ABB and IBM today announced a strategic collaboration that brings together ABB’s established digital offering, ABB Ability, with IBM Watson Internet of Things cognitive capabilities to unlock new value for customers in utilities, industry and transport and infrastructure.
Users will benefit from ABB’s knowledge and extensive portfolio of digital solutions combined with IBM’s expertise in artificial intelligence and machine learning as well as different industry verticals. The first two joint industry solutions powered by ABB Ability and Watson are designed to bring real-time cognitive insights to the factory floor and smart grids.
“This powerful combination marks truly the next level of industrial technology, moving beyond current connected systems that simply gather data, to industrial operations and machines that use data to sense, analyse, optimise and take actions that drive greater uptime, speed and yield for industrial customers,” said ABB CEO Ulrich Spiesshofer.
“With an installed base of 70 million connected devices, 70,000 digital control systems and 6000 enterprise software solutions, ABB is a trusted leader in the industrial space, and has a four decade long history of creating digital solutions for customers. IBM is a leader in artificial intelligence and cognitive computing. Together, IBM and ABB will create powerful solutions for customers to benefit from the Fourth Industrial Revolution.”
New suite of solutions
The new suite of breakthrough solutions developed by ABB and IBM will help companies address in a completely new way some of their biggest industrial challenges, such as improving quality control, reducing downtime and increasing speed and yield of industrial processes. These solutions will move beyond current connected systems that simply gather data, to cognitive industrial machines that use data to understand, sense, reason and take actions supporting industrial workers to help eliminate inefficient processes and redundant tasks.
“This important collaboration with ABB will take Watson even deeper into industrial applications — from manufacturing, to utilities, to transportation and more,” said Ginni Rometty, IBM Chairman, president and CEO. “The data generated from industrial companies' products, facilities and systems holds the promise of exponential advances in innovation, efficiency and safety.
"Only with Watson's broad cognitive capabilities and our platform's unique support for industries can this vast new resource be turned into value, with trust. We are eager to work in partnership with ABB on this new industrial era.”
Bringing cognitive insights to the factory floor
As an example, ABB and IBM will leverage Watson’s artificial intelligence to help find defects via real-time production images that are captured through an ABB system, and then analysed using IBM Watson IoT for Manufacturing. Previously, these inspections were done manually, which was often a slow and error-prone process. By bringing the power of Watson's real time cognitive insights directly to the shop floor in combination with ABB’s industrial automation technology, companies will be better equipped to increase the volume flowing through their production lines while improving accuracy and consistency.
As parts flow through the manufacturing process, the solution will alert the manufacturer to critical faults — not visible to the human eye — in the quality of assembly. This enables fast intervention from quality control experts. Easier identification of defects impacts all goods on the production line, and helps improve a company’s competitiveness while helping avoid costly recalls and reputational damage.
In another example, ABB and IBM will apply Watson’s capabilities to predict supply patterns in electricity generation and demand from historical and weather data, to help utilities optimise the operation and maintenance of today’s smart grids, which are facing the increased complexity created by the new balance of conventional as well as renewable power sources.
Forecasts of temperature, sunshine and wind speed will be used to predict consumption demand, which will help utilities determine optimal load management as well as real-time pricing.