How to Leverage Data Acquisition on Your Weigh Price Labeler

By Mike Alyounes, engineering supervisor, Ossid, a division of ProMach

Technological advances enable today's weigh price labeling machines to not only weigh, price, and label packages faster, easier, and more reliably, but also to collect and archive real time data on packaging line productivity and throughput. Packagers that leverage data acquisition capabilities to monitor production and make process improvements gain strategic advantages that are key to improving performance and profitability. The open architecture of weigh price labeling machines now available makes integration with upstream and downstream systems seamless, offering users the opportunity to further automate their packaging systems. Since collected data is archived, traceability information is available quickly and easily should a quality issue arise.

Monitoring production

Fresh foods such as meats and cheeses are weighed, priced, and labeled at the point of production rather than at the store. The weigh price labeler collects the actual weight, total price, sell-by date, and bar code information of every unit that is packaged.

Often the end customer specifies that packages weigh between a minimum and maximum amount or an exact amount. The weigh price labeler collects the actual weight and total price of each unit. By reviewing the collected data, the producer can determine if the overall quantity of the product being supplied exceeds what the end user is being charged for. For example, if the end user is specifying that each tray of boneless chicken contains two pounds and analysis of the collected data reveals that packages weighed two pounds and one ounce, then steps can be taken to either improve the accuracy of the equipment feeding the tray, such as slicers, or the producers can bill the customer at a higher rate so profits are not lost.

By analyzing the data acquired from individual production lines running the same product using identical equipment but achieving different levels of productivity, companies can look for causes for the variance. This may lead to uncovering issues such as insufficient operator training.

Process improvements

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