What is the Industrial Science of physical and dynamic couplings?

The industrial transformations of materials are based on a simple general physical principle: technical means make it possible to change materials, substances or materials from certain states to other states, with the aim of giving the final state specific characteristics, in terms of form, structure or functions.

For most products, these transformations take place over several so-called unit stages, using ingredients and materials most of the time in a mixture. In practice, these operations commonly pose difficulties, which regularly transform into problems impacting quality, development times, productivity or even innovation capabilities.

Empiricism, normative and science

Contrary to a widespread imagination, industrial practices are not all guided by the teachings of science. A large number of technical operations are in practice based on empiricism, ie trial-and-error approaches based essentially on the know-how and common sense of the teams to achieve results.

In addition, the Prescriptive measurement approaches, often standardized by industry, are far from consistently scientifically rigorous. Thus, they regularly induce serious biases to discriminate unambiguously between materials and products.

Unfortunately, these standards often constitute support methods in R&D for development, paradoxically maintaining the empiricism of industrialization and production practices.

Taking into account the couplings between materials and implementation at the heart of our Industrial Science

Faced with the numerous concrete problems induced by these practices, from R&D to production and application, industrialization, sizing, supply of inputs or marketing, RHEONIS has gradually developed an original methodology and methods to enable the implementation of cutting-edge scientific approaches adapted to the specific context of the problem and without the delays generally required by science.

The heart of our Industrial Science consists in taking into account and analyzing the physical and dynamic couplings between matter and its conditions of implementation, often invisible to measurement standards and considered indirectly by basic science techniques.

A pragmatic approach to the interfaces between various sciences and engineering approaches

If these couplings take on so much importance in the industrial processes of transformation of matter, it is because these transformations occur at different scales, spatial, temporal, energetic, and that the effective variabilities of kinetics, diffusion, gradients, may cause adverse effects.

Most problems showing up at mesoscopic and macroscopic scales, it is particularly relevant to work at these scales. Thus, depending on the issues, we mobilize knowledge and methods from the fields of physics (polymers, self-assembled structures, interfaces), rheology, mechanics, complex fluid mechanics, thermal, tribology, to shed light on industrial phenomena. Our diagnostic, experimental, measurement and statistical data processing approaches are resolutely scientific, whether it involves interpreting phenomena, modeling correlations or developing models.

We have thus developed our Industrial Phenomenology method, our Industrial Behavioral R&D approach, a unique understanding of the specificities of Behavioral Instrumental Techniques and an extraordinary practice of rheometry, practices linked to Smart-Data and systemic methods (SPIQI, TranZform) to support industries in their progress.

A resolutely industrial approach

Our approach is resolutely industrial, in the first place because it starts from concrete problems and comes back to them systematically, with elements of understanding, solutions, optimizations, suggestions, methods or tracks. In practice, this mobilizes our experience of industrial processes, technical issues, our knowledge of industrial methods, their limits and their biases, to design study approaches that maximize the chances of success while limiting deadlines and costs.

Therefore, all our approaches are systematically compared and tested against concrete data to ensure and adjust their operational relevance. This is how we develop robust predictive approaches that can be internalized by our Clients.

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Last Updated on February 16, 2023 by Vincent Billot