Before installation, it is important to choose a device with optimal specifications to ensure inspections can be done accurately and consistently throughout the life of the machine. This article outlines the things an engineer should know before choosing a data acquisition device for embedding into equipment. Contributed by Shaina Warner, marketing communications manager, Microscan
Automation starts with data. The faster and more accurately data is communicated to a machine, the faster and more accurately the machine can perform its automated functions. In stand-alone machines, data acquisition is often achieved by integrating compact automated devices like barcode readers and machine vision cameras, offering companies the tireless efficiency and precision of machine-based data collection.
Unlike human operators who function at an error rate of around 1 out of every 300 data string entries, automated devices acquire data with an error rate of less than 1 in 3,000,000. This level of accuracy greatly favours barcode reading and inspection for tasks ranging from logging product and component information, enabling traceability in production, ensuring data accuracy, and communicating with equipment to trigger additional automated processes such as routing, rejecting, and batching.
1. Barcode Type And Orientation
Knowing the barcode type is key to narrowing down the list of possibilities when it comes to choosing an embedded barcode reader. Barcode readers may be either laser-based or camera-based. Laser-based barcode readers – often referred to as laser scanners – shine a laser spot over the dark and light elements of the barcode, measuring the reflected light from each element as it returns to the scanner, and use the scanner’s photo detector to transform a wave pattern light signal into a code string. Camera-based barcode readers and machine vision devices – often referred to as imagers – use rows of CCD or CMOS sensors in a two-dimensional array (the imager’s built-in camera) to generate an image of a symbol that is decoded using image processing.
Linear (1D) barcode like UPC or stacked symbols like PDF417 can be decoded by both laser scanners and barcode imagers. 2D symbols like QR Code and Data Matrix can only be decoded by 2D imagers. This makes the choice of embedded barcode reader clear for applications requiring 2D code reading.
Space restrictions or specific design requirements for integrated equipment may dictate that barcodes be fed into a machine at a particular orientation. How a barcode reader or machine vision camera is oriented in relation to the barcode and the direction the barcode is traveling are important considerations when selecting such a device for an application. When choosing a laser scanner, the scanner must always be oriented such that the laser scan line is perpendicular to the bars of the barcode.
2. Inspection Requirements
Applications requiring automated data acquisition beyond simple barcode reading (such as barcode quality verification; code, label, or part presence and orientation; product defect detection; colour inspection; and other visual inspection processes), require the use of machine vision cameras and software. Machine vision cameras, like 2D barcode imagers, are data acquisition devices that function by taking images of parts or codes to be inspected.
These images are processed by the camera to search for pixel- level variations, using software to compare the acquired data from the image to an expected result. This comparison results in images that meet the expected criteria (parts that pass inspection) and images that do not (parts that fail inspections).
The key to acquiring accurate and reliable data for machine vision inspection, as with barcode imaging, is to obtain a complete, high-contrast, and high-resolution image for the camera to process. Application requirements can greatly affect the ability of machine vision cameras to obtain high-quality images. Certain environments may require cameras with a greater ability to meet these criteria.
3. Application Speed
Time is of the essence in automated applications, and time savings is one of the main reasons for implementing an automated machine. Automation helps companies do more with less to increase operational output at a lower cost. Depending on how fast a machine is expected to run, and how fast a device is expected to acquire data for automated processes, certain factors may make one device better-suited for an embedded application than another.
Part of this has to do with differences between laser scanners and image-based barcode and machine vision cameras. Laser scanners can be faster at decoding 1D barcodes than imagers – as fast as 1,000 real-time decodes per second, as noted earlier. This is because the laser scanner is interpreting fewer elements when obtaining an encoded data string from a barcode; it is simply looking at a wave pattern caused by a reflection of light.
Camera-based imagers, on the other hand, must capture and process complete 2D images, including barcodes, part features, and any elements surrounding the actual area of interest, and extract data based on thousands of varying pixel elements within the image. This means that imagers can be more precise, but may also have longer decode times depending on the device and application. Recent advancements in processing technology have enabled faster processing times, and choosing a high-speed imager for high-speed applications is critical.
4. Integration Space
Integration space within turnkey systems is precious real estate. Every component in a system has its place, but the more efficiently that space is used, the smaller the footprint of the overall machine. Many embedded imagers are designed with constrained and geometrically-complex spatial requirements in mind. When choosing an embedded device for an application, it is very important to understand the integration space to find a device with the proper mechanical envelope and optical envelope to read each barcode or perform inspections reliably.
The mechanical envelope is the physical space required to accommodate an imaging device in relation to the barcode or part for inspection. Mechanical envelope takes part orientation into consideration as well as several other spatial requirements, including mounting, three-dimensional space allotment, and cable routing. The essential question is: How much physical space must the imaging device occupy in order to read a code or inspect a part reliably?
When evaluating mounting options for embedded devices, first take the time to note the characteristics of the barcodes or parts and their physical substrate. If, for example, barcodes are on a highly reflective surface, an imager may need to be mounted with an angled bracket to avoid specular or direct re ection from the barcodes, which can ‘blind’ the camera.
While it is critical that data acquisition devices be compact enough in size and scale to physically fit the available dimensions of the integration space, even more important is the space required for these devices to capture images (data). Simply because a barcode reader or machine vision camera fits into a particular space does not guarantee that it can read barcodes or correctly inspect parts presented to it at any size, orientation, or distance. The total dimensional space required by a particular device to decode a symbol or inspect a part at a specified distance is called its optical envelope (also sometimes called the ‘read’ or ‘inspection’ envelope).
The challenge when reading barcodes or inspecting parts at close range is achieving a field of view large enough to span the entire symbol or large enough to capture an object of interest.
Device size, mounting angle, and the distance from the device to the part all comprise the optical envelope and directly affect how much space must be available within a machine for a specific device to perform data acquisition tasks with reliability and repeatability. Since each device’s optics are slightly different, the required distance between a device and part will vary from unit to unit. Devices with smaller optical envelopes have the advantage of requiring less physical space between the device and the symbol or part to be inspected, minimising the overall mechanical footprint.
5. Data Communication Needs
The final thing to know about an application before choosing an embedded device for data acquisition is: how will the system communicate with the device, and how will the device communicate data back to the system? Communication specifications can determine the physical space occupied by the device and its accessories, the speed at which an embedded device must perform, the type of connectivity to the system, and the software used to set up and control the device. These characteristics can be determined by a device’s electrical functionality and software interface.
Power requirements, connectivity, inputs/outputs, and trigger methods all comprise the electrical considerations of embedding a data acquisition device. Many devices are designed with low power requirements in order to reduce the drain on the host instrument. Communication and connectivity options range from high-speed USB and Ethernet to RS-232.
While power requirements are fairly standard, triggering methods can vary greatly. Triggering allows an operator to tell a device when to expect a part or barcode to enter the eld of view, or how many scans or images to take of each object. There are two kinds of triggers: discrete (external) triggers and serial triggers. The decision about which type of trigger to use is typically based on preference: programming versus wiring.
Discrete triggers are separate sensors, often called object detectors, which can be wired directly into a barcode reader or machine vision camera. Discrete triggers require less programming than serial triggers. Serial triggers are sent from an external device, such as a PLC or host PC, which tells the reader or camera to look for a barcode or perform an inspection. Serial triggers are quite often used in embedded applications to provide more control over an embedded device from outside the machine.
Once the hardware setup for the data acquisition device is defined, the engineer should determine the type of software interface needed to control the device and to achieve optimal data output. Barcode readers and machine vision cameras today are capable of more than just interpreting images and outputting data. Instead, these devices function like independent computers with their own algorithms and processors, reducing the amount of programming required on the device to process data and putting the power in the hands of the operator to control the imager from outside the machine.
Technologies such as embedded web servers allow seamless connectivity to databases or other systems on a network. A smart camera can also be set up via software to make decisions based on inspection data, such as triggering an event or shutting down a process. Software for data communication should be able to initialize the device, check its status, and create a real-time communication protocol between the device, the machine, and the outside world.
Understanding an application’s requirements is critical in choosing the best device for successful data acquisition. By planning for application specifications early in the design process, and by incorporating those specifications into the design, engineers can dramatically increase the reliability and accuracy of their data acquisition processes for the life of their machines. The correct embedded barcode reader or machine vision camera provides the exibility to meet expanding requirements without the need for future design adjustments, significantly lowering the cost of ownership for the life of the entire system.