The servitization of connected assets

Servicing specialty vehicles is a complex task due to several factors. These assets are often widely dispersed, sometimes in remote, hard-to-access areas, making it challenging to dispatch field service engineers. Ensuring that personnel arrive on-site with the correct spare parts is crucial to avoid repeat visits and wasted time. Additionally, specialty vehicle OEMs must navigate a complex ecosystem of local dealerships and varying country regulations, making it difficult to create a consistent and effective service experience across different partners. Resistance to change is common if the value for dealers or maintenance partners isn't clear.

The specialty vehicle market is also characterized by continuous mergers and acquisitions, leading service organizations to manage multiple vehicle models from various vendors. This diversity complicates remote diagnosis and troubleshooting, increasing the time required to address issues. Further, the associated Service tools often provide limited or no visibility into vehicle performance, forcing personnel to navigate multiple specialized IT systems. This increases training time for new team members and hinders the ability to deliver consistent customer support.

Given the demanding environments in which these vehicles operate, end-users have high expectations for remote support. However, specialty vehicles typically come with extensive operating manuals and lengthy diagnostic procedures, which users are increasingly reluctant to consult. They expect automated, clear instructions and recommendations instead. Specialty vehicles frequently send data and diagnostic codes, where naive data processing rules can trigger false positive detections. There is often a disconnect between the expectations of domain experts who design these rules and the overburdened IT staff tasked with implementing them.

The Baseline Foundation needed to meet the Challenge 

Firstly, the Waylay Digital Twin platform is incredibly quick to deploy, typically very little IT support is required, you can be in production in 3-4 weeks, for very large organizations the average is 3 months. The Waylay Digital Twin seamlessly integrates with your service operations platforms, enabling real-time monitoring of IIoT assets. Whether you have a thousand or a million assets, Waylay Digital Twin offers comprehensive visibility, allowing business users to remotely monitor and manage all critical assets with ease, irrespective of the underlying IT Systems already in place.

With its flexible vehicle telematics and diagnostic real-time code processing middleware, Waylay empowers service operations teams to effectively manage their ambitious growth projections, even with limited IT resources. The Waylay Digital Twin provides a user-friendly interface for business users and domain experts to create and deploy specialty rules effortlessly, without needing to write any code. This streamlined process ensures rapid turnaround for new use cases, from creation and testing to live deployment in production. 

The Brand New Feature Waylay GenAI: 

Multi-Language Support and Efficient Repair Instruction Search

During the beta testing of our new Generative AI feature, we embraced the concept of "eating our own dog food" to ensure its effectiveness and reliability. By using the feature internally, we could thoroughly assess its capabilities in real-world scenarios. This hands-on approach allowed us to identify and address any issues promptly, ensuring that the tool met our high standards before rolling it out to customers.

One of the critical enhancements we focused on was the ability to efficiently search for repair instructions once the root cause of an issue was identified. In practice, we used repair manuals to determine the correct troubleshooting actions for various asset problems. However, we discovered that not every asset type had the most up-to-date manual sections for every issue. Some solutions were detailed in manuals for other machines, leading to missed repair actions for specific asset types, despite the proper instructions being available in other documents.

To tackle this, we optimized our LLM pipeline to search and retrieve for relevant remedy instructions across closely related documents, similar to how a human would cross-reference materials. This adjustment allowed the model to provide accurate repair actions even when exact instructions were missing from a specific manual, showcasing its remarkable capability.

Furthermore, we integrated real-time language translation to send precise instructions to repair personnel globally. This feature ensures that regardless of the technician's location, they receive accurate, understandable directions, accompanied by links to the most relevant sections of the repair manual.

By rigorously testing the Generative AI feature ourselves, we ensured that it could deliver on its promise of enhancing the customer experience through multi-language support and efficient repair instruction search. This hands-on approach proved invaluable in refining the tool and guaranteeing its readiness for broader deployment.

If you want to learn more about this solution, Contact us today and experience the power of explainable auto-remedies, seamless service assurance, and groundbreaking GenAI applications firsthand.

Alternatively, watch the demo below to see this all in action.