Double sheet detection, also known as double blank detection, is an essential step in stamping quality control processes, as failure to do so can cause costly damage and downtime. Analog inductive sensors can deliver a cost-effective and easy way to add this step to stamping processes.
Most people have experienced on a smaller scale what happens when the office printer accidentally feeds two sheets of paper; the machine jams and the clog must be manually removed. Beyond the annoyance of not getting the printout right away, this typically doesn’t cause any significant issues to the equipment. In the stamping world, two sheets being fed into a machine can severely affect productivity and quality.
When two metal sheets stick together and are fed into a machine together, the additional thickness can damage the stamping dies and other equipment like the robot loaders, which can cause the production line to shut down for repairs. Even if the tool fares better and does not get damaged, the stamped product will likely be defective. In today’s highly competitive and just-in-time market, machine downtime and rejected shipments due to quality can be very costly.
A simple solution to detect multiple sheets of metal is analog inductive sensing. This kind of sensor offers non-contact sensing with a 0…10V analog output, which can be used to determine when the thickness of the metallic material changes. As the material gets thicker, or as multiple sheets of metal stack on top of one another, the analog output from the sensor varies proportionally. These sensors can be used with ferrous or non-ferrous metals, but the operating range will be reduced for non-ferrous metals. As shown in the graph (Image 1), as the distance with the metallic target changes, the analog output increases from 0 to 10V.
The pictures above, shows the technology in action. With a single sheet of aluminum, the output from the sensor is 2.946V, and for two sheets, the output is 5.67V. The user can establish these values as a reference for when there is more than one sheet of metal being fed into the machine and stop the equipment from attempting to process the material before it is damaged. These sensors can be placed perpendicular or inline with the target material and are offered in various form factors so they can be integrated into a wide range of applications.
Packaging industries must operate with the highest standards of quality and productivity. Overall Equipment Effectiveness (OEE) is a scoring system widely used to track production processes in packaging. An OEE score is calculated using data specifying quality (percent of good parts), performance (performance of nominal speed) and equipment availability (percent of planned uptime).
Quality issues can directly impact the customer, so it is essential to have processes in place to ensure the product is safe to use and appropriately labeled before it ships out. Additionally, defects to the packaging like dents, scratches and inadequate labeling can affect customer confidence in a product and their willingness to buy it at the store. Issues with quality can lead to unplanned downtime, waste and loss of productivity, affecting all three metrics of the OEE score.
Traditionally, visual inspections and packaging line audits have been used to monitor quality, however, this labor can be challenging in high volume applications. Sensing solutions can be used to partly automate the process, but complex demands, including multiple package formats and product formulas in the same line, require the flexibility that machine vision offers. Machine vision is also a vital component in adding traceability down to the unit in case a quality defect or product recall does occur.
Vision systems can increase productivity in a packaging line by reducing the amount of planned and unplanned downtime for manual quality inspection. Vision can be reliably used to detect quality defects as soon as they happen. With this information, a company can make educated improvements to the equipment to improve repeatability and OEE and ensure that no defective product reaches the customers’ hands.
Some vision applications for quality assurance in packaging include:
Check that a label is in place, lined up correctly and free of scratches and tears. Ensure that any printed graphics, codes and text are legible and printed with the expected quality. Use a combination of OCR (Optical Character Recognition) to read a lot number, expiration date or product information, and then OCV (Optical Character Verification) to ensure legibility.
Primary and secondary packaging inspection for dents and damage
Inspect bottles, cans and boxes to make sure that their geometry has not been altered during the manufacturing process. For example, check that a bottle rim is circular and has not been crushed so that the bottle cap can be put on after filling with product.
Safety seal/cap presence and position verification
Verifying that a cap and/or seal has been placed correctly on a bottle, and/or that the container being used is the correct one for the formula / product being manufactured.
Product position verification in packages with multiple items
In packages of solids, making sure they have been filled adequately and in the correct sequence. In pharmaceutical industries, this can be used to check that blister packs have a pill in each space, and in food industries to ensure that the correct food item is placed in each space of the package.
Certification of proper liquid level in containers
For applications in which it can’t be done reliably with traditional sensing technologies, vision systems can be used to ensure that a bottle has been filled to its nominal volume.
The flexibility of vision systems allows for addressing these complex applications and many more with a well-designed vision solution.
For more information on Balluff vision solutions and applications, visit www.balluff.com.