Error-proofing conveyed product with vision+sensor designs

When it comes to the level of quality acceptable in today's manufacturing environment, there is no negotiation. Machines must produce 100% perfect parts all day, all the time, and at ever faster rates at increasingly lower costs.

A few years ago, the quality burden rested on the PLC. Today, the inspection task falls largely to sensors and vision systems that measure products in various ways to see if they are in spec. The next step in automated product quality improvement is the merger of sensors and vision systems, achieving a new breed of devices that offer the versatility of vision but at a much lower cost.

Inspection perfection

Over the past few years, the terms total quality management (TQM), lean manufacturing, error proofing, mistake proofing, and Pokayoke have been used to describe various programs designed to drive out mistakes in the manufacturing process. Nowadays, it's recognized that the most effective error-proofing programs use sensors to eliminate errors as an integral part of the manufacturing process itself. Sensors error proof each manufacturing step to prevent bad parts from being produced in the first place by checking each step and either eliminating out-of-tolerance parts or stopping the process altogether.

Discrete sensor-driven error proofing typically works best when manufactured parts can be automatically positioned (for inspection) the same way every time, so that sensors can be aimed to verify a specific aspect of the part, a feature that indicates that a manufacturing step was done correctly. This calls for sensors stationed all along the production path, each making individual mini-inspections.

At the other end of the spectrum, vision-based inspection employs expensive equipment to mimic a conventional in-line or final inspection process, but in an automated manner. Vision methodology has the advantages of being able to inspect parts in various attitudes relative to the camera, as well as to inspect more than one attribute simultaneously, such as appearance, presence/absence, dimensional attributes, and positioning.

These two technologies — sensor-based error proofing and vision-based inspection — tend to be at polar opposites in complexity and capability. In the past, sensor-driven error proofing has been limited to discrete functionality based on specific technology. This includes photoelectric sensing, proximity sensing, or laser-based sensing, for example, to error proof a production or manufacturing process. This method works exceptionally well in the discrete manufacturing arena, providing relatively inexpensive solutions based on application expertise.

On the other hand, vision systems typically provide more complex multitasking sensing involving many simultaneous sensing methods or algorithms. These methods can perform error-proofing operations similar to discrete sensors, but with the addition of complex sensing that requires interconnection between sensing methods.

Sensor suppliers are now providing more sophisticated sensors and application techniques, thereby advancing up the curve toward vision solutions. Meanwhile, vision providers are trying to reach down the curve toward the discrete sensor world. Instead of a crash of technologies, a new layer of technology is evolving that combines the best of both worlds. With the merging of these technologies and the simplified “sensor like” approach to configuration and usage, end users can apply higher level sensing at a lower cost point — allowing optical sensors to be applied more readily in a true error-proofing scheme.

Vision made clear

Vision-based optical sensor products bridge the gap between simple and sophisticated by providing an easy-to-implement, practical, and cost effective way to error proof production. Because these sensors simultaneously check several aspects of the product with a single device that uses a simple configuration interface, the technology can be learned and used quickly by field operators.

Optical sensors with simplified configuration interfaces and multiple inspection/measurement algorithms driving multiple sensing options provide more information than a single function “smart camera” or a standard discrete sensor. At the same time, they avoid the complexity of vision systems, as well as the associated costs and required expertise for achieving reliable error proofing.

Optical sensors 101

A vision-based sensor is meant to be used more like a smart sensor, and less like a vision system. Like a traditional sensor, it's configured to look for certain product attributes to make sure specific aspects of the product are present, the part is configured correctly, and positioning is verified. But unlike a discrete sensor, an optical sensor does not need the part to be presented exactly the same way for each inspection, thereby reducing fixturing costs.

In addition, unlike a discrete sensor, it can check for multiple characteristics at the same time, thus justifying its cost by taking the place of several sensors, each of which can only check on one thing and allow little flexibility. As opposed to using a more traditional sensing array, optical sensors can significantly reduce the complexity and cost of error proofing while improving reliability. This opens up a whole new world of error proofing for reducing planned down time, enabling easier line changeovers, and better accommodating flexible or “build to suit” manufacturing.

Optical sensors are also ideal candidates for applications that have multiple points of discrete inspection, but do not have tight part fixturing. This type of sensor is ideal when different parts are run on the same line and require line configuration changes that would seriously hamper sensor arrays or require significant changeover or planned down time to allow for changes in sensor placement.

Not a silver bullet

In addition to understanding where optical sensors may excel, it's also important to know where they won't work as well as other inspection solutions. An optical sensor would not be as useful in cases where a single discrete sensor or two could just as easily solve the application. At the other end of the spectrum, optical sensors are not as useful in situations where complex inspection algorithms or internal logic are necessary. In these cases, a vision system would remain the better choice.

The missing link

When it comes to true error proofing, no can deny that using sensors to find errors in the process is the most effective method that can be employed. A vision-based optical sensor can provide the missing link between using multiple sensors with inflexible configurations, complex controller logic, and fixturing or higher end vision systems that can be overkill in complexity and cost for certain applications. When multiple products are manufactured on the same production lines, the need for cost-effective flexibility is even greater.

An optical sensor can be used to replace the sensor arrays required for several tasks and provide flexibility by using multiple job configurations to run multiple products on the same line by simply changing to the next part configuration in the sensor.

For example, if multiple box sizes are run on a packaging line with each box requiring a label to be applied to the top, the planned down time to change over to the next box can take more than an hour with sensor arrays. In this case, a minimum of a four sensor arrays on a sliding bracket with stops would be needed to detect the four corners of the label. Using a single optical sensor, an operator can detect if the label is present and if it is positioned, say, to between 0.1 mm and 0.7 mm in all four corners. This will also allow verification that all four corners have been properly fastened for boxes ranging from 25 to 150 mm wide. (Additional box sizes are possible depending on lens size chosen.) These detections can be done at line speeds as fast as 750 parts per minute.

As in most cases, lighting plays a key role in assuring the stability and reliability of the application. Another important note is to remember to use this sensor like a sensor. Trying to include too many verifications in a single sensor defeats the purpose of the error-proofing concept. The most successful error-proofing schemes keep error checking simple and distributed at the points where processes are performed, not at a single inspection location. Single inspection points for the entire process are what lead to more complex and expensive vision systems at the other end of the spectrum. The key advantage of using an optical sensor is its ability to simplify and provide even more flexibility to the existing error-proofing scheme.

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