Bernie Anger is vice president and general manager of GE’s Intelligent Platforms. We spoke with him in August about the company’s new plans for its industrial equipment: APIs. The plan is to build RESTful APIs for GE industrial equipment, and to give developers a cloud-based IDE in which to build controls for automating and monitoring said equipment.
SD Times: What is the existing business inside of GE that you’re hoping to bring to the cloud?
Bernie Anger: When you think about some of the underlying automation we use in industrial platforms, they exist in two forms. When you think about building a control system, there are two types of controls: one [for] dedicated controls and [another for] general-purpose controls.
An aircraft engine or a turbine has a control algorithm, but we also have a set of products that are general market-automation-type platforms. We call them Intelligent Platforms. We create platforms that are enablers for people who are trying to automate things. An OEM that builds a piece of machinery will use our equipment to automate that machinery.
Generally, we have fairly horizontal products. People will use our control platform to automate different machines.
Dedicated controls are for someone who says, “I want to build something to automate a single process,” like the anti-lock braking system in a car. It does one thing and does it well. These are usually developed using traditional development tools. It might use real-time Linux, and you’d use an IDE to build it.
It’s safe to assume as a corollary that the people doing that work have a good understanding of the constraints of real-time systems. Normally, specialized single-purpose controls are designed by people who understand that. When you cross over into the world of general purpose, we end up isolating customers from the majority of the complexity associated with building real-time systems.
Historically, control systems were designed to last 15 years. The average Intel chip lasts seven years.
Why is it now time to tie these control devices into the cloud?
There is now a lot more computing power at the edge nodes; say, a computer that sits next to the oil wellhead or packaging machine. Take that, give it a level of computing power similar to what you see in a desktop device. Rather than having it be a dedicated piece of equipment, it allows you to combine that with an almost unlimited server in the cloud.