There are not many who realize that machine vision solutions and technologies are part of the basis of digitalization, since data collection for controlling production would be almost impossible without these intelligent sensors.
Production control is continuously evolving toward digitalization and self-direction. In recent years, digital tools, intelligent software applications and machine learning solutions have conquered a large portion of production control processes, and this development trend does not show signs of going down. However, there are not many who realize that machine vision solutions and technologies are part of the basis of digitalization, since data collection for controlling production would be almost impossible without these intelligent sensors. But what does machine vision actually mean and why is it a good idea for industrial companies to take an interest in it?
1. Machine vision has virtually unlimited areas of application
The rapidly evolving machine vision technology can be widely applied in different sectors. Microscopically accurate machine vision can be used to acquire real-time information from production and products, such as shapes, colors and surface structure. Imaging based on machine vision efficiently produces digital information that can be utilized in measuring, production control and analysis, quality control and optimization, etc.
Areas of application include:
- Web monitoring and control (for example, steel or paper web production lines)
- Product calculation and sorting in a process
- Code and mark scanning in production
- Ensuring traceability of materials
- Measurement and inspection tasks
- Assembly and handling of materials
- Quality assurance in assembly
2. Machine vision solutions bring efficiency and improve profitability
Running a production company is not simple but requires, above all, comprehensive control and optimization of a multidimensional entity. Good news is that machine vision can help solve several challenges at once and improve profitability, quality and efficiency of operations. With machine vision, it is possible to achieve a 10% production increase and reduce material losses by 25%–50%.
The production increase comes mainly from an increase in the production rate and improved efficiency. The production rate can be increased when items are produced and inspected at a multiple speed compared to the speed and accuracy of the human eye. In turn, machine vision reduces material loss when quality defects can be tackled in time and materials can be used as efficiently as possible. Cost savings are naturally also generated when human resources can be freed from, say, quality control tasks and used elsewhere.
3. Advanced machine vision solutions replace both the human eye and human decision-making
At its simplest, a machine vision system may consist of a camera that sends data to a computer for analysis. Likewise, a machine vision solution can mean a notably larger entity connected to production control, automation and robotics, running and optimizing the whole production virtually independently.
A combination of artificial intelligence and machine vision can also solve problems that would be too complicated to program in operating systems.
Along with technological development, various opportunities of artificial intelligence and machine learning are more and more often integrated into machine vision solutions. This allows automation and production control systems to exploit information collected by machine vision in a more efficient way than before thanks to algorithms of artificial intelligence that mine key figures from massive datasets to optimize and forecast activities. A combination of artificial intelligence and machine vision can also solve problems that would be too complicated to program in operating systems or otherwise too heavy and awkward to maintain with traditional machine vision solutions alone.
4. Investment in the design stage of a machine vision project pays off
At its smallest, a machine vision solution could include a compact smart camera only. However, a professional expert is necessary already in the early discussions to maximize the benefits of the solution for production improvement. Areas of application and items for improvement may be found in surprising places.
Since there is virtually an unlimited number of machine vision solutions and related areas of application, a machine vision project typically starts from a pre-analysis and design step, during which the measurement method to be used in the system is defined together with the customer. The scope of the system and technological choices are determined, in addition to the customer’s needs, based on the measurement conditions, for example. Lighting conditions, for instance, are one of the most critical aspects to consider when planning machine vision solutions. Often, it is also a good idea to test the measuring methods and devices selected for use on a real-world production line, as well as collect raw data for the software development.
The design step is the most important part of the deployment of a machine vision solution since, in addition to specifying the machine vision technology to apply and the requirements of the application, this step is used to identify the most cost-efficient and sensible way to implement the solution.
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