Overview

Over the last 3-4 decades, process manufacturing companies have invested in improved control and better information management solutions to drive improved process performance including reduced safety and environmental risks, improved production, lower operating costs and lower working capital. In recent years, there has been increased focus on leveraging the large amounts of data collected to detect and respond to events more quickly and effectively. There have been several projects across industry to use machine learning and AI and many of these have not been effective. The webinar will look at the various methods and how to choose one that will be effective.

Speakers

Andrew Ogden-Swift, Managing Director, Newland Controls (UK) Limited

Andrew has over 40 years experience in justification, development, implementation and support of digital technologies in process manufacturing. He has held positions with Esso, KBC, ABB and Honeywell. He now works as a consultant, working mainly for operating companies and start-up companies.

Howard Boder, Consultant, Newland Controls (UK) Limited

Howard is Director & co-founder of an APC consultancy NewLand Control, with 37 years' experience in deploying digital technologies across a wide range of industries.

The material presented in this webinar has not been peer-reviewed. Any opinions are the presenters' own and do not necessarily represent those of IChemE or the Process Management and Control Special Interest Group. The information is given in good faith but without any liability on the part of IChemE.

Time

10:00–11:00 BST.

Software

The presentation will be delivered via GoToWebinar®. Check system requirements.

You are advised to join the webinar at least ten minutes before the scheduled start time, to allow for your computer to connect.

Webinar archive

This webinar is free of charge and open to all to attend, but if you wish to access the slides and a recording to replay on demand then you will need to be a member of the Process Management and Control Special Interest Group.