Resources

White Paper 1: Obtain the tools to lead your sector towards 4.0

Posted on:8 June 2023

The decarbonization of the industry appears today as a major challenge, both for economic, geopolitical, and environmental reasons. Energy renovation, use of renewable energies… what are the actions to be implemented to achieve this? How can industrial players be supported today?
To assist you in this transition, we have written the Dametis White Paper, in 3 chapters, so that you get the keys to guide your industry towards 4.0!

The drafting of this White Paper was made possible thanks to the Dametis experts.

Julian Aristizabal
Co-founder, CEO

Jeremy Barrais
Product Manager
Nicolas Duran
Co-founder CTO
Sébastien Papouin
Technical Director

Cyril Quemeneur
Energy Engineer

A. Memory and environmental intelligence

“If ‘the development of full artificial intelligence could spell the end of the human race’ (Stephen Hawking, 2014), intelligent software, on the other hand, can put an end to energy waste in the industry. For example, energy data involved in the production of a product – from mascara to cars to mashed potato sachets – far exceeds the storage and processing capacity of the human brain.

Naturally, professionals have therefore started by outsourcing their ‘energy memory’ to paper files and Excel spreadsheets. This is the case when an operator records meter readings on a printed form and files it away in a binder, before eventually a colleague transcribes, with more or less errors, this data onto a computer. The same externalized storage phenomenon occurs when various software programs lie dormant in a corner of the factory, keeping all kinds of data, especially energy-related, without doing anything with it.”

Environmental expertise in a software

A collaborative platform for environmental transition should ideally concentrate, in the hands of each user, the global human expertise in industrial environmental efficiency. To achieve this, it must be a true expert system.
“An expert system is an artificial intelligence (AI) computer tool designed to simulate the know-how of a specialist in a specific and well-defined field, by exploiting a certain amount of knowledge explicitly provided by domain experts.”

Environmental data 4.0 craftsmen.

A software must first collect, second by second, a large amount of data, wherever it may be: PLCs, ERP, MES, sensors, virtual sensors with algorithms…
And just as a carpenter studies his wood before working on it – is it sturdy, irregular, knotty…? – a software must “understand” its material (the data) before doing anything with it. Is the data erroneous (sensor drift, parameter error…) or correct?
To get the keys to guide your industry towards 4.0, click on the button below, and we will send you the first chapter of our White Paper.