In today’s industrial domain, digital transformation is accelerating at unprecedented speed. Technologies such as artificial intelligence, IoT, and advanced software are reshaping manufacturing, power distribution, and operations worldwide. Yet, translating promising concepts into robust, scalable industrial solutions remains a challenge. Long asset lifecycles, strict safety protocols, and the convergence of operational technology (OT) and information technology (IT) demand exceptional reliability, cybersecurity, and resilience – requirements seldom met through ad-hoc development.

The risk of “pilot purgatory” – where promising innovations stall after a single trial – is real. To counter this, ABB has developed a formal innovation framework that guides the journey from idea to scalable solution. This framework integrates two interdependent foundational elements: a structured process and a flexible technology platform. The ABB Accelerator is a structured engine for collaborative, ecosystem-driven innovation. It identifies, validates, and matures high-potential ideas. Complementing this is the Core Platform, a cloud-native technology backbone based on principles such as Infrastructure as Code (IaC) and containerization, enabling secure, scalable deployment – on-premises, in the cloud, or at the edge.

Together, these two foundational elements form ABB’s repeatable innovation formula, one that accelerates time to market, reduces risks, and ensures scalable, sustainable deployment. Two examples »01, »02 of real-world use cases illustrate how this innovation engine works in practice and how it has delivered transformative outcomes.

01 Case study 1: Follow Me

A salient example of the power of ABB’s “engine and chassis” innovation framework is “Follow Me,” a breakthrough in industrial robot programming from the Shanghai Accelerator event. The program’s developers based their innovation on the fact that adoption of traditional robot programming is particularly difficult for small and medium-sized enterprises (SMEs), as well as in high-mix, low-volume production environments. The process typically requires highly skilled roboticists to perform offline programming with CAD models, followed by extensive online fine-tuning on the factory floor. The resulting high cost and complexity effectively lock many potential users out of the benefits of robotic automation.

In view of this, “Follow Me” developers came up with an intuitive, demonstration-based programming approach that allows an operator with no programming expertise to simply guide a robot’s end-effector along a desired path »01a. High-fidelity internal sensors capture the entire motion at teaching speeds of up to 1,000 mm/s. Advanced AI algorithms then instantly process the raw path data to generate a smooth, kinematically optimized trajectory. This automated procedure delivers precise, executable programs in seconds, achieving path accuracies within three to 15 mm and orientation accuracies ranging from two to 3.5 degrees, thus allowing a robot to perform a task on its own without further human intervention »01b.

The solution’s versatility is remarkable. Supporting full six-degrees-of-freedom (6-DoF) movement, “Follow Me” is applicable to complex tasks that require nuanced tool orientation and control »03. It seamlessly integrates with standard I/O signals, enabling the control of external machinery such as spray guns, polishing heads, and grippers. As a result, this solution caters to a wide array of industrial applications – from powder spraying and painting to cleaning, grinding, and even teleoperation.

The rapid development of “Follow Me” is a clear demonstration of the synergy between process and platform. The Accelerator process ensured initial validation. By bringing together customers, partners, and internal experts, the concept was vetted against real-world needs, ensuring that development was focused on solving a genuine industrial pain point. This collaborative feedback was crucial in refining the feature set and defining the value proposition.

Simultaneously, the Core Platform ­provided pivotal technological leverage. The reuse of pre-built, containerized modules for the robot’s base operating system and communication infrastructure saved the R&D team months of foundational work. The platform also provided a standardized environment for testing and simulation. This freed the team to focus their resources entirely on novel, value-­adding components – specifically, the sophisticated path-teaching algorithm and the intuitive user interface

02 Case Study 2: AI for quality inspection in manufacturing

ABB’s “engine and chassis” innovation framework is just as transformative for the company’s own operations as it is for those of its customers. An AI-powered quality inspection system at an ABB factory in Frosinone, Italy is a case in point. To understand the key role of AI in this context, one must consider that in high-volume manufacturing, ensuring 100 percent quality is paramount. Manual visual inspection, while necessary, is labor-intensive, slow, and inconsistent. The goal is therefore to design an automated defect detection system that performs quality inspections with superhuman speed and precision on the production line.

To achieve this goal, a solution has been developed whose architecture is engineered for real-time performance and scalability. High-resolution cameras capture images of circuit breakers as they are being manufactured »02a. The images are processed by a compact convolutional neural network (CNN) model. This AI model, which is optimized for edge inference, is deployed onto industrial PCs on the factory floor. This edge architecture is vital, enabling real-time, ultra-low latency analysis without the delays associated with transferring large data volumes to the cloud.

If a defect is detected »02b, the system sends a signal via a standardized API, triggering immediate corrective actions, such as diverting the defective unit from the line. The fully-automated inspection cycle for quality control significantly increases the overall automation of the line and improves detection accuracy for defects »02c.

This quality inspection project highlights how innovative approaches can enhance both quality and manufacturing efficiency. Its structured process enabled validation and delivery of a working proof-of-concept within a single quarter. Executive sponsorship and close collaboraton ensured that development aligned with operational requirements and measurable business outcomes. The solution built in Frosinone can be replicated across other factory sites with minimal adjustments, thus embodying the “design once, deploy many” principle. Looking ahead, this use case also serves as a foundation to explore next-generation agentic AI and data platforms, paving the way for autonomous agents that will significantly boost quality and productivity in manufacturing.

In today’s industrial domain, digital transformation is accelerating at unprecedented speed. Technologies such as artificial intelligence, IoT, and advanced software are reshaping manufacturing, power distribution, and operations worldwide. Yet, translating promising concepts into robust, scalable industrial solutions remains a challenge. Long asset lifecycles, strict safety protocols, and the convergence of operational technology (OT) and information technology (IT) demand exceptional reliability, cybersecurity, and resilience – requirements seldom met through ad-hoc development.

The risk of “pilot purgatory” – where promising innovations stall after a single trial – is real. To counter this, ABB has developed a formal innovation framework that guides the journey from idea to scalable solution. This framework integrates two interdependent foundational elements: a structured process and a flexible technology platform. The ABB Accelerator is a structured engine for collaborative, ecosystem-driven innovation. It identifies, validates, and matures high-potential ideas. Complementing this is the Core Platform, a cloud-native technology backbone based on principles such as Infrastructure as Code (IaC) and containerization, enabling secure, scalable deployment – on-premises, in the cloud, or at the edge.

Together, these two foundational elements form ABB’s repeatable innovation formula, one that accelerates time to market, reduces risks, and ensures scalable, sustainable deployment. Two examples »01, »02 of real-world use cases illustrate how this innovation engine works in practice and how it has delivered transformative outcomes.

Three pillars

The ABB Accelerator is an outcome-driven process designed to fast-track innovation through four stages: ideation, validation, piloting, and scalable deployment. Launched at events in Krakow and Bangalore in 2024 and expanded to Mexico and Shanghai early in 2025, the process is built on three core pillars:

• Business Value: Every innovation begins with a real-world problem statement, often sourced from customers or ABB’s Business Areas. This disciplined focus ensures projects are technically feasible and selected for clear market relevance and measurable impact, such as increased efficiency, reduced costs, or new revenue streams.
• People Development: Innovation thrives in a culture of learning. The Accelerator cultivates digital skills via “AI Boost” sessions and hands-on training, accelerating project delivery and internal expertise, including agile methodologies, lean startup principles, and emerging technologies.
• Ecosystem Building: Collaboration is at the heart of the Accelerator. Recognizing that no single entity holds all the answers, the process actively engages a diverse ecosystem of collaborators. This includes strategic customers who provide invaluable real-world context, academic institutions that contribute cutting-edge research, and innovative startups that bring specialized technologies or novel approaches. This open, co-innovative model ensures that projects are enriched with diverse perspectives, leading to more robust and impactful solutions.

The Accelerator process provides early proof-of-concepts and iterative feedback cycles that ensure rapid validation and scalability from the outset – engineering for operational excellence, not just novelty.

Of course, one might suggest that the resulting innovations could emerge organically from within a business. However, the concept behind the accelerator is that, by creating an ecosystem driven by focused, collaborative incentives, it makes innovations more reusable and widely recognized, thus ultimately boosting the velocity of innovation and resulting in a competitively significant impact. This is why ABB’s Accelerator focuses on three pillars: Business Value, People Development, and Ecosystem Building – not just business value.

Engine and chassis

If the Accelerator is the engine that drives innovation, then the Core Platform is the robust chassis that delivers it to market. Built on cloud-native principles, it offers automation, security, and scalability through containerization and Infrastructure as Code (IaC), empowering teams to rapidly build, test, and deploy industrial applications. This combination of characteristics offers the following key advantages:

• Flexibility: Aligned with ABB’s “Local for Local” strategy, the platform is infrastructure-agnostic – supporting deployment on-site or in major cloud environments to meet regional regulations and data sovereignty needs. This hybrid capability is critical for industrial customers with diverse IT landscapes.
• Standardization: Pre-built modules, standardized APIs for data exchange, and security protocols create a shared language that allows disparate systems to interoperate seamlessly, enabling integration without rigidity. This ensures adherence to architectural guidelines, while providing flexibility for localized adaptations.
• Scalability and automation: Solutions developed on the core platform are “born scalable.” Standardized containerized modules and reusable components enable a “develop once, deploy many” model, reducing the engineering effort required to roll out a solution to multiple sites. This is underpinned by CI/CD (continuous integration/continuous deployment) pipelines that automate the building, testing, and deployment of software, removing manual bottlenecks and increasing the velocity of innovation.

Repeatable formula for leadership

In an era defined by rapid digital transformation, the ability to convert innovative concepts into industrial-grade solutions quickly and reliably is essential. ABB’s innovation framework, which is anchored by the Accelerator process and powered by the core platform, offers a repeatable and scalable model for success. This systematic engine for innovation enables ABB to continuously deliver advanced solutions that address both customer-facing challenges and internal operational efficiency.

The two case studies presented in this article are not isolated stories but tangible outputs of a disciplined, collaborative approach that de-risked the innovation journey and accelerated time-to-market. By clearly defining the innovation process and anchoring it in a flexible yet robust technology infrastructure, ABB has bolstered its leadership in industrial digital transformation.

As industries face increasingly complex challenges, ABB’s dual-pronged strategy provides the agility and resilience required for long-term success. The company’s approach is about embracing technological advancements and harnessing the collective genius of its global ecosystem, thus ensuring that each innovation delivers measurable value. By leading with a systematic, co-innovative mindset, ABB is not merely adapting to change, it is driving it.

References
[1] Dubé, Renaud and Dymczyk, Marcin, “Seeing with AI,” ABB Review 01/2025