All baked goods have universal visual traits that consumers have come to expect. For example, the crust or color of a baguette, or the volume and uniformity of a bagel, are instantly identifiable to the product type. Then, there are other features that are specific to brand standards, like the seed coverage of a hamburger bun, the swirl of frosting on a cupcake, or the positioning and depth of a split on a loaf of bread.

The cookie and biscuit markets are highly competitive, with several brands worldwide vying for consumer attention through unique shapes and designs to go along with alternative recipe formulations like gluten-free, reduced sugar/salt, and other varieties. Amid the push to innovate and meet consumer demands, cookie companies that prioritize tight visual criteria in their product development process will have a competitive advantage.

Relying solely on manual observation of products introduces subjectivity into a process that can be difficult to manage globally. As a result, vision inspection technologies used in recipe R&D or at-line settings have been vital tools to help cookie brands develop product-specific visual standards.

Step 1: Identify the Core Traits that are Important to Your Products

Start the visual measurement-development process by focusing on one or two essential features of your product. Is your cookie recognized for its baked color or shape? Or, if your cookie is stamped with a logo or design – will the new product formulation maintain the design through the baking process, or is a process adjustment needed for that specific product type? Starting basic and building onto initial measurements over time will help bakers develop more substantial standards and help them understand their products and production processes. 

Step 2: Collect a Wide Range of Product Samples

Once you have your essential parameters selected, next begins the sampling collection process. It is important to have a collection of good and bad samples to find an acceptable tolerance for cookie quality based on those few defined traits. Depending on the product, this may require several baking trials and hundreds of samples. While this may be a laborious process, the baking quality team will be more confident that their brand standards are met in the long run. 

Step 3: Use Data to Tweak Processes and Manage the Operating Environment

Producing cookies on an industrial scale is a far different process from a home kitchen. For a home baker, adding more water, flour, or other ingredients in a dough only-the-fly is much more feasible than in a high-volume baking operation. Therefore, a benchtop vision system like the TheiaVu® series can help bakers key in on factors affecting product variations, such as flour or ingredient quality, resting time, oven temperature, outside operating environment, production equipment, and more.

Step 4: Collaborate to Implement Standards

Remember – the goal of vision inspection technology is to help the production team develop consistent products, not create waste. Throughout the measurement development process, it is important for quality control and production departments to collaborate to ensure realistic, repeatable tolerances. For many companies, this is typically where an integrated Vision Process Control solution can help ensure standards are controlled at critical stages of the production process. This article explains more about the value Vision Process Control applications offer to baking operations.

Consider a Low-Risk Method to Develop Higher Visual Standards for Cookies and Other Baked Products

Vision inspection systems, like the TheiaVu® Series, are highly accurate. Still, their primary value to baking companies depends on the proper setting of product specifications and inspection parameters based on the production line. Because of this, taking enough time to develop repeatable product tolerances is the best route to success. However, transferring these measurements and tolerances to a production line is the next logical step in the process.

Learn more about how companies automate vision inspection capabilities into their baking process.

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