Trust but verify.
That’s the best way to stay out of hot water, they say – especially if you’re a manufacturer, warehouse operator or other downstream supply chain entity that must comply with numerous industry, government and customer mandates. So, you train people on how to confirm the quality consistency and design conformity of every part and finished good coming off the line. You may even invest in machine vision systems that can automatically inspect everything from automotive and electronic components to food, beverage and pharmaceutical items for production, assembly, and fill accuracy. You understand the risks of oversights from a consumer safety and financial consequence perspective.
But are you giving equal consideration and investment to the production and verification of the labels going on those products or their packaging? Or do you just trust that your print-and-apply system is configured and operating correctly?
Though the print engines used in today’s print-and-apply systems are known for their accuracy, it’s risky to trust that every label is being placed in the right position and reflects the right information. Humans are still the ones programming print engines, and print engines are still printers. Printheads will eventually need to be replaced and, until someone notices that they do, the quality of a labels could temporarily decline.
It doesn’t make sense to have someone standing on the line, keeping eyes on every labeled product or package running through the print-and-apply system. It may be hard to thoroughly inspect every labeled item without slowing down – or stopping – operations. And the person assigned to verify label quality and accuracy could overlook errors. I’ve had a document reviewed by six different people who missed a glaring inaccuracy, with the seventh person flagging it – after it had been published. In my case, I had the flexibility to immediately update the document and republish it. But you won’t have the luxury of fixing an incorrect or non-compliant label once it is let loose in the supply chain.
The next recipient might be able to fix the label issue, if caught by an inbound team at a warehouse for example. Or they might be able to stop the further shipment of mislabeled products. But what if the labeling error is identified by a regulatory inspector or consumer? Or what if the package is erroneously sent to the wrong person, or stalled progress at a sorting station, because the address is incorrect or illegible? The consequences could be severe and costly.
That’s why we’re seeing a trend toward automated “trust, but verify” in labeling applications and, specifically, print-and-apply labeling applications.
There are a few reasons why 1D and 2D label validations should be automated in conjunction with print-and-apply systems. You need to be 100% sure…
a label is present, and the information is correct as soon as it’s printed and (supposed to be) applied. Label integrity is critical to compliance in highly regulated industries, such as pharma, automotive and food and beverage. If text isn’t bold enough or the right color, or a lot number is missing, you could be financially liable for misuse or the inability to recall quickly. Of course, a missing label is never a good thing, as that leads to waste and fulfillment delays.
label data is readable. A person may say that a barcode or address is readable, but a scanner might disagree. It’s important that all data can be extracted by scanners as goods move through the supply chain.
label placement is correct. People’s perceptions are subjective, as I mentioned before. If a label is affixed even a half centimeter off from its required position, it’s possible the human eye won’t discern that, and you could be deemed non-compliant.
By installing fixed industrial scanning and machine vision systems on the line next to your print engines, you’ll be able to immediately catch and resolve any issues with label quality, positioning, or data accuracy before affected items make it off the line and to the loading dock or further downstream into the supply chain.
The fixed industrial scanners can look for the presence or absence of labels and data, while machine vision systems can be trained to look for a shape or logo (aka a “Model”) on a label. When the item passes under the machine vision camera in an outbound inspection application, it will look for that Model to ensure presence and proper positioning. If used for sortation, it will look for the courier logo and redirect the package to the right line for onward distribution. Machine vision systems can also measure the brightness or perform a pixel count within a search region on the label. You can define the inspection criteria within a set of limits, and products that exceed these limits will fail.
The beauty of this type of automated validation scan is that it can double as a progress report and doesn’t involve any manual intervention unless the system identifies an issue. I don’t have to tell you that product traceability is becoming mission critical for many reasons. So, anytime you can confirm that an item has passed a certain checkpoint, you and other stakeholders gain valuable operational insight that can inform business planning, reporting and optimization. By simultaneously eliminating product or package touchpoints throughout your processes, you will also free up workers to focus on even higher-value tasks. And that will only strengthen your ability to keep production, fulfillment, and distribution operations compliant and consistently on schedule.
If you’re curious how exactly a fixed industrial scanner or machine vision system could be integrated into your current print-and-apply process, let’s schedule time to chat. We can take a close look at your entire operational workflow today, as well as your labeling requirements, to determine the best way to automate validations and build trust in the outcomes.
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Laith Marmash is a product marketing specialist with over 20 years of experience in the manufacturing and factory automation sectors. His extensive career spans several technologies such as print and apply, laser marking, inkjet printing and most recently, machine vision. He brings perspectives gained from designing and integrating production line solutions, to creating and delivering effective customer communications.
He is a passionate advocate about empowering customers to learn and adopt technologies and solutions that can help them successfully introduce and integrate digital automation into their operational environments to increase efficiencies and improve productivity.
Laith holds a Bachelor of Engineering Honours degree (BEng Hons) from Loughborough University in the United Kingdom.
Prior to joining Zebra, Laith’s career included engineering, sales and marketing roles at numerous B2B technology companies such as Videojet, Cognex and Stemmer Imaging.