Application analysis
Evaluation of product characteristics, operating conditions and control objectives to identify the most suitable solution.
Machine Vision
Advanced vision technologies to control, recognize and guide production processes, transforming images and visual data into reliable operational information.
Overview
Acquire information directly from the product and process.
Machine Vision Systems use industrial cameras and image-processing software to acquire information for production-process control.
Unlike traditional sensors, which detect a limited number of parameters, a vision system is able to analyze shape, position, dimensions, presence of components, markings and characteristics of the product.
Machine Vision is used for quality control, identification, traceability, robot guidance and in-process verification across the manufacturing process.
Skills
What we can
offer
Lighting study
Definition of the lighting conditions necessary to ensure reliable and repeatable images.
Development of vision applications
Creation of control, identification, measurement and verification logics according to the specific needs of the process.
Integration with robots and automation
Connection of vision systems with PLC, robots, supervision and field devices to make the information acquired an integral part of the production process.
Commissioning and support
Testing, performance optimization and support during the plant start-up phases.
Focus
Main aspects
Automatic verification of product conformity by checking dimensional characteristics, presence of components, assemblies and visible defects.
Reading of barcodes, Datamatrix, QR Codes and markings for managing traceability and connection with company systems.
Identification of the position and orientation of products to allow the robot to automatically adapt its operations.
Verification of dimensions, distances, alignments and geometric tolerances during the production process.
Selection of the most suitable technology depending on the application, using two-dimensional images or three-dimensional systems to acquire the necessary information.
Each application requires the definition of specific algorithms and control criteria to correctly distinguish compliant and non-compliant products.
In some traditional applications, image-processing techniques can deliver reliable, easily interpretable results.
When control becomes more complex and rules are difficult to define in a deterministic way, it is possible to use tools based on Artificial Intelligence and Deep Learning to support advanced classification and recognition activities.
Artificial Intelligence represents a technology available among the different possible options and is used when it offers a real advantage for the specific application.
When control becomes more complex and rules are difficult to define in a deterministic way, it is possible to use tools based on Artificial Intelligence and Deep Learning to support advanced classification and recognition activities.
Artificial Intelligence represents a technology available among the different possible options and is used when it offers a real advantage for the specific application.
LET'S GET STARTED