Lector code analytics detects poor print quality in good time

4. November 2016

Preventing the effects of process errors

Reading codes on packaging and secondary packaging is an essential part of intralogistics and distribution processes. If a code is hard or even impossible to read, this will result in disruptions to the production process or downtime in sub-processes in the supply chain. To stop process errors causing poor print quality in the codes, SICK offers customers an intelligent solution: Thanks to the Lector Code Analytics function, process errors can be detected in good time so that their negative effects can be prevented in advance.

 

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The configurable image-based code readers in the Lector® series provide the best possible read performance, allow for optimum throughput, and are equipped with the Code Analytics function. The Lector63x is a flexible, imagebased code reader installed inside compact housing and features high image resolution and replaceable optics. This makes it particularly well suited to reading smaller codes from a great distance and with high production speeds. The Lector64x was designed for decoding 1D, 2D, and directly marked codes in real time. Thanks to its dynamic focus, the Lector65x offers a maximum degree of flexibility with regard to object height and transport speed. An image resolution of 2 to 4 megapixels gives it a large field of view, thereby ensuring maximum freedom for code positioning.

Better than good or nothing at all: Products from the Lector® series can now transmit additional information to the plant control unit (PLC).

Better than good or nothing at all: Products from the Lector® series can now transmit additional information to the plant control unit (PLC).

New Lector Code Analytics function for fine-tuning read results

Previously, the image-based code readers in the Lector® series could only distinguish between a good read result (Good Read) and no read results (No Read). This information could only indicate the actual read rate, e.g., 95%. There was no way to determine the trigger for a No Read, meaning that the cause remained unclear. A poor read rate reduced throughput and the productivity of a plant. There was no way to determine whether the poor results stemmed from process-related factors or whether they were caused by faulty settings for the read technology, for example. With the help of the Lector Code Analytics software function (which is very easy to activate during configuration), the Lector63x, Lector64x, and Lector65x image-based code readers can also use the images to generate additional information. Products in the Lector® series can transmit this additional information to the plant control unit (PLC), which in turn can emit warnings at an early stage before the production line comes to a standstill. Furthermore, the information can be displayed via one of the read device’s web servers. The user can, for example, receive notifications on the number of Good Reads, No Reads, and the number of objects without a code. This data can be used to determine effective read rates. With an effective read rate of say 90%, you can see precisely that, for example, 3% of the objects from the 10% of No Read codes did not have a code at all. Furthermore, Lector Code Analytics can see when codes are in place but cannot be read and can even provide information on the possible causes.

 

With the Lector Code Analytics function, images of codes can be evaluated, assigned to error  categories, and used to identify the reasons behind poor read results.

With the Lector Code Analytics function, images of codes can be evaluated, assigned to error categories, and used to identify the reasons behind poor read results.

SICK Sensor Intelligence. – Uncovering process errors and generating added value

With Lector Code Analytics, images of the codes can be emitted, stored, and categorized very effectively. The images are therefore available to the user for process analysis purposes. Using the fault categories, the user receives criteria for identifying causes within the process that go beyond simple code reading. As a result, he can implement suitable measures in good time in order to prevent the print quality of the codes from deteriorating along with the throughput. With this intelligent solution from SICK, operators can reduce their workload, avoid downtime, and, above all, cut costs. This makes the entire process chain more stable, all the way down to the last identification point:

 

  • Codes are used in every distribution center and sorting process
  • Parcel services work with codes that are read by transit centers
  • Food producers mark their products with codes that can be read at every stage in the supply chain
  • The manufacturing industry uses codes in intralogistic processes and for sending out products

 

The added value is clear to see – after all, Lector Code Analytics means that poor quality or unreadable codes do not leave the premises in the first place.

 

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