Machine vision product research: Positive attitudes, outlooks, new products

2008 machine vision research results and advice from survey takers follows, along with links to 16 machine vision products and the machine vision online resource guide.


Machine vision trends and technologies Control Engineering North American print edition Product Research article, “


Machine Vision Eyes a Healthy Tomorrow

” show increased interest and investment in machine vision products. Additional machine vision research results and advice from survey takers follows, along with links to more machine vision product information and the machine vision online resource guide, below.


Machine vision system lighting is among the largest challenges, survey respondents said. This image is from Banner Lighting Solutions.
Machine vision system lighting is among the largest challenges, survey respondents said. This image is from Banner Lighting Solutions.

Overall, the latest machine vision survey projects healthy spending levels for vision systems over the next 12 months, and an interest in systems that are easy to install and use. Less than half of all respondents (48%) are concerned that machine vision is too complex or costly to implement. When asked about forces that limit the use of machine vision, only 7% said understanding the technology was a factor. When asked to advise others about vision systems based on their experiences, respondents repeatedly said pay attention to the lighting, some calling it “the largest issue.”
Within the next year, a solid majority can be expected to be using a vision system integrator for installation assistance. Slightly more than a third (38%) said they currently use an integrator. Of the 63% who do not now use an integrator, nearly 22% said that they plan to do so in the next 12 months.
Diversity among network protocols used for machine vision systems appears to be increasing. USB has enjoyed significant growth since the previous study, surpassing a declining “proprietary” as the most popular network choice. Gigabit Ethernet and Camera Link have also gained ground. One respondent now using GigE went so far as to recommend users “stay away from proprietary interfaces.”
Almost half of all respondents (47%) indicate they have used smart vision sensors. Of that number, more than three-quarters said the smart vision sensors met their requirements. Opinions shared by respondents about these devices indicate an acceptance of smart sensors in some applications, such as identifying objects and their location, and checking parts assemblies. However, respondents also noted limitations of smart vision sensors in some areas, including speed and field of view.
Applications, features, consistency
Some 70% of the survey respondents said they were involved in specifying, recommending, and/or buying machine vision products. About 70% of that number did so for in-plant requirements, with about 20% using them for OEM (resale) requirements and the remaining 10% using them for both types of applications.
Applications were grouped into three primary areas: motion control, quality control (QC) inspection, and product identification (see bar chart). Among specific activities, respondents said they used machine vision products most of all for barcode applications (90%). Also at the top of the list were robot motion control (at 78%), product inspection (at 73%), and assembly guidance (at 72%). The results mirror, in large part, previous survey results which place the same applications at the top, but with robot motion control in the fourth spot. Rounding out the most popular applications this time around are assembly inspection (at 70%), packaging inspection (at 56%), character (also at 56%), print quality and readability (at 52%), and moving vehicle automation (at 15%).
Performance and ease of use also continue to be the features most respondents want in a machine vision system. Nearly all respondents call these factors important or very important, as they had in the earlier study. Ease of set-up is not far behind, and price and technical support round out the top five features identified as important or very important. Compared to the previous study, technical support appears not quite as critical as it had been, dropping from third to a tie for fourth in order of importance. Price joins technical support in the fourth spot tie, rising from sixth place in 2007. Complete solution (including software) falls to seventh place. It was fifth in the previous survey.
Proprietary networks falter
Investigating current and future use of network protocols, the survey revealed some changes in the choice of networks used with machine vision systems. Asked specifically about their use of five networks—USB, FireWire (IEEE 1394), Camera Link, Gigabit Ethernet, and proprietary—61 % of those responding said they used USB (up from 49% in the previous study). Although 9% of that total said they plan to discontinue using the network within the next 12 months, among those stating they did not now use USB, 17% said they planned to implement it in the next 12 months.
A solid majority (56%) now use Gigabit Ethernet, while another 26% say will be implementing it in the next 12 months.
More than half of the respondents (52%) also said they used Camera Link, with another 12% planning to use it in the next 12 months. Only 44% of those responding report they use a proprietary network for the machine vision applications (compared to 58% in the 2007 survey), and only a small number (9%) said they planned to use one in the next 12 months. Nearly half said they did not use a proprietary network and did not plan to adopt one in the next 12 months. Only 35% said they use FireWire, while 17% of those not now using it said they plan to implement it within the next 12 months. A small number of respondents (18%) said they were using a protocol other than those named. Among the others mentioned were 100 MB Ethernet and Serial RS-232/485. Responses total more than 100% due to use of multiple protocols.
Steady, solid growth
The outlook for purchasing machine vision products over the next 12 months is bright, showing just 7% of respondents expecting a decline in spending (see accompanying pie chart). A significant 93% anticipate spending will remain the same (52%) or grow (41%) during that time. Factors most limiting the use of machine vision include the capital budget (38%), engineering resources (16%), priority relative to other automation projects (13%), acceptance by factory personnel (11%), and understanding of vision technology (7%).

Nearly half of the respondents (46%) have purchased between 1 and 4 units over the past 12 months. Perhaps more significantly, close to a fifth (17%) have bought more than 15 units. Spending levels concentrated in the $20,000 to $50,000 range (20%). Some 65% of respondents bought machine vision products and systems worth $5,000 to $200,000.
For those seeking to invest in machine vision products and systems in the near term, advice is abundant, if not obvious. Subscribers caution to consider the environment in which the system will be used, have a thorough understanding of the application, select equipment that is easy to use, ensure the availability of adequate support. But one word surfaces every time, through it all: lighting.


Illumination products from Banner Engineering include configurations in five color options with an array of filters, diffusers, and mounting systems.
Illumination products from Banner Engineering

Don’t overlook lighting!
Universally, respondents warn: “Pay attention to the lighting.” “Proper lighting is the largest issue.” “Two words: lighting and lenses.” “Correct lighting is critical.” “For effective applications, you must pay attention to proper lighting, lenses, and information coordination.” “Consistent lighting will yield the best and most consistent results.”
One respondent explains it this way: “Make sure you pay special attention to your lights. Never take machine vision lighting for granted. Your lighting is more likely to degrade over time than the camera itself and it can make or break a system.” Says another, “It’s all about lighting. The human eye is a bad judge of what‘good’ light is. You have to see the lighting from the camera sensor’s perspective.” 
The foundation of machine vision is lighting, concludes one respondent. “When designing a project, don’t spend all your time researching cameras and optics. Spending the time upfront to make sure you have the proper lighting for your application will pay off tenfold in the end.”


16 machine vision products: Cognex, Banner Engineering, Keyence, National Instruments, Omron Electronics, Sick, and more

Cognex In-Sight Micro

Banner Engineering machine vision illumination products

CV-3000 vision system, Keyence Corp. of America

NI 1744, NI 1762, NI 1764 smart cameras, National Instruments

Omron Electronics ZFX machine vision sensor

Sick Inspector Vision Sensor finds defects

HawkEye 1600T camera, Microscan Systems

Matrox Design Assistant 2.0 software from Matrox Imaging

Phantom Miro: crash tests, assembly line, Vision Research

Genie C1410 and M1410, GigE vision-compliant, Dalsa

Optical Character Verifier 2, Systech International

5 MP progressive scan camera, digital interface, Jai Inc.

Impact Software Suite, v. 8.0, PPT Vision Inc.

CleverDragon high-speed machine vision, Toshiba Teli America

Castell QuadCam 3D safety zone system

PV500, Panasonic Electric Works Corp. of America

– Edited by Jeanine Katzel , consulting editor
Control Engineering
Register here .


Machine vision online resource guide

Machine Vision Comes of Age

How should control engineers use machine vision?

On Track with Machine Vision for application examples

Machine Vision: Now is the Time (Product Research article, products)

Machine Vision Product Research May 2007 (Survey results in Resource Center; registration required)

Machine Vision: Not Just for Metrology Anymore (robotics applications)

Measure Up with Machine Vision (tricks and tips, references, setup hints)

Buyer’s guide search on machine vision

Automation Integrator Guide contains companies with machine vision expertise .

Latest Control Engineering products, news, articles on machine vision

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