GE is embarking on a big push with GE Predix, its software platform which provides industrial-level analytics on connected machinery on the factory floor or out in the field.
Like a lot of firms, GE has modernised itself. The firm that we used to know as General Electric now prefers the nattier modern shortening (think CA for Computer Associates, LG for Lucky Goldstar, ASDA for Associated Dairies and so on).
The company’s focus has also progressed — what started out as a firm founded in electric lighting, fixtures and sockets has become an Industrial Internet of Things (IIoT) operation with a specialism in turbine sensor analytics and other industrial applications.
GE is already having a busy month in the news; GE Digital has signed new strategic IIoT partnerships with Oracle and Deutsche Telekom to develop complimentary solutions.
GE Predix predicts…
The firm also now puts forward its suite of Asset Performance Management (APM) to run on its GE Predix platform — essentially a bunch of software positioned at Platform-as-a-Service (PaaS) level to shoulder industrial-scale analytics and operations optimisation technologies.
The promise here hinges around firms being able to use cloud-based data analytics to improve the reliability and availability of their assets, minimise total cost of ownership and reduce operational risks — and it works for both GE and non-GE assets, as you might hope.
GE admits that APM is not a new concept and companies have for some time now been forced to integrate a range of disparate solutions to monitor and maintain their industrial equipment. But, it claims, no comprehensive solution has existed to support the industrial data generated by these assets.
“For example, Enterprise Asset Management (EAM) and Enterprise Resource Planning (ERP) systems can report on how equipment was used and maintained – but cannot analyse the volumes of rich diagnostic data that can be processed with big data techniques to predict and prevent equipment issues,” asserts Derek Porter, GM for Predix applications at GE Digital.
GE Predix also seeks to provide developers with security, real-time data management and cloud infrastructure management to develop and maintain applications. There is a machine and equipment tier here that provides a unified view of an asset, virtually anytime, anywhere, to understand equipment performance at many levels. Reliability management and maintenance optimisation are also a key features of GE Predix.
Related: How GE is building a services company through cloud and IIoT
Microsoft manufacturing machinations
Microsoft, it appears, is in broad agreement with the importance of the technologies being put forward by GE here. Microsoft CEO Satya Nadella spoke on this subject last week in his keynote address at Hannover Messe 2016, the world’s largest industrial technology fair, in Germany. Nadella thinks that a digital transformation is remaking companies and their factories, bringing the intersection of manufacturing and technology even closer.
“Enabling that transformation are systems of intelligence that help companies gain insight and take action from Big Data, optimise their operations and change the very nature of the business models around their industrial products,” Nadella said.
For example, Siemens Healthcare, together with Microsoft, built a healthcare cloud platform for doctors, radiologists and patients so they can collaborate on connected information, such as diagnostic data from imaging devices, and transform how health care is delivered.
You want more examples? No problem… Liebherr is using intelligence to predict a potential breakdown of commercial refrigerators and freezers, with service tickets generated automatically so the problem is fixed immediately, crucial for maintaining proper storage.
At Jabil, predictive analytics are being used on assembly floor equipment to discover errors and failures before they happen. “So that means even if there is a mistake made in the first step” of production, “They’re able to connect back to the cloud, use machine learning, detect that mistake and correct it before it goes all the way to the end of the production line,” Nadella said.
In the near future…
These software systems need to be continuous learning systems so that means every operation and every run gets better and better. This is the future of industrial operational intelligence in heavy (and some not so heavy) industry.
It’s time to clock-on, in a more automated way.