Smart Production
Automation, Digitalization, and Artificial Intelligence for a More Efficient Industry
Automation, Digitalization, and Artificial Intelligence for a More Efficient Industry
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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.
Cobots support operators in strenuous tasks, improving safety and well-being at work.
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.
The FDM 3D printer creates complex prototypes at low cost, making it ideal for testing and rapid development.
The MJF 3D printer produces complex and functional components, optimizing time and production processes.
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 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.
A device monitors and optimizes the energy consumption of an industrial line, improving energy efficiency.
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.
The Pick to Light system optimizes picking and inventory management, reducing errors.
The interactive station guides the operator with projections, reducing errors and optimizing training and efficiency.
Exoskeletons reduce physical strain and improve posture, safety and ergonomics during work.
Smart glasses support maintenance, training and logistics through augmented reality.
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.
The semi-automated process is simulated with a digital twin to optimize design and production.