A better view: Technology improvements make vision systems viable production tools

Prudent use of machine vision systems can reduce the overall need for human labor, which is a critical cost factor in developed countries. Quality control processes that currently rely on human intervention also can be error-proofed by switching certain functions to machine vision systems.


Prudent use of machine vision systems can reduce the overall need for human labor, which is a critical cost factor in developed countries. Quality control processes that currently rely on human intervention also can be error-proofed by switching certain functions to machine vision systems.
These are a few of the observations contained in a report titled Advances in Machine Vision Systems, issued by the Technical Insights research arm of Frost & Sullivan .
The report provides a technology overview and outlook for the machine vision systems industry. It covers architectures by which vision systems are built, machine vision cameras, advanced imaging and image processing techniques, infrared imaging, robotics, and artificial intelligence and vision. This report is based on detailed analysis of technology and industry trends following extensive interviews with market participants.
Frost & Sullivan says machine vision systems are becoming more practical in manufacturing settings because they now incorporate user-friendly features that minimize operator training thereby resulting in considerable cost benefits for the end user. As quality expectations continue to rise, the implementation of machine vision systems appears inevitable.
Additionally, the regulatory compliance standards in the food and pharmaceutical industries drive the advancement of machine vision technologies. Overall, the prevention of liability due to defective products makes the deployment of vision systems very attractive.
“Machine vision systems are increasingly used for complex factory applications due to advancements in machine vision components such as cameras, illumination systems, processors, and imaging techniques,” notes Frost & Sullivan Research Analyst Vishnu Sivadevan. “Experience gained in solving challenging inspection tasks enables machine vision integration to progress further.”
However, due to the availability of low-cost labor in developing economies, machine vision systems remain confined to high-end or large-scale manufacturers as they represent a significant cost for small-scale and medium-scale manufacturers. On the operational level, vision systems entail a high cost of development and deployment while posing challenges for future upgrades.
Vision systemsecifications of inspected products.
“Pre-deployment costs and cost of ownership are major factors that must be considered to ensure a high return-on-investment,” notes Sivadevan.
“Continuous maintenance and operator training support are essential for high-end machine vision systems.”
Apart from cost-effective deployment, maintenance, and upgradeability of machine vision systems, integrators must cater to the rapid changes in manufacturing environments by providing continuous support for end users’ evolving needs.
Currently, machine vision enables core application areas such as semiconductor manufacturing inspection processes. The number of potential applications for machine vision continues to increase with the rate of innovation.

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