Circular Economy
Ecoinnovation and valorization of industrial and agri-food wastes
Circular Economy
In the Circular Economy area, we help our clients to find new opportunities for their waste and industrial by-products. A waste can cease to be considered a problem and become a useful part of another production process, i.e. it can have a second life. This is known as the Circular Economy and is based on the principle of “closing the life cycle” of products. All industries have a great challenge ahead, the management of their waste to reach zero waste. In ATRIA we help our customers to achieve this goal through different methods and new technologies.
In the Circular Economy area, we help our clients to find new opportunities for their waste and industrial by-products. A waste can cease to be considered a problem and become a useful part of another production process, i.e. it can have a second life. This is known as the Circular Economy and is based on the principle of “closing the life cycle” of products. All industries have a great challenge ahead, the management of their waste to reach zero waste. In ATRIA we help our customers to achieve this goal through different methods and new technologies.
New opportunities for by-products
One of the big questions in the Circular Economy is: What do I do with this waste or by-product? At ATRIA we take care of answering each particular case. To do this, we characterize the waste or by-product and look for innovative solutions, either to reintroduce it into a new production process, or to treat it with a method that increases its value. At ATRIA we differentiate waste and by-products into 2 large groups:
Food Industry waste
These wastes, being organic, can lose their properties if they are not properly managed. For example, washing water, fruit residues, beet molasses, microalgae, etc.
Industrial waste
They are usually inert. For example, ashes, polymers, sulfur, electronics, metals, etc.
Steps to follow
Case study and analysis
To determine where or what a waste or by-product can be used for, it is necessary to know its composition and properties. Therefore, first of all, it is necessary to perform a characterization and analysis of the chemical composition in order to evaluate it.
Selection of the valorization technology
We look for applications and identify opportunities and make a diagnosis of the possible ways of valorization. We study the transformation process or the adaptation of technology to reintroduce the waste into the value chain.
Testing and prototyping
In many cases it is necessary to adapt the material. In our laboratory, we carry out concept tests, demonstrators and prototypes to check that the valorized product is suitable and meets the necessary requirements.
Industry integration
Once the laboratory scale valorization has been performed, it is necessary to design the industrial extraction process to be carried out. Our engineers can carry out the selection of the industrial equipment, the design of the plant and all the necessary process.
Synergies. Do you need a partner?
We help you to establish collaborations and synergies in the search for business partners, suppliers and potential customers for whom it would be beneficial to incorporate these wastes into their production process.
Improvements in recycling processes through industry 4.0
Digital transformation is the present. Technologies such as vision, deep learning or robotics are capable of promoting the use of resources, greater control and monitoring of them, thus boosting the circular economy.
Physical characterization of materials
Through technologies such as spectroscopy, algorithms and IoT we achieve systems for measuring the physical characteristics and composition of different materials.
Optical separation
The sensors and robotics we use in the area of Industry 4.0 are used to classify materials. In this way, recycling is improved, avoiding intruders that could cause problems later on in the production lines.
Quality control of materials
In many cases, if by-products are recycled, it is important to control the quality of the materials and their purity.
How we work
Data collection
Any system that includes artificial vision and deep learning needs to start from an initial database, which can be data or images to create the classification algorithm.
Labeling and training
The previously collected data needs to be labeled to identify the study feature and classify it according to previously set categories. These data are trained to create a network capable of extracting these categories.
Evaluation
To evaluate the model, new images are taken from which a metric is obtained to qualify the performance. This stage is used to check how the model behaves in new situations.
Instalation
The system is installed in a real environment and the algorithm is evaluated. The algorithm is checked to ensure that it returns the necessary information according to the specific case.
