What are typical applications of Machine Vision in Industry?
In the manufacturing industry, machine vision systems comprise sophisticated cameras, optics, lighting and algorithms. These components collaborate to capture and process images for diverse applications, acting as a constant overseer of the production process.
The use of machine vision technology in the manufacturing sector is widespread. Since its introduction in the 1980s, the advancement of the technology and its take up has been continuous. It is now common to see vision systems in the production process, indeed they form an integral and critical element of it.
Machine Vision plays a pivotal role in quality assurance
Utilising high speed cameras and complex image processing algorithms, these systems identify product defects and irregularities with remarkable accuracy and speed. Visualise a process producing many products a second; it is not feasible for a human to inspect each and every part to ensure the label is correctly applied, that all fastenings are in place, that the right components are correctly fitted and so on. Either the process must be slowed to allow the human the time to keep up, the quality standard must be reduced, or multiple humans must be employed to perform the task, thus increasing the production cost of the product. It is in this scenario that Machine Vision systems come into their own as they have the ability to apply the same criteria, time and time again, at very high speed, therefore reducing cost, increasing throughput and ensuring quality.
Vision System Verifies correct fitting of bottle cap
Guidance and Positioning
The drive to automate production processes has resulted in a great increase in the take-up of robots and other motion systems. Machine Vision systems are essential for directing these systems. Machine vision systems accurately identify the position and orientation of parts. This precision is vital for tasks such as assembly, welding, and packaging, enhancing accuracy, reducing waste, and improving efficiency. Imagine a scenario whereby a wheel is to be lifted off a conveyor, by a robot, and fitted onto the axle hub of a car; a secondary robot will then fit the bolts through the wheel into the axle hub. It is therefore essential that the holes in the wheel align with the holes in the axle hub. A vision system would enable this by determining the orientation of the wheel on the conveyor and feeding this to the robot, therefore allowing the robot to correctly orientate the wheel before fitting it to the hub. In effect the vision system gives the motion system the power of sight.
Non-Contact Measurement
Machine vision is increasingly used as a non-contact measurement device in various industries for precise, efficient dimensional analysis. For example, in electronics manufacturing, machine vision systems are employed to measure the dimensions of components like circuit boards. High-resolution cameras capture images of the parts as they pass on the conveyor. Advanced image processing algorithms then analyse these images, measuring dimensions such as length, width, and height with high accuracy. This non-contact method allows for rapid, consistent measurements without risking damage to delicate parts. Such systems are crucial for ensuring quality control, verifying that components meet strict specifications before assembly or shipping.
Barcode Reading and Tracking
In the logistics industry, barcode reading applications are vital for streamlining operations and ensuring efficiency. These systems use optical scanners or cameras to read barcodes on packages, instantly retrieving and processing data about the item. This automated process reduces human error, speeds up sorting, and tracking of goods, and enhances inventory management. The data collected from barcodes integrates seamlessly with supply chain management systems, enabling real-time tracking and improved decision-making. This technology is essential in warehouses, distribution centres, and during transportation, ensuring that goods are accurately logged, monitored, and delivered on time.
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A machine Vision system processes 3D data and identifies the location and of holes in a machined surface.
3D Measurement
Advanced machine vision systems are capable of conducting precise 3D measurements. In the manufacture of orthopaedics, for example, 3D machine vision plays a crucial role in producing precision medical implants, such as knee or hip joints. These systems use advanced cameras and sensors to create detailed three-dimensional images of the implants during production. This allows for highly accurate measurements of complex geometries and surfaces, essential for ensuring the implants fit perfectly with human anatomy. The 3D data collected assists in verifying dimensions, detecting surface irregularities, and ensuring the overall quality of the implants. By implementing 3D machine vision, manufacturers can achieve higher precision, reduce errors, and ensure that their products meet stringent medical standards, ultimately leading to better patient outcomes.
There are many, many other applications of machine vision technology. Very many of these are commonplace and mature, the examples above are not intended to form an exhaustive list but to give an initial understanding as to the capability and benefits of Machine Vision in the manufacturing industry.
In summary these can be said to be :
Increased Efficiency and Productivity: These systems operate continuously, offering consistent performance and significantly enhancing production process efficiency.
Improved Product Quality: Machine vision's precision in defect detection exceeds human capabilities, leading to marked improvements in product quality.
Cost Reduction: By minimising defects and enhancing process efficiency, machine vision leads to substantial cost savings and reduces the need for manual inspections.
Enhanced Flexibility: These systems can be reconfigured for various applications within manufacturing, demonstrating versatility.
Data Collection and Analysis: Machine vision systems provide valuable data for process improvement, maintenance prediction, and informed decision-making.
As with all technology, the deployment of machine vision does not come without its challenges. These are discussed in length in other articles on this site, some items to consider are summarised below.
Complexity of Implementation: Tailoring machine vision systems to specific manufacturing processes requires meticulous planning and expertise. A system assuring quality is a system upon which the manufacture must depend. Whilst the capability of the technology is not in question, any application will be dependent upon the quality of its engineering and deployment to realise this.
Lighting and Environmental Conditions: A vision system is an optical system and its effectiveness is therefore contingent on the information within the image it acquires. Optimal lighting and the control of environmental conditions are key factors in ensuring repeatable robust performance.
Cost of Implementation: While initial implementation costs can be substantial, they are often offset by long-term benefits.
Integration with Existing Systems: Merging machine vision systems with current manufacturing processes and machinery demands technical expertise.
In summary, Machine vision has, and continues to, revolutionise the manufacturing sector by offering unparalleled precision, efficiency, and flexibility. As technology advances, the potential applications and benefits of the technology will continue to grow. It is not merely an automation tool but a transformative force in manufacturing, driving quality, efficiency, and innovation.