Companies focusing on industrial-level analytics and big data

GE and Microsoft are focusing more on how big data and industrial-level analytics can transform manufacturing as well as the Industrial Internet of Things (IIoT).

05/26/2016


In recent years, GE's focus progressed from being a firm founded in electric lighting, fixtures, and sockets to an Industrial Internet of Things (IIoT) operation that specializes in turbine sensor analytics and other industrial applications. The firm is putting forward its suite of asset performance management (APM) to run on its GE Predix platform, which is software positioned at a platform-as-a-service (PaaS) level to shoulder industrial-scale analytics and operations optimization technologies.

This concept is dependent on firms being able to use cloud-based data analytics to improve the reliability and availability of their assets, minimize total cost of ownership and reduce operational risks. APM is not a new concept, and companies have been forced to integrate a range of disparate solutions to monitor and maintain their industrial equipment. GE, however, is working on a comprehensive solution to support the industrial data generated by these assets.

Figure 1: Whereas IEEE 1588 requires special and complex microcontroller-based hardware even for the most simple of digital I/O devices, EtherCAT DC devices can be implemented without microcontroller support, resulting in lower device and system costs. CoDerek Porter, GM for Predix applications at GE Digital, said, “For example, enterprise asset management (EAM) and enterprise resource planning (ERP) systems can report on how equipment was used and maintained–but cannot analyze the volumes of rich diagnostic data that can be processed with big data techniques to predict and prevent equipment issues."

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.

Microsoft manufacturing machinations

Microsoft is also focusing on the importance of the technologies being put forward by GE here. Microsoft CEO Satya Nadella spoke on this subject in his keynote address at Hannover Messe 2016, the world’s largest industrial technology fair, in Germany. Nadella believes 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, optimize 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.

Nadella also talked about how Jabil is using predictive analytics 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 get better and better. This is the future of industrial operational intelligence in heavy (and some not so heavy) industry.

Adrian Bridgwater is editor at Internet of Business, which is hosting the Internet of Manufacturing Conference November 1-2, 2016, in Chicago. This article originally appeared hereInternet of Business is a CFE Media content partner. Edited by Chris Vavra, CFE Media, cvavra@cfemedia.com.

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