Success cases

Quick Urban Forestation

Quick Urban Forestation

Solution:

Cesefor coordinated the Life+ Quick Urban Forestation project, which was carried out in collaboration with IClaves SL and SDL Medio Ambiente, and with the Valladolid City Council. Its main objective was to create an experimental urban forest in the city of Valladolid. The aim of the experiment was to test different techniques for planting native species in an effort to grow an urban forest which would not require irrigation in the heat of the summer. Nearly 15,000 trees have been planted, a network of monitoring and information analysis has been deployed in order to obtain information about the temperature and humidity in the roots and on the surface, and to observe the behaviour of the plants' stems. The data obtained from sensors was processed and a survival analysis was conducted to study the results of the experiment.  Plant data was extracted every 30 minutes during 2 and a half years, the dataset that has been generated as a result of the project is available in open data formats on the project's website.

Maintenance 4.0

Intelligent and predictive maintenance management in production systems

Solution:

This project aims to develop an integrated and intelligent solution for optimal industrial maintenance, that will improve, according to the principles of Industry 4.0, the performance of production processes. To this end, the following aspects are considered: (i) advanced online analysis of the collected data in order to monitor and detect premature failures in the machines that operate on the production plant and, consequently, the need for maintenance interventions, and (ii) support to technicians during maintenance interventions through an intelligent decision support system, contributing to a faster and more effective recovery from any failure that may have occurred.

Deep cyberbullying analytics

Deep cyberbullying analytics

Solution:

A cognitive engine for the detection and prevention of cyberbullying on the Internet. Applies Artificial Intelligence and Data Analytics technologies to build graphs and social interaction models on the basis of Big Data, automating and facilitating the tasks associated with the timely prevention, detection and suppression of cyberbullying in the workplace and at school, since information will be available from a variety of open sources such as Facebook, Twitter and LinkedIn.

People analytics

People analytics

Solution:

People Analytics Expert System. Applies Artificial Intelligence and Big Data techniques to the information about people that is extracted from different public sources. Patterns are identified and profiles are elaborated to help gain greater knowledge about people and predict their behaviour. This enables the system users to make decisions on the basis of objective data.

GO0D MAN

aGent Oriented Zero Defect Multi-stage mANufacturing

Solution:

The project aims the development of Zero-Defect Manufacturing (ZDM) strategies in multi-stage production systems, through the integration of quality control and process control using cyber-physical systems, intelligent inspection systems and advanced data analysis tools. As result, it will be possible the earlier and real-time deviations and patterns, and consequently to avoid the occurrence of defects in the stations and their propagation to posterior processes.

GRACE

Integration of Process and Quality Control Using Multi-agent Technology

Solution:

Development of distributed production control systems integrating process and quality control levels using multi-agent systems principles and self-adaptation procedures to support variation and fluctuation in processes and products.

ARUM

Adaptive Production Management

Solution:

Development of mechanisms focusing the achievement of faster and more adaptive ramp-up processes using multi-agent systems.

PERFoRM

Production harmonizEd Reconfiguration of Flexible Robots and Machinery

Solution:

Conceptual transformation of existing Production Systems towards plug&produce production systems to achieve flexible manufacturing environments based on rapid and seamless reconfiguration of machinery and robots as response to operational or business events.

The design of Vitartis' 4.0

The design of Vitartis' 4.0 strategy for the agro-food sector in Castile and Leon

Solution:

The objective of the project, carried out in 2016, was to perform an Industry 4.0 diagnostic for several of Vitartis' partner companies. The diagnosis considered several areas: processes and technologies, human resources, market, communication and business model.

In the design phase of the strategy, the analysed data was integrated and compared with the data obtained in other studies and reports. The results showed the degree to which the agro-food companies in Castile and Leon were exploiting the benefits offered by 4.0 technologies. This made it possible to draw up a series of measures to be implemented by the AEI (Spanish State Research Agency) in the field of Industry 4.0.

DiASpORA4.0

The development of Automated Simulation Models based on Industry 4.0 for the Agrifood Industry.

Solution:

The objective of this project, conducted in 2017 and 2018, was to develop digital models to simulate three production processes, which the participating industries had identified as critical. To do this, a series of variables were identified (cycle time, raw material supply times, goods delivery times, the times between machine breakdown or the level of an intermediate stock) and were analysed in a simulated environment that resembled a real setting. 

The simulation of the digital twin achieved a hybridisation of the physical and digital worlds by including, in the model, real data from the process. As a result, a digital model has been developed which is capable of predicting the behaviour of the physical model and of modifying it according to the established optimisation objectives.

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