Talk about my Pitch-In projects: IIoT and Predictive Maintenance for Legacy Manufacturing System

Glad to talk about two pitch-in projects we recently work on. One project is led by myself with Sheffield team (M17), the other is led by Alexandra's team from Cambridge IfM. Please check the video recording of my presentation. The other projects presented in this webinar are also quite interesting. It also got many interesting Q&A at the end.

-Link of the video:

Title: IIoT and Predictive Maintenance for Legacy Manufacturing System

https://youtu.be/0VgfkGVRt1E?t=2305

- Link of the webinar:

https://www.ifm.eng.cam.ac.uk/events/pitchin-webinar/

- Link of our dataset repository:

E-coating ultrafiltration maintenance dataset

https://www.kaggle.com/boyangs444/process-data-for-predictive-maintenance

- Links of related projects:

• M17 Pitch-In: Internet of Things (IoT) approach for predictive maintenance: a manufacturing case study

• M12 Pitch-In: Distributed learning with IoT for quality control in manufacturing

- Links of related press articles:

• Developing an automated industry IoT solution for predictive maintenance

• Building strategic partnerships with industry: Tinsley Bridge and the University of Sheffield

We have submitted our research paper and it is under review at this moment. Once the paper is published, I will make our project GitHub repository public.

Song, B., Brintrup, A., Turner, C., Kelly, A. and Tiwari, A. (2020). Deep Transfer Learning for Industry Internet of Things based Predictive Maintenance. IEEE Systems Journal (under review)