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Smart Production

Automation, Digitalization, and Artificial Intelligence for a More Efficient Industry

Collaborative Robotics to increase safety and efficiency in production lines
Additive Manufacturing to reduce waste and create customized components
Monitoring and Control to optimize production and improve quality
Energy Efficiency to reduce consumption and optimize plant operations
Operator Assistance Systems to enhance ergonomics and workplace safety
Process Digital Twin to simulate and optimize production performance

Technologies and processes in this field

Find out more about how we work and the experience we have gained.

Collaborative Robotics
Additive Manufactuing
Monitoring and control
Energy efficiency and monitoring
Operator assistance systems
Digital twin process

Collaborative Robotics

Collaborative Robotics (or Cobotica) represents a revolution in industrial production, allowing robots to work side by side with operators in complete safety. Cobots are equipped with advanced sensors that detect contact with external objects, preventing accidents and improving workplace ergonomics. These robots can be easily programmed through a free drive mode, allowing for quick reconfiguration based on production line needs. Furthermore, their ability to support repetitive tasks and lifting operations reduces operator fatigue and increases overall efficiency.

Collaborative robotics
Cobot
Human-machine interaction

Additive Manufactuing

Additive Manufacturing, also known as 3D printing, is a revolutionary technology that allows the creation of objects by depositing successive layers of material. This method enables the production of components with complex geometries that would be impossible to achieve with traditional technologies. SLM (Selective Laser Melting) systems for metals and MJF (Multi Jet Fusion) systems for polymers allow the creation of strong, lightweight parts. Thanks to on-demand customization and reduced production waste, additive manufacturing represents a sustainable and efficient solution for Industry 4.0.

3D printing
Additive Manufactuing

Monitoring and control

Smart monitoring and control of production allow real-time collection and analysis of data from machines, assessing performance, consumption, and adherence to production targets. By using IoT sensors and predictive analytics algorithms, inefficiencies can be detected, and downtime reduced. Digital dashboards provide a comprehensive overview of production times, order progress, and production line performance. Integration with MES (Manufacturing Execution System) software enables tracking every stage of production, improving resource management and planning.

Smart Monitoring
Real-time analysis
Optimized production

Energy efficiency and monitoring

Smart monitoring and control of production allow real-time collection and analysis of data from machines, assessing performance, consumption, and adherence to production targets. By using IoT sensors and predictive analytics algorithms, inefficiencies can be detected, and downtime reduced. Digital dashboards provide a comprehensive overview of production times, order progress, and production line performance. Integration with MES (Manufacturing Execution System) software enables tracking every stage of production, improving resource management and planning.

Energy monitoring
Smart Dashboards
Energy management

Operator assistance systems

Operator assistance systems improve human-machine interaction through advanced technologies that enhance safety and efficiency. Augmented reality, used through smart glasses and fixed cameras, guides operators in assembly and maintenance processes by providing visual instructions and reducing errors. Exoskeletons and cobots assist operators in physically demanding tasks, reducing physical strain and improving workplace ergonomics. These tools are essential for increasing productivity, minimizing injuries, and fostering a safer and more efficient work environment.

Operator assistance
Exoskeletons
Augmented reality
Productivity
Security

Digital twin process

The digital twin process represents a virtual replica of the factory, used to simulate and optimize production in real-time. By integrating with IoT systems and advanced analytics, it allows for the prediction of plant performance and identification of bottlenecks in the production line. This model enables the simulation of alternative scenarios, optimization of energy consumption, and improvement of product quality. Additionally, the digital twin supports business decisions through cost and performance analysis, facilitating the planning of new investments.

Digital Twin
Performance analysis
Cost optimization