Making Factories Smarter Through Machine Learning
Looking to the near future, not only will the Smart Factory( and other IIoT related“ things”) track and identify issues prior to failure, but also without human involvement( Figure 7). Already in various stages of development, we will see products and systems taking action on their own, selfoptimizing – a more prescriptive approach leading to the future of real machine time selfoptimization through Machine Learning at the Edge.
Figure 7: Evolution of Information Optimization( Image Source: Automation World webinar) This approach, of self-optimizing and self-prognostics is already under investigation. As recognized today, Machine Learning is rapidly evolving and will continue to increase in adoption in new and innovative ways, taking a pivotal role in further enhancing the intelligence of the factory.
Acknowledgements: This research has been supported by the Spanish Centre for the Development of Industrial Technology( CDTI) through the TIC-20150093 project.
IIC Journal of Innovation- 39-