Machine vision is reshaping the global
manufacturing industry by helping companies create and generate
products that could not have been manufactured in previous eras.
Think of semiconductors as one example of a product that could not be
designed or manufactured in large quantities without the assistance
of automated microscopy, defect detection, and many more machine
vision-enabled production machines.
Machine vision also enhances existing
production processes, allowing trees to be more efficiently made into
lumber, saving the environment while providing necessary raw
materials, as well as cutting waste, rework and associated energy
consumption from manufactured products ranging from cars to
camcorders by identifying defects before a “bad” product passes
further down a manufacturing line. All of these accomplishments make
companies more efficient and productive, which in turn help them to
employ more people worldwide.
Today, using automation and machine
vision, companies are not forced to move all manufacturing to a
region of the world with the lowest labor cost. Around the globe,
machine vision is helping companies keep production next to customer
markets, allowing them to better respond to changing customer
demands, spread the wealth of employment, raise the standard of
living across all regions, and reduce the negative environmental
impact of shipping and logistics.
Will these benefits taper off, or
continue to increase? As recent developments reveal, advances in
machine vision technology that make machine vision systems more
efficient directly impact the productivity of the customer in a
mutually beneficial relationship that isn’t likely to disappear any
time soon.
Hardware Improvements for Hard
Returns
Machine vision automation allows
companies to produce more, faster, and at less cost than manual
operations. With this in mind, technological advances that make
machine vision systems faster and more powerful convey productivity
improvements to its users.
For example, recent work at the machine
vision’s North American trade association, AIA, helps machine
vision suppliers’ guidelines for improving system performance while
retaining the compatibility that is critical to a successful global
automation industry. Examples include the new USB3 Vision standard,
which followed close on the heels of the first USB 3.0 standard
release from the electronics industry; new Camera Link HS IP core
solutions that allow hardware designers to use common FPGA cores to
increase the bandwidth of one industry’s highest speed network
standards; and new pixel format naming conventions that further
increase compatibility among different hardware manufacturers through
the GigE Vision standard.
Machine vision suppliers are not afraid
to leverage developments from outside their industry and supporting
associations, too. For example, NorPix (Montreal, Quebec, Canada) a
provider of high-speed digital video recording solutions, recently
introduced a discreet hardware module for high-speed, high-quality
JPEG compression.
“We incorporated NVIDIA graphics
cards into the new module, and we’ve shown that now a single
computer can record video from 10 cameras simultaneously in high
definition at 30 frames per second,” explains NorPix President Luc
Nocente. “This allows you to record more cameras at once, or fewer
cameras for longer periods of time without buying a huge computer.
Our customers from pharmaceuticals to paper mills use these solutions
to video high-speed processes, either before fielding a machine
vision system or after fielding the system. In both cases, the video
helps them to understand where defects originate and to design a
solution. The ability to put multiple cameras around a piece of
production equipment and slow down the process in video is crucial to
helping our customers understand how they can improve their process,
or improve the performance of an existing machine vision
quality-assurance system.”
Recently, the Imaging Solutions Group
(Fairport, New York), a specialist in custom camera and imaging
solutions, delivers on-cameras FPGAs to enhance automated fluorescent
systems used in medical screening and drug discovery as well as
multi-spectral imaging systems for checking agricultural crop
health.
“By utilizing unique functions found
in Imaging
Solution Group cameras, companies that make automated fluorescent
microscopes and screening machines can operate faster and complete an
automated inspection in a shorter period of time,” explains Kerry
Van Iseghem, co-founder of Imaging
Solution Group. “ISG LightWise smart cameras can integrate
imaging algorithms to detect and count fluorescent results within an
image and keep track of results without the need for PC involvement.
Multi-Spectral Imaging Systems can be optimized via Imaging
Solution Group LightWise Smart cameras. By utilizing on-board CPU
and FPGA’s along with large image buffers, unique algorithms can be
used to optimize Multi-Spectral Imaging Systems. For instance,
agricultural applications can use multi-spectral techniques to
determine moisture and plant growth quickly with smart cameras.”
Everything Doesn’t Have to Be
Hard
Running a production line faster is one
easy way to measure productivity enhancements, but machine vision
technologies are spreading beyond traditional manufacturing
industries.
“Of course, the default definition is
ROI [return on investment], or increasing throughput,” explains
Michael Cyros, chief commercial officer at Allied Vision Technologies
(Newburyport, Massachusetts). “But there are many other points
about productivity that I like to consider. For example, providing
enhanced-quality images to the doctor, aiding sportscasters and TV
viewers with clearer images combined with scene tracking, guiding a
surgeon more accurately, helping ensure that a customer is happy with
the exact fit of their new glasses, and on and on. So, ‘increased
productivity’ has a much wider meaning for me than the traditional
definitions of the measurement of productivity.
“The main point I wanted to make is
that ‘productivity’ improvements aren’t just related to a
quantifiable or clearly objective measurement. There is also a very
large area for subjective interpretation of ‘productivity,’ and
this is where the non-industrial application markets really benefit
from ‘productivity’ enhancements,” Cyros said.
How does using machine
vision system for golf swing analysis increase productivity? “Is
it helping a player become more ‘productive’ in their game to
reach the hole in fewer shots?” Cyros asks. “No. The real answer
there is it helps the sales people in the golf pro supply shops make
more sales with less investment because the customer will already
know exactly what they’d like to purchase to improve their game and
overall experience. So, productivity must be measured also in very
subjective, as well as objective, terms.”
To know more about Imaging
Solution Group visit: http://www.mvrpl.com/
Contact us at:
Menzel Vision & Robotics Pvt Ltd
Address: 4, A-Wing, Bezzola Complex,
Sion Trombay Road, Chembur
400071 Mumbai, India
Tel:(+91) 22 67993158
Fax: (+91) 22 67993159
Mobile:+91 9323786005 / 9820143131
E-mail: info@mvrpl.com
Website: http://www.mvrpl.com/
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