UPTIME Predictive Maintenance:
Lessons Learned and Best Practices in White Goods Industry
The UPTIME 1st live webinar will highlight the differences between classic preventive maintenance and predictive maintenance using historical data and real time data as well as illustrate benefits of predictive maintenance by a concrete implementation in the White Goods Industry. The UPTIME white goods business case deals with Whirlpool’s complex automatic production line, which produces drums for clothes dryers. The business case aims to anticipate planned intervention on machines, to reduce unexpected breakdowns and delay other interventions, thus save money and improve safety.
Moreover, in the webinar you will be provided with three main important lessons learned as well as best practices for manufacturing companies to get started with predictive maintenance.
The webinar is free of charge, dedicated to people who want to learn and see a concrete implementation of the UPTIME Predictive Maintenance Platform in a real business case. It will be interactive, where you will have the opportunity to ask questions to the experts panel and we will be happy to receive your feedback. If you have any questions or comments, please contact us.
Pierluigi Petrali has been working at Whirlpool Europe since 1989. He started his career in Information Technology, working at introduction in Whirlpool of CIM, MES and Fault Tolerant Networks. He has then worked in innovation projects, contributing to the spread and growth of TRIZ methodology in Italy and Europe and to the development of product/process design support approaches.
Presently he coordinates manufacturing research and development activities for EMEA region. Directly involved as technical and main partner in more than 10 funded research projects under FP7 and H2020 program in the last five years, he is currently working in definition and implementation of Whirlpool Industry 4.0 strategy.
He is the inventor of five patents and author several technical papers and public speech on TRIZ, Technology Forecasting, Manufacturing Quality, Internet of Things and Industry 4.0.
24 – 25 March 2020
20 – 24 April 2020
08 – 12 June 2020
15 – 19 June 2020
29 – 30 June 2020