How digital assistants are changing maintenance organizations

June 17, 2020 | 3 minute read
Text Size 100%:

By Lee Sacco, Senior Director of Applications Development, Oracle SCM

Your maintenance organization needs complete and accurate asset and maintenance data for analytics, quality management, financial reporting, and regulatory compliance. But while maintenance technicians love fixing problems, they don't always love typing and clicking on a computer. Greasy fingers, tools-in-hand, and a backlog of broken machines to fix take priority over data entry, even though that data is priceless to the business. Oracle Digital Assistant (ODA) allows technicians to capture that data and keep their hands free to do the work they do best. 

On May 15th, Oracle’s Solution Engineering team published a Maintenance Assistant skill for Oracle Digital Assistant that provides a voice interface between technicians, the Oracle Maintenance Cloud, and Oracle Machine Learning. Technicians can use their voice to capture data, complete operations, issue materials, and request data in the Maintenance Cloud application. They can also request machine learning predictions for root cause of failure, recommended next best action, and additional maintenance recommendations from Oracle Machine Learning. 

Stream the business case overview and see the digital assistant in action here:

Oracle Digital Assistant enables AI-powered conversations, letting technicians use natural language to give commands and request information, with enterprise-specific speech recognition out-of-box and the ability to learn industry- and company-specific vocabulary. 

For example, the Maintenance Assistant skill knows maintenance-specific vocabulary like “start work order”, “complete operation” and “job complete” and is ready to learn synonyms and jargon on-the-fly. The AI can deal with accents, synonyms, awkward phrasing, and noisy shop floors. 

Besides the AI engine, ODA makes it easy to enhance or extend the Maintenance Assistant skill and setup business-specific processes and workflows without coding. For example, the Maintenance Assistant requires the technician to enter a root cause of failure before completing the job, but additional constraints can easily be added based on an organization’s unique processes. 

ODA also provides a single, unified interface to connect to multiple systems, functions, or services. The Maintenance Assistant uses this unified interface to capture maintenance data in the Maintenance Cloud application while invoking predictions and recommendations from Oracle Machine Learning. ODA makes it easy to connect and disconnect apps and services based on the unique needs of the business. 

For example, ODA could be configured to retrieve data from a legacy system or request a machine learning prediction of the remaining useful life of a part if the technician wants that information. Because the Maintenance Cloud application has a built-in Extract, Transform and Load (ETL) program that generates a machine-learning-ready set of historical asset and maintenance data, Oracle Machine Learning can effectively mine this data to find patterns, make predictions, and offer recommendations. 

ODA also allows technicians to use the voice interfaces they use in their own homes, like Alexa, Siri and Google Assistant, making it much more familiar, comfortable, and enjoyable to use. And when the technicians enjoy using the system, the business is more likely to get that complete and accurate data it needs. The Maintenance Cloud with Oracle Digital Assistant and Oracle Machine Learning helps technicians see data in new ways, discover insights, unlock endless possibilities. 

Guest Author

Previous Post

How to improve your procurement processes with Contract Lifecycle Management

Ana Galindo | 4 min read

Next Post

Managing risk for a more resilient and agile supply chain

Guest Author | 3 min read