You already know all the benefits of the use of vision systems and their assistance in automation of manufacturing, accuracy, consistency, safety and others. Optical character recognition is a good example of the extension of utility that is created for task automation by vision systems. Using OCR is a way for an automated system to capture data during product manufacturing. This data capture can be for safety reasons, like for identifying the lot number of some food product or the identification of subsequent steps that must be done in the production process. For instance, the production process must include a special cap tightening procedure for bottle caps if the lot number is a certain number for soda bottles. This task automation is not performed in the process if the lot number is different. Using OCR the automation controller can determine when any units has the lot number that will need special tightening. There are many variation on this theme which will allow for the conditional processing of products based on the OCR of machine-readable characters on products.
OCR is a part of the vision capability that is a necessity in conjunction with high speed automation. Having machinery be able to read characters on products or raw materials at a very high speed is very beneficial task automation. A string of characters on a surface is transformed from a digital image that is “read” by OCR into a string of characters that can be interpreted by the automation controller. This string of characters turns into an instruction for automation devices. The character string can also be an instruction to the program to issue a conditional command to an automation device. In any event, it is the same as a program in the controller being able to give a conditional instruction to an automation device while it is working, without human intervention.
There are many requirements and restrictions in place that are designed to assure the safety of products before they arrive in the market place. All the raw materials that are used in food and drug products are produced in limited-sized control batches for easy identification all the way through the supply chain down to the consumer. As a result of this control the batch numbers of any consumable products must be visible on all of these products when they leave the plant. Optical character verification is a type of task automation that is used to verify that the product has the required batch or lot numbers applied before leaving the plant to go to the consumer. At every stage of movement through the manufacturing operation OCV is used to make sure that raw material batches are as they should be when container filling, packaging, and other operations are done. Consumable product batches of raw materials are assigned to labels that are put on their product containers. The batch numbers of the raw materials that are in the containers are printed on the labels. If there is a discrepancy between the batch numbers on product labels and the actual contents of the product there are serious consequences for manufacturers. OCV is used to help keep batches and their product labels synchronized.
In days gone by when I worked as a manager in a manufacturing facility there was very little task automation. It was necessary for the production personnel to bring the drums of raw materials to the production line while the manufacturing line was running. During the setup process for a given manufacturing job I would give the batch numbers of the product to be produced to these personnel for retrieval. These personnel would go warehouse and bring to the production floor the drums that contained the raw material for the job. You can see the immediately from this short explanation what the inherent dangers are. It would take a very careful examination to make sure that the right batches of raw materials were brought to the production line in the order that matched the labels to be put on the completed products. I was very careful to double check the batches of raw materials before they were put into the hoppers for filling. It was a very expensive procedure to “rework” products that were mislabeled . In fact it could mean termination.
With the advent of OCR and OCV it is now possible for the same production process to run under the control of an automation controller that is helped by character recognition and verification. The controller would recognized that the correct raw material was available because of the OCR ability of automation. Labels and batches would also be matched in the same way. The automation controller would not allow the wrong labels to be put on product containers.
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