I am really interested to hear from others on here about their thoughts and experience with any IIoT Condition Based Monitoring or Predictive Maintenance Tools?
It is an area that seems to be gathering pace in the industrial world with a number of acronyms and buzz words floating around such as:
- Industry 4.0
- AI (Artificial Inteligence)
- ANNs (Artificial Neural Networks)
- Deep Learning
- Big Data Analytics
- IIoT (Industrial Internet of Things)
- Machine Learning
- Digital Twins
- Anomoly Detection
And I am sure there are many more! With all these buzz words floating about, it would be great to hear about how this technology is actually being used and what members thoughts and ideas are in relation to it?
I have thought of a few specific areas and questions that could be used for a basis of some comments......... (Please don't restrict comments to only these points below though!)
- What tools are out there (hardware and software) - both in terms of:
- Development kits such as the Brainium /SMARTEDGE AGILE that is currently available for RoadTesting
- Or commercial solutions such as GE's Predix Platform or the Honeywell Connected Plant portfolio of products
- Have you used any of these tools in industry?
- How have you or would you use some of the cloud based machine learning tools offered by some of the big cloud providers such as Amazon or Microsoft Azure?
- Does anyone have any 'Success Stories' where they have used some of these technologies to optimise machine maintenance and reduce unplanned breakdowns or even improve production yields and quality?
- What security concerns are there or should be considered around using Internet connected devices in a production environment?
- What are the advantages of using an IIoT based system vs an 'in house' system - eg. Do the AI tools available on the cloud help predict issues earlier and more accurately than a non cloud connected system?
- How easy is it to set up an IIoT based solution? How easy is it to utilise the large volumes of data that can be collected and how do you go about setting up good machine learning models?
I look forward to reading the comments others have on this!