It is vital that Infineum’s priorities on carbon, waste and water become an even more prominent part of our company culture, building on years of excellent work. That means bringing them to the fore in the way we track progress and make decisions. In 2020 we took significant steps to bring these dimensions of performance into business processes.

Action on measuring and prioritising sustainability includes:

  • Building a new sustainability dashboard. During 2020, Infineum brought together monitoring of environmental performance from Manufacturing Plants and Business and Technology Centres in a new sustainability dashboard that captures progress on carbon emission, energy, water, and waste. The dashboard was launched across all sites, and will help us drive action on our sustainability goals.
  • Integrating sustainability considerations into corporate capital and design processes. We drove sustainability criteria into our corporate processes and global design standards and appraisals for all projects. We also integrated an internal proxy cost of carbon for all capital investments. Our aim is to move from ring-fenced sustainability projects to a fully-encompassing approach to new designs, supporting a cultural shift towards a sustainability thinking within the company.

Digitalisation is a key enabler for our operations

Digitalisation has always been a cornerstone in our operations and is a key element of our strategy and part of our manufacturing journey to make our operations more efficient and modern. In 2020 we ran several pilots to support the key manufacturing value drivers and better understand our sustainability capabilities, via digitalisation technologies such as connectivity, mobility, wireless instruments, advanced analytics including machine learning, and cloud technology. In 2019 we began using drones to conduct flare inspections normally carried out manually, with benefits including better safety management and a more efficient way of working.  We are also improving our foundational technologies and data platform and as part of our continuous industrial process optimisation work.

Applying Machine Learning

One of our pilot manufacturing projects on the cutting edge of digitalisation came from applying Machine Learning using historical process and quality data from our Bayway Dispersant Unit. The application of Machine Learning algorithms to large-scale Infineum datasets has the potential to uncover previously unknown relationships that would otherwise remain hidden. The knowledge developed by uncovering these patterns can be employed to drive cost minimisation, process optimisation, capacity improvements and reliability on our Manufacturing Plants.

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