Machine Vision in Field Service Operations and Manufacturing: How BCG X’s AI-Driven Approach Can Help Unlock $8 Billion in Value
At BCG X, we are not following the trends in AI adoption in field service operations and manufacturing: We’re playing a crucial role in setting them. With hundreds of successful implementations, our experience spans a vast range of use cases in which the combination of AI & machine vision plays a transformative role. AI & machine vision stands at the forefront of industrial innovation, offering capabilities that address complex servicing and manufacturing challenges. These combined technologies enhance precision, speed, and efficiency, which are critical to maintaining competitive advantage in a rapidly evolving market. By integrating AI-driven solutions such as real-time quality inspection, predictive maintenance, and automated inventory management, service providers and manufacturers can achieve:
- Increased Operational Efficiency: AI algorithms powered by machine vision optimize production workflows, reducing waste and increasing throughput.
- Enhanced Quality Control: Machine vision conducts inspections with greater accuracy than human operators, significantly reducing error rates.
- Advanced Predictive Analytics: AI minimizes downtime and extends the lifespan of machinery by predicting equipment failures and maintenance needs.
The economic implications of these enhancements are profound. As AI & machine vision applications become more widespread, they can unlock $8 billion of potential impact on the industry. This estimate is grounded in a comprehensive analysis of operational improvements and cost savings across hundreds of successful AI deployments. Why, then, is adoption of this powerful combination of technologies so low?
The answer lies at the very crux of implementing AI & machine vision in field service operations and manufacturing. For one, the task of building and maintaining a machine vision solution is not straightforward. Every implementation is akin to “tailoring a suit,” requiring customization on the field and shop floor. Furthermore, there is the matter of “closing the loop.” Many companies build algorithms successfully, only to fail when trying to link them to actionable insights. Finally, there are significant infrastructural needs. Implementation of AI & machine vision requires the presence — and continuous maintenance — of suitable hardware and software. Meeting these three challenges alone can be challenging for many companies.
BCG X’s Field Service AI and Manufacturing AI has developed a 5-step approach focused on building and deploying AI & machine vision applications to unlock business value:
Start with value before execution: Drawing upon decades of our experience and the expertise of our clients, we focus on connecting the dots between the development of algorithms and their implementation. The key is to zoom in on use cases that will create maximum value. To ensure this, we meticulously assess every potential use case for its ability to deliver significant ROI (return on investment).
One of our clients, a food manufacturer, had developed a number of potential use case ideas, but was not certain of the value they might gain from them. In response, our team of experts and data scientists collaborated with the client to evaluate the proficiency and potential business impact to first conceiving and then implementing the most promising use cases. Our strategic analysis extended across the client’s entire manufacturing and field service value chain, allowing us to uncover nuanced value propositions that a simplistic approach might have otherwise overlooked. This approach resulted in a potential cost reduction of $13M for a single plant, highlighting the remarkable potential of these interventions.
Build a scalable architecture to enable customization: Leveraging our expertise in digital solutions, we have engineered a highly scalable machine vision architecture designed to accommodate individual clients and support a diverse range of use cases. This architectural agility is achieved through the strategic utilization of IoT edge devices, standardized deployment methodologies, and a multidisciplinary team of experts specializing in IoT, engineering, data analytics, and cloud computing.
Our machine vision architecture helped us deliver scalable and easily maintainable solutions across various client engagements. As a result, our clients were able in a matter of months to successfully scale their pilot implementations to operate across multiple factories, attesting to the efficacy and scalability of our architectural approach.
Develop in BCG’s Machine Vision Lab environment to accelerate iteration cycles: To build and test machine vision algorithms, we needed an environment to build fast prototypes and ensure rapid iteration cycles. Our Lab, which brings together physical and digital capabilities under one accessible roof, provided us with the perfect environment. The lab’s specialized tools, including industrial cameras and edge computers and gateways, enabled us to deliver effective, real-world AI solutions from day one.
The Machine Vision Lab has enabled BCG teams to promptly develop prototypes and, within weeks, roll out adaptable, custom algorithms, thus making the formerly formidable task of customization both accessible and modular. This rapid pace was achieved through persistent testing only within the lab environment, ensuring that our clients’ production lines and services remained unaffected. The process also included continuous feedback and validation from experts, further refining the implementation of these sophisticated technologies.
Design a user interface (UI) to meet specific needs: In deploying machine vision technology, the UI plays a crucial role in ensuring that the data generated is easily understandable and actionable. Our approach is to tailor the UI design to meet the unique operational needs of each client. Through an iterative design process, we create a seamless experience for the hybrid teams, enabling them to quickly interpret the machine vision results and take necessary actions to maximize value.
A tangible example of this approach is our collaboration with one client’s shift managers and engineers to develop a customized user interface. The goal was to allow quick actions and reactions based on the data presented. The iterative feedback process helped refine the interface, ensuring that the necessary actions were clearly identifiable. The customized UI significantly minimized reaction time of shift managers and engineers.
This experience reaffirmed the importance of a tailored UI in effectively harnessing machine vision technology. By creating an intuitive interface that caters to our clients’ specific needs and operational contexts, we can significantly enhance the decision-making process, ensuring that the insights generated by machine vision algorithms are utilized to their fullest potential, thereby achieving operational excellence.
Enable customers through upskilling and focus on value: Building on the resources offered by our scalable infrastructure and machine vision lab, we offer expertise in the form of AI & machine vision specialists. The specialists’ role goes beyond immediate problem-solving: They serve to upskill talent within organizations, guiding them through their AI journey. Our end goal is to foster a hybrid team of operational-technology, information-technology, and data science professionals capable of maintaining and improving machine vision systems. By focusing on talent development, we prepare our clients for a sustainable future in the realm of machine vision.
Working closely with another long-standing client, we successfully built a dedicated Data Science and Engineering team, effectively reshaping the client’s approach to data utilization and algorithm creation. Our approach fostered collaboration among previously siloed teams, enabling the client to co-create cohesive, unified analytical solutions focused on value.
These five steps represent an innovative approach to unlocking the value of machine vision applications. By shifting the focus from mere development to implementation and value creation, we are establishing a new trend, one that helps our clients use machine vision to rethink entire field service and manufacturing processes.
