Infographic: AI Manufacturers Adopt Proactive Models to Maximize Machinery Uptime

While OEMs were once limited to managing after-service for their equipment to a break fix model, artificial intelligence (AI) manufacturers are ridding the industry of this reactive model in favor of one that is proactive, and focuses on maximizing machinery uptime.

Gary Brooks, CMO of Syncron:

In a recent report “Maximized Product Uptime: The Emerging Industry Standard,” Syncron, a provider of cloud-based after-sales service solutions, wrote that most manufacturers are on the cusp of investing in predictive analytics, machine learning and artificial intelligence technologies.

Furthermore, the study, which was done in conjunction with Worldwide Business Research (WBR) and polled 300 decision makers including both OEMs and end users, found that this push toward technology adoption is being driven by customer’s demands for manufacturer’s ability to guarantee and deliver equipment uptime.

All of this very much suggests the industry is moving towards servitization, in which manufactures sell the performance of their products as a service rather than selling the product itself. Naturally, this move puts the responsibility for maintaining the equipment squarely back with the OEM—and it addresses the demand from customer to be freed from the cost and complexity of equipment ownership.

“The drive to servitization is a reaction to the customer sentiment of ‘I want it when I need it, I only want to pay for it when I need it and when it breaks, I want it to be someone else’s reasonability,’” Brooks adds. “On-demand is driving massive change to the OEMs business model.

In order to meet these expectations, after-sales service efforts must become an intelligent part of the OEMs value chain that now stretches from design and procurement throughout the lifecycle of the product.  Today, 82% manufacturers report that product uptime plays into customer buying decision, while 57% of end users report they would pay extra for an uptime guarantee.

“Today’s manufacturers are well aware of their need to evolve their after-sales service functions to meet their customers’ increasing demands for maximized product uptime,” said Sara Mueller, Field Service Portfolio Director at WBR.  “While a growing list of industry leaders take steps to implement the appropriate systems, technologies and resources to meet their customers’ evolving service expectations, the laggards reject the need for change and cling to the ‘status quo’ break-fix service model.”

Currently, most OEMs are gathering data from sensor-equipped products in the field—a fairly key requirement for predictive maintenance. However, only 25% are currently using the data to support their service efforts. More than half of OEMs plan to make AI and machine learning a major investment, while 90 percent intend to invest in predictive analytics within the next 12 months.

Take a look at the infographic below to see more survey results.

Read the full story on our sister site EBNonline