Vision system inspects buns in high-volume baking processes
A machine vision system developed at Georgia Tech Research Institute inspects the color and characteristics of baked buns for food service and fast food customers.
A machine vision system developed atGeorgia Tech Research Institute (Atlanta, GA, USA) inspects the color and characteristics of baked buns for food service and fast food customers. Improving the quality control of bun baking is of great importance to customers such as Arby's, Wendy's, and McDonald's, among others. The baking industry is the third largest segment of Georgia’s food processing industry (13% by sales volume) with operations located throughout the state.
A growing number of fast food providers are placing increasing demands on quality control for bun size, shape, color, and topping coverage (sesame seeds, etc.). Accurate control of the quality is challenging considering the high volume production, with rates of up to 1,000 buns per minute on a line. The high volume also indicates the need for automated control (correcting a drifting color before it goes out of specification would save thousands of buns).
The standard inspection process is for workers to remove a few samples of the product each hour and to inspect both the top and bottom manually against customer specifications. Customers are pushing for a more accurate and uniform assessment process, and a means to actively control this product. Anarticle on the Georgia Tech website describes the imaging system with automated feedback to an oven control system.
Posted byVision Systems Design