As massive leaps forward in technology advances the level of proficiency and competition in almost every industrial sector, industries are fast harnessing the power of cutting-edge technology to stay in the race.
In effect, Artificial Intelligence and Machine Vision are two such technologies rapidly transforming various industrial sectors. As a result, AI-powered machine vision systems are taking their place in sensitive industries such as the electronic design and manufacturing industries and are set about building up stronger digital economies.
In this piece, we examine the world of AI-powered vision and how design companies are advancing the design and manufacturing industries with the power of AI.
Arshon is utilizing AI-powered Machine Vision in 6 ways to Advance Electronic Design and Manufacturing as followings:
- Real-Time Tracking
One great way of meeting with constant demands and staying in form is to keep track of subsequent projects of current customers. Keeping track of assets allows room for inventory management alongside efficiency in operations.
However, as noted in present systems and due to increase in tasks, real-time tracking is not as efficient as it should be. AI-enabled machine vision is designed to enable manufacturing and design companies to control real-time tracking of projects even in their most discrete stages.
In effect, machine vision systems enabled by Artificial Intelligence plays an important role in providing key data management functionalities to enhance the tracking and matching capabilities of existing systems.
Design and manufacturing involve numerous details. Circuit boards, for instance, are made up of quantum details which need careful analysis before assembling.
- Quality Control
Quality assessment and control is an integral part of manufacturing and design that in its element determines the integrity of a product. Machine vision systems help in this area by going through the intricacies of the design to verify the integrity of the products.
Most of these systems are capable of storing data and through checks over time, compare real-time data with the stored data to spot out even the minutest defects in design.
In effect, EMC (Electromagnetic Compatibility) testing used by Arshon Technology uses the spot-on power of AI-enabled machine vision to check the status of electronic devices.
- Visual Inspection
Much like with quality control, AI-enabled machine vision systems are equipped with the abilities to go through various designs and materials to pick out surface defects as well as the presence or absence of certain properties needed for manufacturing.
Visual Inspection gives manufacturing a better outlook by picking out properties such as color and matching it with an ideal condition or property already pre-learned. One peculiarity of machine vision systems is their capability for deep learning.
Hence, the applications of visual inspecting help companies save more time and cost on operations by spotting out defects on materials even before use. Not only does it give final products the outstanding results aimed at, but it also gives companies the leverage to advance in a competitive environment.
- Identification and Classification
As companies advance, data get more difficult to analyze and it is no news that every design and manufacturing company rely on a lot of data to make up their final products. Machine vision systems help companies through their deep learning capabilities to give more insight into logistics by identification and classification.
These days, Machine vision-enabled systems are trained to identify parts or packages by using optical character recognition functionalities to pick out texts. Some are trained to scan through bar codes, shapes, sizes or colors for identification and further classification. Arshon Technology and similar organizations leverage machine vision to identify and classify the materials needed for design and manufacturing.
- Metrology
Metrology is one of the most essential parts of sensitive companies such as electronic design companies as well as the manufacturing industry as a whole. Precision and accuracy is needed in standard measurements before production.
PCB designs, FPGA based system designs and other industrial designs require measures of accuracy and precision before moving on to manufacturing stages.
AI systems enabled with machine vision provides direct help in these sections. Sufficient growth in these areas has seen companies use 3D-imageries and machine vision-analyzed data to ascertain the precise and accurate data needed for measurements.
- Predictive Maintenance
For years, the manufacturing industry at large has harnessed the power of traditional preventive maintenance for due control and assessment on the performance of their equipment. However, applications of these measures required lots of manual data analysis.
AI-enabled systems are designed to harness the power of machine vision to affect the predictive maintenance of machines. Through this, manufacturers are able to identify defects in their machines and analyze volumes of information better.
In effect, this allows manufacturers to identify the full potential and optimal performance of existing machinery while averting downtime and likely hazards due to faults.
AI Systems Leading the Way to a Revolution
Huge advancements in the global industrial sector have subsequently raised the bar for companies in terms of competition and efficiency hence, the race towards advanced technologies.
In a bid to meet up with constant demands, newer technologies are being developed and adopted to surpass the limitations of older systems. For companies within the manufacturing and design industries, Artificial Intelligence and machine vision systems are powerful tools to have in hand for being part of the next revolution.
The adoption of AI systems is already growing at a significant rate and is bound to be one of the key technologies to be sought after the most in the future.
As a fact, companies are harnessing the functionalities of AI-enabled machine vision and implementing it to achieve operational efficiency and improve their product quality robustness.
