Search Engine Industrial Plant Data

Background

This thesis will be written at ABB AG. ABB (www.abb.com) is a leader in power and automation technologies that enable utility and industry customers to improve performance while lowering environmental impact. The ABB Group of companies operates in around 100 countries and employs about 145,000 people.

Thesis Description

A typical industrial plant, such as a petro-chemical plant, generates a large amount of data every year: measurement values, alarm and event logs, laboratory results, maintenance reports, and so on. The amount of data gathered can easily sum up several hundreds of gigabytes per year, resulting in truly big data. The availability of such historic data makes big data analytics and technologies interesting also for the industrial domain. In our BMWF public funded project “FEE”, ABB Corporate Research is collaborating with industry and university partners to develop such concepts for big data analytics for industrial plants.

The objective of your master thesis will be the development of (big) data analytics algorithms and methodologies to enable building a search engine that will allow plant operators to search their historic plant data for information related to their current plant situation, e.g. searching whether a given plant situation has already happened in the past in a similar way.

 

For additional information, please see the attached file.