Challenge

As the company’s technicians repair and replace broken home appliances, they enter detailed descriptions in service call records. This information is in the form of unstructured natural language, and is hidden from normal business analytics and reporting.

Approach

Apply natural language processing and text mining techniques to identify specific product defects seen in the field. These insights are then turned into structured data which can be correlated with other manufacturing information. With the help of machine learning, the company can identify product anomalies prior to shipment.

Industry

  • Manufacturing

Tools Used

  • Data Science Experience (DSX) Local

Data Science Techniques

  • NLP, Text mining, ML (Anomaly detection)

Benefits:

  • Improvements in product quality as well as manufacturing processes

Need help with a similar case?

Contact us to find out how we can help!