Malfunction area classification to support the remote diagnostics of medical device

The classification algorithm is able to identify the correct malfunction area given a free text input with an average of 85% accuracy. It can also handle multi languages.

Input(s):

• Service work order (SWO) data

Main feature(s):

• The classification algorithm and user interface are developed to automatically determine the suspected malfunction area given (limited) service case details such as subject, problem reported by customer, consumed replaced parts, or case activity notes written by engineers

Output(s):

• Identified malfunction area for the given SWO

• Require service work order (description of the problem) as text input
• Some specific Python libraries required

Remote service engineer of medical devices.

Licensing