the cost of research.

Heller: Interesting. Let's talk about these brilliant factories that you're working to develop. How does your advanced manufacturing strategy fit into the equation of brilliant factories? How are you learning about brilliant factories?

Biller: Brilliant factories is really what we want to do at General Electric, trying to implement the digital thread into our 400 or so factories. The key there is really to connect, from product development to manufacturing engineering, then connecting to the factories, to our supply-chain partners, through our service shops, and close the loop back to engineering.

If we are successful in implementing that digital thread across the company, really what we're going to get is two things. It's going to help us greatly with reducing our time to introduce new products, because we're going to have much faster learning circles between design and manufacturing engineering.

Furthermore, it's going to help us to become much, much more agile for our factories and supply chain, because we'll be able to harvest the real-time information we are getting from the factory floor -- from our machines, controllers, robots, our IT systems, and so forth -- to help optimize our fulfillment throughput and so forth in real time, thereby producing perfect visibility of the operations at General Electric.

Heller: This is part of a larger-scale -- if we zoom out a little bit more -- the Industrial Internet? Does this all fit into that whole vision?

Biller: Yes, I think that's a very good example. The Industrial Internet.  We started that a few years ago, and we now have just about 1,000 people out in San Ramon building varied production hard and software for us on a platform which we call Predix. What those guys are trying to help our customers with is trying to get better performance, better utilization, out of their assets.

For example, a jet engine produces just about a terabyte of data during a single flight. What you want to do is, you want to actually analyze those data, and help them improve the performance of that engine, and determine, is there some maintenance you've got to do, and things like that.

Now turn that to your factories, and think about, "Oh, interesting... I can do the same thing on my factory floor, because I'm running machines there too." Then I connect those machines, and get to the systems level, looking at that systems level in the factory, and optimizing the factory in real time.

Then I can even blow past the four doors of the factory and say, "Now I'm going to include my supply chain," using technologies like RFID and so forth, thereby getting real-time data from my supply chain, and then optimize that.

The farther you go on a systems level, the better you are off, because it allows you to take away inefficiencies in the supply chain and the factory, and so forth.

Heller: It's all about learning about systems intelligence, how everything fits into each other, and leveraging that data to improve outcomes for GE's business, and the customer's business.

Biller: That's exactly right.


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