Read about some real Industry 4.0 usecases.
Companies and organisations are naturally secretive about new innovations as they don’t want competitors knowing what they are doing. This is unfortunate because Industry 4.0 success stories aren’t shared which hinders rather than encourages uptake of new technologies. This is particularly so in the area of Industry 4.0 AI machine learning where projects and their valuable insights are rarely shared.
- BeOne Analyzer – Natural Language Processing (NLP) and Sentiment Analysis to extract conversation from messenger service, extract products, brands, types, or models information, analyze the conversation’s sentiment based on weighed words scoring.
- QCNext a vision based AI/ML Quality Check Solution – Quality Check process during manufacturing and that’s how the idea to develop a vision based AI/ML solutions that would improve the QC process.
SAP have had a history of sharing case studies. Their older Industry 4.0 overview also provides some examples:
With an Industry 4.0-enabled factory, Harley-Davidson can build 1,700 bike variations on one production line and ship an individualized bike approximately every 90 seconds. At the same time, the company has brought costs down 7%, increased net margin by 19%, and slashed the locked schedule to build a bike from 21 days to 6 hours
Certain steel and paper companies are building the Internet of Things directly into their production processes to detect or predict deteriorating quality. Their goal is to detect issues early enough for operators to “save” the product by making adjustments in real time.
The paper also has some information on customer value through the use of feedback. Customers can become vital contributors of insights:
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