Automating Lubricant Analysis with Castrol SmartMonitor Using AWS IoT SiteWise

Castrol provides lubricants and key services for marine and industrial customers. One vital service is to check the relevant oil condition parameters. This is especially important for marine customers, which represent unique challenges such as hostile operating environments. The traditional UOA process is done manually and requires scheduled downtime to test a machine’s oil, send it to a lab, and wait for results, which can take up to 3–8 weeks. “Seeing near-real-time UOA data will not only help the technical personnel on board but also the vessel’s captain, who has ultimate responsibility for the vessel and its crew. Any UOA data moving away from the normal values can have safety and financial impacts, and early detection can prevent these,” says Barry Sullivan, technical service engineer at Castrol.

Castrol decided to build a near-real-time digital solution for its customers using AWS IoT services. SmartMonitor is part of a top-down strategic initiative to digitize Castrol’s products and use managed, low-code services, and it represents a proof point for future projects. Castrol had already been using AWS before, but this solution was the company’s first instance of using AWS IoT services.

Working alongside the AWS Solutions Architecture and supplier teams, Castrol Digital architected and built an IoT solution. The company also collaborated with AWS Professional Services—a global team of experts that helps organizations deliver their cloud initiatives—to quickly resolve early technical issues while ingesting sensor data into the cloud. Castrol rolled out its minimum viable product in December 2021, after 6 months of development, and has since added several trial customers to test the solution. Castrol made key architectural decisions that reduced time to value and achieved long-term business agility for this solution.

After hardware installation, Castrol can onboard new SmartMonitor customers in as little as 1 week. This simple solution helps customers install their own sensors onsite, whereas connectivity and configuration are fully managed by the Castrol team. The solution collects machine data, determines which sensor type will be used, and runs the information through an automated script to generate a database and visualization layer. This automatically creates the services needed in AWS so that customer data can be fed directly into the solution. This automation frees up manpower for other activities while minimizing touchpoints with critical machinery and oil.

Oil quality data is read by sensors connected to an edge gateway running at the customer site using AWS IoT Greengrass, an open-source edge runtime and cloud service for building, deploying, and managing intelligent applications at the edge. SmartMonitor can convert any sensor protocol to MQTT for consumption in the cloud but also cache sensor data locally in case the gateway experiences interruptions in communications. (See figure 1. IoT architecture.)

The data is then securely sent to AWS IoT Core, which can be used to connect billions of IoT devices and route trillions of messages to AWS services without managing infrastructure. From there, data is sent through SmartMonitor’s AWS-powered pipeline, which determines how the oil is functioning. This enriched data is stored in AWS IoT SiteWise, a managed service that simplifies collecting, organizing, and analyzing industrial equipment data. Under the AWS Shared Responsibility Model, Castrol prioritized strong security in its data storage setup and the adoption of a single sign-on system. “We are following the principle of least privilege,” says Hind Messbah, technical lead of SmartMonitor at Castrol. “Users are granted the minimum level of access needed to visualize their dashboards, and we reduce the potential impact of broad access.”

The solution gives customers access to near-real-time insights on oil quality so that they can respond proactively to potential issues. (See figure 2. High-level architecture.) It also relies on data-driven maintenance, so it maximizes lubricant use and minimizes waste, thereby saving money for customers. During the solution trial, one customer saved over 100,000 dollars in repair and maintenance costs by early detection of a water leak in their lubrication system. “Our customers save costs by taking corrective action when our solution notifies them that machinery isn’t performing as it should,” says Bhav Magar, principal IoT delivery lead of SmartMonitor at Castrol.

The SmartMonitor team estimates that customers will reduce engine repair and maintenance costs by up to 10 percent through early alerting, and the solution has a two times potential return on investment in the first 5 years. Castrol can also scale seamlessly with its new solution. “Castrol designed a modular and extensible architecture using AWS-native services such as AWS IoT SiteWise. With the incorporation of microservices and modularity within the AWS solution, we plan to expand the application’s scalability, reaching a broader external customer base and encompassing all Castrol plants,” says Noorddin Taj, lead architect of SmartMonitor at Castrol. With 14–20 business-to-business enterprise customers, the company is analyzing millions of data points per month and will scale up when the product is released commercially.

Castrol has achieved success with its trial customers and plans to roll the solution out commercially in 2024. The company is also interested in building similar solutions using AWS IoT services for other use cases, such as waste oil, mining equipment, and liquid condition monitoring.

The company is improving the user experience of its solution. It is using AWS to provide a more customized website experience with new functionalities—for example, giving more control over graph components and improving insight navigation.

“The solution we’ve built using AWS is technically advanced and has solid analytics behind it,” says Magar. “To build it in 6 months and be able to release new features in an agile and iterative approach over time was a big achievement.”