Victoria Lietha ABB Technology Ventures Zurich, Switzerland, firstname.lastname@example.org
It has long been a part of ABB’s philosophy to use an “outside-in” approach, where external ideas are brought into the company to complement ABB’s own innovation activities. By engaging with external partners, such as universities, research institutes, or startups, ABB can identify and capitalize on breakthrough technologies or new business models that help the company find new offerings for its customers.
AI – often dubbed “the next technology frontier” or “the Intelligence Revolution” – is one area where collaboration can make all the difference. AI has the potential to enhance human capabilities in a wide range of industries. While AI is still a growing field, in terms of venture capital (VC) investments it is one of the best-funded sectors. Large companies in almost every industry are trying to integrate AI capabilities into their offerings. According to the AI Index Report 2019, globally, investments in AI startups have increased at an average annual growth rate of over 48 percent since 2010 (2018: $40.4 billion) .
In this context, in 2019, ABB ran the ABB Industrial AI Accelerator program, with the aim of fostering the development and utilization of AI to drive the next level of the industrial revolution  →01.
The program sought out startups that have new, promising ideas on how to use AI components to provide solutions – or startups that can develop enabling technologies to deploy such solutions in an industrial setting. In joining the ABB Industrial AI Accelerator program, startups received coaching and technical support as well as the opportunity to win customers and grow and commercialize their solution on a global stage. The startups selected for the program also competed for the title of overall winner.
How the Industrial AI Accelerator winner was selected
In all, seven promising, mostly early-stage, startups were selected to join the Industrial AI Accelerator program to explore industrial applications of their concepts and speed up their development. The seven were chosen from over 100 startups across 20 countries in a two-month review by ABB, supported by delphai (AtomLeap GmbH). Delphai is a a self-service market intelligence platform that uses AI to give insights on global innovation trends, market developments, and companies.
The selected startups joined a four-month program in which they were paired with an appropriate ABB Division or function so they could benefit from ABB’s deep domain knowledge and thus accelerate their growth.
At the end of the four months, the seven startups presented their solutions to around 70 attendees at a “Demo Day.” Each startup had to pitch their solution to a six-member jury – consisting of business and technology experts as well as investors – and face critical questions. The jury selected Greenlytics as the winner.
Accelerating into the future
While the collaboration projects were spread across different industrial applications, they all had in common a clearly defined use case for which the startup and ABB together developed a specific solution and which benefited both parties.
To drive further collaboration with ABB and help the startups to accelerate and expand into a global market, SynerLeap, ABB’s innovation growth hub, handed over free memberships to three of the startups – Greenlytics, Vathos Robotics and OneWatt – for the next six months . The other finalists – Cobrainer, Dutch Analytics, Intelecy and 8power – will continue in their drive to develop promising new solutions.
Accelerating startups through such a program has a strategic motivation, as explains Kurt Kaltenegger, Head of ABB Technology Ventures (ATV): “ABB’s Industrial AI Accelerator program was just one way ABB partners with startups. With our global startup innovation hub SynerLeap, for example, we are matching startups to our business organization in order to collaborate and perform proof-of-concept projects together. This approach speeds up the development of differentiating innovations that can win new customers or address pain points of existing customers. We are also providing financial support via strategic venture capital to accelerate and enable the further growth of best-in-class startups.”
 The Stanford Institute for Human-Centered Artificial Intelligence, “The AI Index Report.” Available: https://hai.stanford.edu/sites/default/files/ai_index_2019_report.pdf Accessed April 7, 2020.
 www.synerleap.com. Accessed April 7, 2020.
A WIDE SPREAD OF AI APPLICATIONS
The activities of the seven startups that participated in the accelerator program demonstrate the diversity of possible applications of AI.
Greenlytics, a Swedish startup, develops tools for AI-based forecasting of wind and solar energy generation and consumption, as well as decision support for power trading and plant optimization. As part of the collaboration project between ABB and Greenlytics, their solution has already been deployed for ABB’s “Mission to Zero” project ABB Busch-Jaeger’s plant in Lüdenscheid, Germany.
As part of the program, the Greenlytics product, SolarMind, was integrated into ABB’s OPTIMAX energy management solution to forecast the power generated by photovoltaic plants. The Greenlytics AI system is continuously updated through inputs such as historical data, location-based plant data and weather data.
“We have seen strong synergies between the Greenlytics product offering and ABB OPTIMAX from the start,” explains ABB’s Julia Marie Leichthammer, who worked closely with Greenlytics. “The significantly more accurate power forecasts by Greenlytics enhance the flexibility of ABB’s predictive energy management system OPTIMAX®, resulting in improved operation and trading coordination, and further reduced cost, of our customer’s distributed generators, consumers and storage.”
The advantages for the startup of ABB collaboration are articulated by Sebastian Haglund El Gaidi, founder of Greenlytics: “We learn from ABB and use the company’s global presence to deliver our services.”
The exercise also provided Greenlytics with the opportunity to expand their vision: “Collaborating with ABB helps us to develop our vision of tomorrows increasingly renewable, distributed and smarter grid. We already learned a lot about the market and customer needs and that is important for a startup.”
Presenting a very different face of AI was Cobrainer. This Munich-based startup applies machine learning to enable intelligent employee mobility for large and medium-sized organizations by offering employees automatic expertise profiling and intelligent job, project and course matching.
Together with the ABB HR team, Cobrainer built and implemented the ABB Career app, based on Cobrainer’s Skill Career technology, which helps students to create a skill profile to receive relevant job recommendations from ABB.
Dutch Analytics of The Hague, in the Netherlands, offers a hosting and management platform called UbiOps that enables the hosting and management of data science applications. Dutch Analytics worked together with ABB’s Marine & Ports business on cooling systems in medium-voltage drives on vessels with diesel-electric propulsion. Ensuring the right level of cooling fluid provision during ship operation is critical. By using data from the ABB Ability™ Marine Remote Diagnostic System installed on ships, the team developed and deployed a model that predicts liquid evaporation rates and advises when the next maintenance should be. Customers in rail, marine and manufacturing industries are already benefiting from this AI technology by predicting breakdowns and increasing asset uptime.
Jorick Naber, COO of Dutch Analytics, says, “collaborating with ABB drives enormous value for Dutch Analytics. We believe the joint project will bring further technology enhancement and help us introduce our UbiOps platform to different industries.”
Intelecy, from Oslo in Norway, offers software to analyze production data from the manufacturing and processing industries and utilizes machine learning to prevent breakdowns, predict failures and improve production processes. Intelecy used production data from the ABB Ability™ Extended Automation System 800xA to provide automatic processing, structuring, labeling and cleaning of raw data from a specific industrial process. The processed data was then used to select, train and deploy industrial machine-learning algorithms and provide new insights.
OneWatt, from Arnhem in The Netherlands, has designed a noninvasive, noncontact predictive motor health maintenance system based on an acoustic method. Data is gathered through their embedded acoustic recognition sensors (EARSs), which literally listen to motors to prevent unnecessary repairs or unplanned downtime. The company worked with ABB to integrate their AI into ABB’s Smart Sensors to give insights into asset operation and developing faults. The partnership has also enabled OneWatt to detect even more faults plaguing industries, such as cavitation, electrical imbalance and motor eccentricity.
Vathos Robotics, from Düsseldorf, Germany, deploys computer vision and machine learning for applications in robotics and factory automation. The modular software architecture of their computer vision technology enabled easy integration into ABB’s robotics applications. Local Web APIs (client-side application programming interfaces) allow the computer power needed to train the AI models to reside in the cloud. For more mission-critical applications, customers can be shielded from the effects of disconnections by edge-computing hardware running on the premises.
8power, from Cambridge, UK, produces self-powered wireless sensor solutions for industrial plant applications and machine condition monitoring. The startup uses its patented Vibration Energy Harvester to power its sensors. This concept helps solve a fundamental problem of the Internet of Things (IoT): how to power the many wireless sensors that the IoT needs without the necessity to replace batteries. 8power has neatly solved the problem by harvesting energy from mechanical vibrations in a very clever way. Together with ABB’s oil and gas team, 8power focused on the integration of AI algorithms integrated into self-powered wireless sensor solutions for diagnostics and monitoring of devices.