The adoption of innovative technologies is a constant pursuit to improve the efficiency and quality of modern processes. Industrial computer vision is revolutionising and changing the way firms operate worldwide. But what exactly is industrial computer vision, and how can it transform industrial processes?
Imagine a scenario where machines can observe and detect information instantly, just as humans do. Industrial computer vision functions similarly to human vision, utilising industrial cameras and specialised software to capture and process images.
However, its true power lies in its ability to extract valuable information from these images using advanced algorithms. This approach allows companies to improve efficiency, increase productivity and elevate quality across a wide range of industrial processes.
In this article, we shall explore the key steps for industry to learn how to integrate advanced technologies such as computer vision. Discover how you can optimise efficiency, productivity and flexibility to be part of the radical change of the fourth industrial revolution.
How do industrial computer vision systems work?
Before understanding the entire implementation process, it is important to know the fundamental principles of industrial computer vision as a key AI tool for automation, inspection and quality control in industry.
- Image acquisition: The first step in industrial computer vision is to capture images of the industrial environment using digital cameras or specialised sensors. The quality and resolution of the images are critical for accurate results.
- Image preprocessing: Once the images are acquired, preprocessing is performed to improve their quality. This includes noise removal, contrast enhancement and lighting normalisation.
- Image segmentation: This step involves isolating objects of interest from the background. To identify the edges or boundaries of objects in the image. Accurate segmentation is crucial for subsequent recognition and analysis.
- Feature extraction: Relevant features of objects, such as size, shape, texture or colour intensity, are identified and extracted. Proper extraction of these features allows for accurate identification of objects.
- Recognition and classification: Using machine learning algorithms, the extracted features are compared with previously learned patterns or predefined models to identify and classify objects in the images.
- Control and decision making: The information obtained is used to control processes or make decisions in the industrial environment. It can activate robots, reject defective products or adjust production parameters.
- Interaction with the industrial environment: Industrial computer vision is not limited to processing images, but can also interact with the industrial environment. This interaction can be carried out through robots, actuators or control systems to manipulate objects, adjust parameters or perform actions in the real world.
Where to begin?
The first step in implementing industrial computer vision is to identify areas of your company that could benefit from this technology. For example, if you are a manufacturing company, you might consider implementing computer vision in the product inspection process to detect defects more efficiently.
Another example could be in the logistics industry, which wishes to improve efficiency in supply chain tracking by using computer vision to automatically identify and classify warehouse products.
Once these areas have been identified, the next step is to establish clear and measurable objectives for your computer vision project. For instance, if you are implementing computer vision in the product inspection process, one objective could be to reduce the number of defective products detected during inspection by 20% over the next six months.
Finally, define what improvements you expect to achieve in terms of efficiency, quality and safety. Setting these objectives will help you measure the success of your industrial computer vision project and justify the investment in this technology.
In search of the best option
With a wide range of tools and technologies available, firms can harness the power of industrial computer vision. Below, we shall mention some of the main tools and technologies available in the market:
Industrial cameras: The eyes of computer vision
Industrial cameras are essential for any computer vision system. They provide high-quality and reliable images, fundamental for accurate analysis. Some leading brands include:
- CCD cameras are ideal for low-light environments or rigorous demands, as they offer high light sensitivity and excellent image quality.
- CMOS cameras are ideal for high-performance applications, as they offer lower power consumption and higher processing speed than CCD cameras.
- Infrared (IR) cameras: allow viewing in low-light conditions or even in darkness, are useful for heat detection and quality control in low-light environments or even in total darkness.
- 3D cameras are perfect for robotics applications, augmented reality and 3D scanning, as they capture depth information along with heat data allowing the creation of three-dimensional models of the environment.
Vision sensors for industry
Vision sensors are compact tools that detect the presence or absence of specific objects or patterns. They are more economical than cameras and are ideal for simple inspection applications.
- Line sensors are ideal for detecting objects along a line, used in applications such as conveyor control and part detection in industrial processes.
- Array sensors are a cost-effective option for capturing two-dimensional images with moderate resolution. They are suitable for low-cost and low-complexity applications in industry.
- Time-of-flight (ToF) sensors are ideal for measuring the distance to an object using light pulses. They are widely used in obstacle detection and 3D mapping in industrial environments.
Computer vision software: The brain of industrial automation
Image processing software is essential in industrial computer vision as it allows for the analysis and extraction of valuable information from images captured by industrial cameras.
SofIA, AI assistant for businesses
SofIA is an AI tool designed to integrate all business systems and provide support in various areas of work within the company. With SofIA, you can easily acquire internal company knowledge and perform diverse roles, seamlessly delegating a variety of tasks. By integrating all of the company’s technological systems, SofIA can free employees from automatic tasks such as clocking in, inputting hours and managing projects.
It is specially designed to address confidentiality needs in companies by integrating directly with the client’s infrastructure, strengthening security by eliminating the need for external Internet connections. This reinforces our commitment to security, privacy and innovation.
OpenCV (Open Source Computer Vision Library)
This is a widely used open-source library in computer vision image processing. It offers a variety of algorithms for edge detection, object recognition and more. Its versatility and efficiency make it a popular choice for companies seeking affordable and flexible vision solutions.
Cognex VisionPro
VisionPro is an industrial vision software suite developed by Cognex, a leader in artificial vision solutions. This platform provides advanced tools for quality inspection, object recognition, barcode reading and many other industrial vision applications.
Computer Vision with Edge
Our highly efficient model architecture is designed to operate locally on Edge devices, significantly reducing latency and conserving bandwidth. This ensures optimal performance and reinforces data privacy and security, especially in environments with limited connectivity. By processing data at the source, we ensure fast and reliable performance without compromising information integrity.
We leverage powerful devices such as NVIDIA Jetson to process natural language and industrial computer vision in real-time.
Other industrial computer vision technologies
Leading machine learning platforms, such as TensorFlow and PyTorch, are essential in developing computer vision systems. These tools offer flexible and comprehensive environments for creating and deploying ML models, allowing companies to train neural networks to recognise patterns in visual data.
In addition to software, specialised hardware such as GPUs are optimised to perform highly parallel calculations and accelerate the training time of industrial computer vision models. NVIDIA Tensor Cores are also tools that allow companies to develop and deploy computer vision models efficiently and scalably, thus driving innovation and competitiveness in the industry.
Select the best partner for your industrial computer vision
In the process of implementing industrial computer vision in your company, it is crucial to seek and select a reliable and experienced provider in this field. This may mean looking for companies with solid experience in developing and implementing computer vision solutions for industry.
It is essential to consider the provider’s previous experience in projects similar to your needs. Review their success stories and clients to evaluate their level of satisfaction, thus ensuring effective implementation of your industrial computer vision projects. If you have more questions or are interested, contact us to speak with our team of experts in industrial computer vision solutions.
Time to act
After choosing the perfect hardware and software or provider for your project, at this stage, a prototype of the computer vision system is designed, adapted to the specific requirements of the industrial process. Industrial cameras and image processing software that best fit the system’s needs are selected.
Then, the system’s operating parameters are defined, such as image resolution, capture speed, and the image processing algorithms necessary for analysis.
Remember that the main objective of the prototype is to create an initial version of the system that allows for testing and adjustments before full implementation.
Validation in productive environments
Once the prototype is developed, exhaustive tests are carried out under real production conditions. This involves integrating the system into your production line or the industrial environment where it will be used.
During the tests, we evaluate how the system functions in real situations, focusing on the ability to detect, identify and classify objects or anomalies in the process. Afterwards, we collect detailed data on the system’s performance, including detection accuracy, processing speed and any problems or failures that may arise.
Finally, based on the test results, we make adjustments and improvements to the system, thus optimising its performance and efficiency.
Progressive implementation Project with Industrial computer vision
Implementing a pilot computer vision system involves the initial introduction of the system in a specific production line or area. During this phase, the performance of the pilot system is closely monitored and data is collected for subsequent analysis.
Following the pilot phase, a thorough evaluation of the system’s performance is carried out, comparing it with the established objectives. The collected data is analysed to determine if the system is meeting expectations, and adjustments and optimisations are made as necessary.
Finally, once the pilot system has demonstrated its effectiveness, it proceeds to full implementation across the entire operation. This involves deploying the computer vision solution in all relevant production lines or areas.
Stress-free integration
For stress-free integration, it is essential that vision systems adapt perfectly to existing ones. This involves ensuring that the new technology can connect seamlessly with the company’s systems already in use, such as production management systems.
Moreover, it is crucial to integrate the data generated by computer vision systems with other company management systems, such as inventory management systems or enterprise resource planning (ERP) systems.
This seamless integration ensures efficient communication between all systems, facilitating informed decision-making and process optimisation.
To change the game with industrial computer vision, it is necessary to change the business culture. It is fundamental to clearly communicate the benefits that computer vision will bring to the industry and the team. This includes highlighting how the technology can improve efficiency, product quality and customer satisfaction.
This is achieved by fostering a culture of innovation and adaptation, where new ideas are valued and promoted. By creating an environment conducive to innovation, the potential of industrial computer vision can be fully harnessed with a channel for transformation.
Monitoring and maintenance of computer vision
To ensure continuous and optimal functioning of the vision system, it is crucial to establish a continuous monitoring system. This involves implementing tools and processes that allow constant supervision of the system’s performance, identifying potential problems or failures, and taking corrective measures in a timely manner.
In addition to continuous monitoring, it is essential to perform regular maintenance and updates to the vision system. This includes activities such as cleaning and calibrating cameras, verifying the accuracy of image processing algorithms and updating software to incorporate improvements and corrections. Likewise, it allows for the prevention of potential problems and prolongs the useful life of the system, thus maximising the return on investment made in industrial computer vision.
8 Steps to implement industrial computer vision
Reflection: The future of industrial computer vision
The future of computer vision in the business realm is truly exciting. Each advancement in this technology provides us with new opportunities to improve efficiency, quality and safety in our industrial processes. However, to fully harness these benefits, we need to constantly evaluate our progress and make necessary adjustments along the way.
This constant evaluation allows us to not only identify areas for improvement, but also maximise the transformative potential of industrial computer vision in business. By adjusting our implementation according to the changing needs of the market and the industry itself, we can ensure that we stay ahead of the competition and offer products and services of the highest quality.
Moreover, it is crucial to plan future updates and improvements to remain at the forefront of innovation. By staying up to date with the latest trends and technologies in industrial computer vision, we demonstrate our commitment to progress and excellence in the sector. If you would like to find out how we can help, do not hesitate to speak with our team of experts. Finally, the future of computer vision is in our hands. It depends on our willingness to adapt, innovate, and lead in our field, ensuring continuous growth and sustainable success for our industry.
