{"id":14796,"date":"2022-02-07T11:06:40","date_gmt":"2022-02-07T10:06:40","guid":{"rendered":"https:\/\/www.profactor.at\/?page_id=14796"},"modified":"2022-03-04T07:29:58","modified_gmt":"2022-03-04T06:29:58","slug":"predmain","status":"publish","type":"page","link":"https:\/\/www.profactor.at\/en\/research\/industrial-automation-systems\/robotics\/projects-archive\/predmain\/","title":{"rendered":"PredMAin"},"content":{"rendered":"

[vc_row][vc_column width=”3\/4″][vc_column_text]\"\"[\/vc_column_text][vc_column_text]PredMAIn (Interreg, 2021-2022)<\/strong><\/p>\n

AI-based predictive maintenance<\/p>\n

 <\/p>\n

Initial situation
\n<\/strong><\/p>\n

AI-based Predictive Maintenance Project (ATCZ279)<\/p>\n

The Interreg programme area Austria-Czech Republic is a region with a high number of SMEs. Many of them are active in the production and manufacturing of production equipment.<\/p>\n

 <\/p>\n

Problem<\/strong><\/p>\n

Predictive maintenance (PM) is currently considered the main application of artificial intelligence (AI) in manufacturing. For several reasons, the associated potential is insufficiently exploited by manufacturing SMEs, which are very strongly represented in the programme region. To a large extent, the prerequisites for the widespread application of AI in predictive maintenance by SMEs are lacking. This includes easy and uncomplicated application by the operating personnel on site. Unlike maintenance staff in large companies, they are often not specially trained in the possible applications, advantages and potential dangers of AI in predictive maintenance.<\/p>\n

 <\/p>\n

Objective<\/strong><\/p>\n

The project objective is therefore the creation and transfer of general and transferable\u00a0knowledge for manufacturing SMEs on AI-based predictive maintenance (output)<\/strong>\u00a0applicable in
\nvarious sectors of production and manufacturing.<\/p>\n

 <\/p>\n

Approach and cross border approach
\n<\/strong><\/p>\n