How to Optimize Production Processes with Vision Inspection

When it comes to the quality of baked goods, snack foods, breaded meat products, and other processed foods, consumers expect consistency. Many of these products enter a complex series of automated steps where machines interact with the product throughout the process.

How to Optimize Production Processes with Vision Inspection

Image Credit: KPM Analytics

For instance, several processed food products consist of ingredients applied outside of the product, such as glazes, seeds, colored seasonings, chocolate chips, and others. A few products may also have logos, branded designs, and other cosmetic features that have been stamped onto the product at some stages of their process.

Food processing machines have been calibrated and frequently checked to guarantee they are executing their particular application in a consistent manner. Over time and for several reasons, such machines have the potential to run out of alignment, clog, or over-apply ingredients, leading to an out-of-spec product.

In food production operations that produce thousands of products every day, many depend on manual product inspection prior to packaging. Yet, as manual inspection is highly subjective and operator-dependent, it can be hard to detect the warning signs of a problem in the production process.

It usually is not until a production run is too far gone that these variations are noticed and adjusted, leading to wasted product or worse.

A Seemingly Minor Insignificance Prompts a Process Malfunction

One cupcake producer recently experienced how a little visual defect could signal a critical issue in the production process. Following baking, every cupcake gets a layer of chocolate frosting over the top, followed by a series of icing swirls employed by a mechanical icing applicator. The thickness and position of the icing are significant for brand standards.

As part of the company’s quality control protocol, a quality assurance specialist is required to hand-pick ten cupcakes from the production line to inspect for product specifications once every hour of their shift. Together with the shape, size, and color of the entire cupcake, they should also investigate the sequence, position, and thickness of the icing swirl.

On this day, one QA operator failed to recognize that the icing swirl began to display subtle inconsistencies from one hour to the next. He guaranteed that various swirls on each cupcake were the correct amount but did not observe that the applied icing was moderately thinner from one hour to the next. Also, the swirls started to move closer to one side of the cupcake rather than down the middle.

How to Optimize Production Processes with Vision Inspection

Image Credit: KPM Analytics

While the production problem was only minor to start with, without an objective method to detect such changes, the cupcake producer gradually found themselves in a quality crisis.

The issue began close to a shift change and because of the lack of data about the problem, minutes into the next shift, the icing applicator began running completely out of spec, leading to a total shutdown of production and wasted cupcakes and ingredients. Due to the previous QA operator's oversight in spotting the gradual subtleties from unit to unit, the result was a critical error that could have been avoided with a simple mechanical adjustment on the machine.

Sights Set on a Better Way to Proactively Detect Difficult-to-Measure Production Flaws

The company's search for a solution lead them to the TheiaVu Compact Vision Inspection System, a benchtop unit developed for the at-line analysis of products. The user positions a product sample on the TheiaVu conveyor, which exposes the product to an array of lasers, high-speed cameras, and imaging software to examine the visual features of the product.

In just a matter of seconds, the TheiaVu presents a full report on the size, shape, and color of the product and as well as elaborate measurements on crumb analysis, topping coverage, and more.

How to Optimize Production Processes with Vision Inspection

Image Credit: KPM Analytics

As the icing appearance is such a significant feature of their cupcake, with the help of KPM Analytics, the company has programmed a custom 2D & 3D TheiaVu measurement to ensure the perfect sequence, swirl placement, and thickness.

As an extra advantage, the TheiaVu soon became a crucial process control instrument to determine any mechanical flaws present in their production equipment, whether that be the icing applicator or elsewhere.

Its quality assurance team, armed with this objective data, has allowed the company to enhance quality and reduced waste, thereby enabling them to produce more cupcakes per shift.

This information has been sourced, reviewed and adapted from materials provided by KPM Analytics.

For more information on this source, please visit KPM Analytics.


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