Bengaluru, Infosys Ltd. on Wednesday said it has developed solutions for Internet of Things (IoT) to benefit from huge data generated by connected devices in the industrial enterprise.
“We have collaborated with GE (General Electric) a digital industrial behemoth, to develop the solutions, which help industrial enterprises improve efficiency and build intelligent linkages between design, production and testing,” the IT bellwether said in a statement from San Francisco, US.
The Industrial Internet Consortium, an international body of industries, governments and academics focused on developing best practices for the Industrial Internet, recently approved two Infosys-led test beds.
“The asset efficiency test bed enables monitoring, analysis and optimisation of infrastructure assets. Its first use focuses on predictive maintenance of an industrial asset like an aircraft landing gear,” the statement said.
Likewise, the industrial digital thread test bed builds more intelligent linkages for manufacturing from design, production and field service.
“By capturing, analysing and relaying real-time sensory and data, the industrial digital thread will generate insights to help field engineers and service teams identify the cause of component failure and provide faster corrections to flaws in design engineering and manufacturing operations,” the statement said.
According to GE’s chief digital officer Bill Ruh, the consortium was set up to help enterprises break down technology barriers and support integration of the physical and digital worlds.
“We see brilliant manufacturing as the next wave of industrial internet innovation, following asset performance management. We are partnering with Infosys to drive efficiency and productivity for the industry,” Ruh said.
The consortium was set up to help organisations break barriers of technology silos and support better integration of the physical and digital worlds.
Infosys chief executive officer Vishal Sikka said: “The IoT is about dissolving complexity and intermediaries that create distance between the point of manufacturing and consumption, between understanding and preventing points of failure in the manufacturing process, in machines or in critical processes.”