Kaeser Kompressoren
Assembly Line
How Kaeser Uses AI to Add Customer Value
To start, the project team looked at Kaeser’s master data. “Just to give you one example: our system contains a six-digit number of suppliers, at least two-thirds of whom were inactive,” Lameter says. Maintaining that data manually would have involved a disproportionate amount of effort, which is why many companies hesitate to tackle data projects of this size.
The result was Predicting Inactive Suppliers, a custom AI use case based on one of the SAP AI Services – the Data Attribute Recommendation service – and SAP Analytics Cloud. This solution has enabled Kaeser to automate more than 80% of its data maintenance tasks, improve data accuracy, and achieve significant productivity gains.
But now, Visual Spare Parts Search, a custom AI use case developed in cooperation with nyris, allows Kaeser service technicians to simply take a photo of the needed spare part. The embedded nyris Visual Search AI service uses image recognition to compare uploaded images against the spare parts database and identify the correct asset ID number.
The proportion of SAP Business AI in Kaeser’s data project rose from less than 10% in the first year to over 30% in the third. Today, the team is now 100% focused on SAP Business AI and has developed 12 specific use cases targeted at adding value for customers.