Georgia Tech's Research Horizons magazine - Fall 2003
The Perfect Buns
Digital imaging system catches bad sandwich buns
by Gary Goettling
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An automated product-inspection prototype is under development by GTRI researchers working with Flowers Bakery in Villa Rica, Ga. Researchers are introducing continuous imaging technology to the large-scale production of sandwich buns for fast-food restaurants, which hold to exacting product specifications
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THE PERFECT BUN: That's one of the goals of an
automated product-inspection prototype under development by Georgia
Tech researchers working with Flowers Bakery in Villa Rica, Ga.
The first phase of the work is introducing continuous imaging technology
to the large-scale production of sandwich buns for fast-food restaurants,
which hold to exacting product specifications.
The fresh-baked buns are scanned by a digital camera as they move
along Flowers' production line. Items not measuring up in terms of
color, shape, seed distribution, size or other criteria are identified
by the computerized eye's imaging software and eventually removed
automatically from the conveyor.
The system concept is under development by engineers from the Georgia
Tech Research Institute's (GTRI) Food Processing Technology Division
in association with researchers from Georgia Tech's School of Electrical
and Computer Engineering (ECE) and BakeTech, a baking equipment manufacturer
in Tucker, Ga.
The project was made possible, in part, by funding from Georgia's
Traditional Industries Program for Food Processing, a 10-year-old
research and development program designed to improve the market competitiveness
of Georgia's food processing industry – the state's second-largest
employer. The Food Processing Advisory Council (FoodPAC) oversees
such state-funded research grants.
The computerized imaging system in development will automate the inspection
process at Flowers. Ultimately, the new approach will save money and
time by increasing yield and reducing waste, says Doug Britton, a
GTRI research engineer and co-principal investigator for the project.
"
It should reduce the time between noticing a problem and fixing it," Britton
explains. Also, the system will automatically record data, such as
product count and the number of out-of-spec buns, to generate production
reports. "Flowers will have all this data immediately for doing
statistical process control so they can implement changes that reduce
the number of poor-quality buns," he adds. "They'll get
a better handle on what they are producing."
The second phase of the project will extend automation by providing
in-line mechanisms to correct the vagaries leading to poor-quality
products. Proofers and ovens – the heat- and humidity-controlled
chambers where dough is sent to rise and bake – are subject
to normal disturbances that can affect product quality. Automatically
compensating for those disturbances reduces time spent correcting
problems.
ECE researchers, working with the GTRI team, are using data from the
screening and image-processing phase and from additional sensor inputs
to build a supervisory control system. It will be able to make changes
in the proofer and oven settings to fix problems as they are detected.
"
Baking is both a science and an art," says Professor Bonnie Heck,
Britton's colleague from ECE. "Good bakers know both and are
able to react based on experience and feedback from the process. We're
trying to enhance the ability of expert and novice bakers alike to
make better quality-control adjustments, while also adding automation
that can mimic some of those adjustments dynamically."
While the computerized quality-control and self-correcting production
system holds great commercial promise for the baking industry, Britton
says, generic aspects of the technology may be adapted to other food
processing industries as well.
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