AI-assisted Service Engineering
AI saves time in service cases.
Diebold Nixdorf, a leading provider of IT solutions and services for retail banks and retailers, is developing and training AI algorithms in the field of cash automation as part of the AI Marketplace initiative. These algorithms are based on historical ATM data and information from service calls.
Understanding ATMs through data
ATMs are highly complex mechatronic systems that are monitored through a multitude of actuator and sensor data. These data are supplemented with information from a service platform, which provides a comprehensive view of the ATM. Currently, patterns in machine data are only mapped to possible defects through simple rules, without providing the service technician with differentiated repair instructions or verifying the service instructions based on the technician’s work results. Advanced AI algorithms are also not used. Therefore, Diebold Nixdorf, in collaboration with Fraunhofer IOSB-INA, is researching use cases to develop a suitable AI solution based on existing machine and service data. The goal is to provide additional information to support the company’s service technicians in repair tasks. Currently, this information is extracted from data pools such as service calls, service contracts, or machine data. The product portfolio is now being enhanced with new services.
AI saves time in service cases
The project aims to significantly reduce the processing time of service cases during technician interventions. For example, the cause of a malfunction can be localized in the service case before the technician arrives at the device. Additionally, the process can help reduce the service call rate. Interfaces to the AI Marketplace platform are also being developed, taking into account the validity and significance of the database and the design of AI applications for product creation.
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