AI-powered Search for Preventive Maintenance in Manufacturing

How many times have you switched your mobile phone service provider when the service or support was poor? How hard did that service provider work to keep you? It’s likely they didn’t try very hard. They have many customers, so losing one isn’t that big of a deal. But for companies that provide complex products like those in manufacturing, aerospace or oil and gas, a high-quality customer support program is critical. The question is, what does a quality customer support program look like?

The Support Challenge for High Value Products

A couple of scenarios to demonstrate the need for strong customer support and preventive maintenance programs in manufacturing industries.

Imagine you are the producer of commercial small jet engines. You want to be certain your engines are always operating at peak efficiency. Before every flight, a service technician does a visual inspection and makes notes in a maintenance log looking for things like rust, cracks, and other anomalies. You also have engine sensor data, service status data, and quality metrics. The problem is this data is spread across different locations, and in different formats, so it’s impossible to get a full picture of what’s happening with your engines.

Now imagine you are responsible for the oil and gas wells at the Houston site. You run regular maintenance checks on those wells, capture drilling data, weather data and more information that can tell you how those wells are operating. Again, this data is in different formats, spread across different systems, so no single view of the information. These wells are expensive to run and the ability to detect non-productive time early would save your company a lot of money.

Two examples, same problem. When you run complex products like those in manufacturing and oil and gas, you are dealing with a lot of disparate data that, if you could bring it all together in a single view, could provide valuable information on how that product is performing. Information that could help you address problems before they become costly.

The Value of AI and Cognitive Search

Preventive maintenance programs are focused on detecting and managing issues early. To do that, they need to aggregate and correlate large volumes of data about a product.

Cognitive search connects all your disparate data sources regardless of format - structured, unstructured, IoT, and brings it into a single view so you can easily search and find the information you need to make the right support decisions.

But that’s only part of the value of cognitive search. Underlying a cognitive solution is AI-powered technology: machine learning, natural language processing (NLP) and text analytics capabilities that can analyze all this data and over time and detect trends and patterns. This is extremely helpful when your products are complex, and maintenance issues are costly.

Without a 360-degree view of your maintenance data, your support team is manually looking across systems, trying to piece together information to get a full picture of the status of a product. What happens if they don’t get all the information they need?

And it’s impossible to detect patterns or trends when you are manually analyzing data. You are building your preventive maintenance program on set maintenance schedules that may not be required or aren’t required soon enough.

Build the Best Preventive Maintenance Program with AI-Powered Search

A mobile phone is not the same as a jet engine, or a gas well, or a piece of manufacturing equipment. You have different expectations for support than with complex manufacturing products and offerings. By developing a preventive maintenance program that is powered by AI technologies, you detect problems before they occur. It’s about operational cost savings, but it’s also about safety - for the people who use the machines, and the people who rely on them running well.

Download the eBook Deliver Better Customer Support in Manufacturing with AI Technologies to learn more about cognitive search solutions for preventive maintenance programs.