Building a Strong Collaborative Framework for Artificial Intelligence
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Building a Strong Collaborative Framework for Artificial Intelligence

Boon Siew Han, Chief Information Officer Asia Pacific, Schaeffler
Boon Siew Han, Chief Information Officer Asia Pacific, Schaeffler

Boon Siew Han, Chief Information Officer Asia Pacific, Schaeffler

Once confined to the domains of science fiction, artificial intelligence (AI) has since come a long way in imitating intelligent human behavior. From transportation to manufacturing and production processes, the advancement of AI has led to profound changes in the world of mobility and motion.

The use of AI can be grouped into rule-based systems and highly complex systems based on Machine Learning and Deep Learning algorithms. This enables the processing of data where these algorithms can draw patterns and make predictions such as visual inspection, predictive maintenance, and sales forecasting.

For the automotive and industrial sectors, these developments have led to greater interest and demand for more intelligent offerings and are paving the way to entirely new production and service concepts. For instance, improved connectivity and Internet of Things (IoT) applications have led to the development of remote condition monitoring and predictive maintenance. These lead to higher efficiency gains and better reliability, ultimately improving production quality.

Likewise, we expect that around 30% of all new passenger cars and light commercial vehicles produced in the world will be partially automated in the automotive sector. Moreover, half of them will have the capability for highly automated driving.

Creating a Robust Artificial Intelligence Framework

In light of these developments, there is a stronger emphasis on leveraging data science and analytics to enhance processes and productivity. To best utilize these opportunities, industrial players should implement a robust artificial intelligence framework and strategy to strategically optimize the use of AI for crucial insights and increased efficiency and agility.

 Cost-effective energy storage will play a key role in that transformation 

At Schaeffler, we have anchored our AI strategy based on six guiding principles: Organization, Talents, Ecosystem, Value, Codex (Code of Ethics), and Processes.

These six guiding principles allow us to strengthen our AI capabilities, focusing on business-value delivery and requirements while establishing trust and competencies among our employees.

For instance, by intelligently integrating AI and machine learning in operational processes and the cloud, we continually optimize various aspects of our plant operations, including our maintenance cycles – allowing us to achieve significant reductions in throughput times at our manufacturing plants.

As we look to better support our employees in their daily work, we are also working on advanced, intelligent assistance functions that enable natural language interaction between humans and machines.

Collaboration and Open Innovation

As a supplier of the automotive and industrial sectors for more than 75 years, we understand that it is only through collaboration and strong partnerships that we can expand the state of new technologies and transfer these insights to our business.

One way we are doing this is through our open innovation model, where we partner with academia for research and knowledge transfer and start-ups to bring vital innovation to our business.

On the academic partnerships front, we established the Schaeffler Hub for Advanced Research (SHARE) network in 2013, with leading universities worldwide – in Europe, Asia/ Pacific, China, and America – where we partner with university scientists, postgraduate and undergraduate students to bring innovative insights that can transform and shape the world of mobility and motion.

For instance, our SHARE at Nanyang Technological University (NTU) lab in Singapore focuses on industrial applications of AI and robotics and was recently awarded the Innovation in Hardware Award for its GraviKart robotic push trolly solution at the International Conference on Social Robotics (ICSR) 2021. Similarly, in other SHARE facilities, we are leveraging AI to support our research and development work in areas such as electric and automated mobility, interurban mobility, battery technology solutions, and digitalization through data-driven modelling and embedded AI systems.

Using intelligent systems and components to provide listening, speaking, and visual recognition capabilities for effective communication between employees and robots, GraviKart is part of our efforts to reimagine shopfloor operations that better support shopfloor employees with their tasks and productivity.

On the other hand, we partner with networks such as Plug and Play to connect with some of the brightest start-ups globally. The partnerships allow us to bring in external perspectives that broaden our knowledge regarding new technologies and processes, which enable us to develop new competencies that generate the highest value for our customers.

Additionally, we have joined an incorporated society with eleven other partners in Germany to foster real-life applications in the field of artificial intelligence for the associated development of ethical and regulatory frameworks for Germany and the rest of Europe.


As advancements in artificial intelligence continue to evolve, so will expectations and acceptance of the technology. Companies should thus start to embark on a strategic, comprehensive long-term plan to integrate these technologies while ensuring openness to new forms of thinking through collaboration to unlock the maximum value of these opportunities.

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