Document Product Quality and Eliminate Disputes with Machine Vision

“I caught a record-breaking walleye last weekend,” an excited Joe announced to his colleagues after returning from his annual fishing excursion to Canada.

“Record-breaking?  Really?  Prove it.” demanded his doubtful co-worker.

Well, I left my cell phone in the cabin so it wouldn’t get wet on the boat so I couldn’t take a picture, but I swear that big guy was the main course for dinner.”

“Okay, sure it was Joe.”

We have all been there — spotted a mountain lion, witnessed an amazing random human interaction, or maybe caught a glimpse at a shooting star.  These are great stories, but they are so much more believable and memorable with a picture or video to back them up.  Now a days, we all carry a camera within arm’s reach.  Capturing life events has never been easier and more common, so why not use cameras to document and record important events and stages within your manufacturing process?

As the smart phone becomes more advanced and common, so does the technology and hardware for industrial cameras (i.e. machine vision).  Machine vision can do so much more than pass fail and measurement type applications.  Taking, storing, and relaying pictures along different stages of a production process could not only set you apart from the competition but also save you costly quality disputes after it leaves your facility.  A picture can tell a thousand words, so what do you want to tell the world?  Here are just a couple examples how you can back up you brand with machine vision:

Package integrity: We have all seen the reduced rack at a grocery store where a can is dented or missing a label.  If this was caused by a large-scale label application defect, someone is losing business.  So, before everyone starts pointing fingers, the manufacturer could simply provide a saved image from their end-of line-vision system to prove the cans were labeled when shipped from their facility.

Assembly defects: When you are producing assembled parts for a larger manufacturer, the standards they set are what you live and die by.  If there is ever a dispute, having several saved images from either individual parts or an audit of them throughout the day could prove your final product met their specifications and could save your contract.

Barcode legibility and placement: Show your retail partners that your product’s bar code will not frustrate the cashier by having to overcome a poorly printed or placed barcode.  Share images with them to show an industrial camera easily reading the code along the packaging line ensuring a hassle-free checkout as well as a barcode grade to ensure their barcode requirements are being met.

In closing, pictures always help tell a story and make it more credible.  Ideally your customers will take your word for it, but when you catch the record-breaking walleye, you want to prove it.

Which RFID Technology is Best for Your Traceability Application?

There are a lot of articles on using RFID for traceability, but it’s hard to know where to begin. Examples of traceability include locating an important asset like a specific mold that is required to run a machine or verifying a specific bin of material required to run production. Spending time looking for these important assets leads to lost time and production delays. RFID can help but understanding the different RFID capabilities will narrow down the type of RFID that is required.

Not all RFID technology is the same. Each RFID technology operates differently and is categorized by the frequency band of the radio spectrum, such as low frequency, high frequency and ultra-high frequency. In low and high frequency RFID, the read range between RFID tag and reader antenna is measured in millimeters and inches. The read range on ultra-high frequency (UHF) RFID technology can range from one meter to 100 meters. Typically, inventory traceability is done using ultra-high frequency band of the radio frequency spectrum, due to the need to read the asset at a further distance so it does not interfere with the production flow. Also, there are cases where there needs to be a reading of multiple tags in an area at the same time to determine where an asset is located. UHF RFID technology allows for simultaneous reading of multiple RFID tags from a single antenna reader.

There are two types of UHF RFID, passive and active.  Passive UHF RFID means that the RFID tags themselves have no additional power source. The UHF reader antenna sends out an electromagnetic wave field, and the RFID tags within the electromagnetic field have an internal antenna that receives the energy which activates the integrated circuit inside the tag to reflect the signals back to start communicating. The read distance between the passive RFID tag and antenna reader is determined by several factors, such as the size of the electromagnetic wave field generated out of the reader antenna and the size of the receiver antenna on the RFID tag. Typical read ranges on passive UHF systems can be anywhere from one to 12 meters, where the larger the power and RFID tag, the longer the range.

Active UHF RFID systems do not require the tag to reflect signals back to communicate because the active RFID tag has its own transmitter and internal battery source. Because of this, with active UFH RFID you can get read ranges of up to 100 meters. There are active tags which wake up and communicate when they receive a radio signal from a reader antenna, while others are beacons which emit a signal at a pre-set interval. Beacon active tags can locate in real time the location of the asset that the RFID tag is attached to. However, a downfall to active RFID tags is the battery life on the tag. If the battery is dead, then the asset will no longer be visible.

Figure 1

Once the strengths and weaknesses of each type of UHF RFID system is known, it’s easier to work with the constraints of the system. For example, the application in Figure 1 shows a reader antenna for reading bins of material placed a few feet away so that its’ not in the way of production. A passive UHF RFID system will work in this case, due to the distance between the antenna and the RFID tag on the bin a few feet away. There is no need to worry about battery life on the passive RFID tag.

Figure 2

If the exact location of a production mold is required in a large facility, then using an active UHF RFID system is likely a better fit. Incorporating an active RFID tag that sends out a beacon at a fixed interval to a data center ensures the location of all assets are always known. With this setup, the exact location of the mold can be found at any time in the facility.

Examining the different types of RFID technology can help determine the correct one to use in a traceability application. This includes analyzing the pros and cons of each technology and seeing which one is the best fit for the application.

The Right Mix of Products for Recipe-Driven Machine Change Over

The filling of medical vials requires flexible automation equipment that can adapt to different vial sizes, colors and capping types. People are often deployed to make those equipment changes, which is also known as a recipe change. But by nature, people are inconsistent, and that inconsistency will cause errors and delay during change over.

Here’s a simple recipe to deliver consistency through operator-guided/verified recipe change. The following ingredients provide a solid recipe-driven change over:

Incoming Components: Barcode

Fixed mount and hand-held barcode scanners at the point-of-loading ensure correct parts are loaded.

Change Parts: RFID

Any machine part that must be replaced during a changeover can have a simple RFID tag installed. A read head reads the tag in ensure it’s the correct part.

Feed Systems: Position Measurement

Some feed systems require only millimeters of adjustment. Position sensor ensure the feed system is set to the correct recipe and is ready to run.

Conveyors Size Change: Rotary Position Indicator

Guide rails and larger sections are adjusted with the use of hand cranks. Digital position indicators show the intended position based on the recipes. The operators adjust to the desired position and then acknowledgment is sent to the control system.

Vial Detection: Array Sensor

Sensor arrays can capture more information, even with the vial variations. In addition to vial presence detection, the size of the vial and stopper/cap is verified as well. No physical changes are required. The recipe will dictate the sensor values required for the vial type.

Final Inspection: Vision

For label placement and defect detection, vision is the go-to product. The recipe will call up the label parameters to be verified.

Traceability: Vision

Often used in conjunction with final inspection, traceability requires capturing the barcode data from the final vials. There are often multiple 1D and 2D barcodes that must be read. A powerful vision system with a larger field of view is ideal for the changing recipes.

All of these ingredients are best when tied together with IO-Link. This ensures easy implantation with class-leading products. With all these ingredients, it has never been easier to implement operator-guided/verified size change.

RFID Gaining Traction in Tire Manufacturing

RFID is one of the hottest trending technologies in the tire industry. It has the potential to increase efficiency in tire production and logistics processes and gather large amounts of data for IIoT.

This technology will:

  • Reveal transparency deep in the processes
  • Minimize the number of rejected tires
  • Improve production processes for fewer failures
  • Increase control of materials
  • Improve the overall quality of individual tires

The challenge of using RFID in the tire industry is dealing with the harsh environments of some of the production areas in automotive plants. But the benefits of RFID to the tire industry are becoming more and more a reality. Suppliers of RFID are talking to tire manufacturing engineers, automation teams, material handling teams and R&D development engineers to develop better tools. For now, here are some examples of where RFID can be implemented in the tire creation process to improve efficiency, quality and cost.

In the mixing process, RFID “labels” are applied to all the chemicals and rubber compounds to assure the mixing of the right recipe of materials. RFID readers can be mounted on TBMs (Tire Build Machines), which are located before the curing press process, to assure the right material reels, parts and tools are in place before the expensive tire build process occurs.

There is also a growing need for RFID in the curing and mold processes. It important to manage the molds and the parts of the mold, like the bead rings, mold containers and mold segments. These are very expensive and there are hundreds in the average plant. Tags need to be able to sustain temperatures above 300 °F continuously for 8 hour shifts with little to no cooling down time.

RFID is an excellent tool to monitor material flow throughout the whole manufacturing process. RFID can be added to a trolly, AGV, conveyors and hook-chain conveyors.

While RFID is already being implemented by some tire manufacturers, there is much room for much growth in this conservative industry. As more manufacturers lean into IIoT and the need for data, RFID will surely be used more and more often.

The tire industry is excited to roll in RFID technology and pumped up to implement it where it makes the most sense and ROI dollars.

For more information about the tire industry, visit https://www.balluff.com/local/us/industries-and-solutions/industry/mobility/tire-industry/

How Condition Monitoring has Evolved and Its Role in IIoT

In recent years, as IIoT and Industry 4.0 have become part of our everyday vocabulary, we’ve also started hearing more about condition monitoring, predictive maintenance (PdM) and predictive analytics. Sometimes, we use these terms interchangeably as well. Strictly speaking, condition monitoring is a root that enables both predictive maintenance and predictive analytics. In today’s blog we will brush up a little on condition monitoring and explore its lineage.

Equipment failures have been around since the beginning of time. Over the years, through observation (collecting data) and brute-force methods, we learned that from time-to-time every piece of equipment needs some TLC. Out of this understanding, maintenance departments came to existence, and there we started having experts that could tell based on touch, smell and noise what is failing or what has gone wrong.

Figure 1: Automation Pyramid

Then we started automating the maintenance function either as a preventative measure (scheduled maintenance) or through some automated pieces of equipment that would collect data and provide alerts about a failure. We proudly call these SCADA systems – Supervisory Control and Data Acquisition. Of course, these systems did not necessarily prevent failures, but help curtail them.  If we look at the automation pyramid, the smart system at the bottom is a PLC and all the sensors are what we call “dumb sensors”. So, that means, whatever information the SCADA system gets would be filtered by the PLC. PLCs were/have been/ and are always focused on the process at hand; they are not data acquisition equipment. So, the data we receive in the SCADA system is only as good as the PLC can provide. That means the information is primarily about processes. So, the only alerts maintenance receives is when the equipment fails, and the process comes to a halt.

With the maintenance experts who could sense impending failures becoming mythological heroes, and  SCADA systems that cannot really tell us the story about the health of the machines, once again, we are looking at condition monitoring with a fresh set of eyes.

Sensors are at the grass root level in the automation pyramid, and until the arrival of IO-Link technology, these sensors were solely focused on their purpose of existence; object detection, or measurement of some kind. The only information one could gather from these sensors was ON/OFF or a signal of 4-20mA, 0-10V, and so on. Now, things are different, these sensors are now becoming pretty intelligent and they, like nosy neighbors, can collect more information about their own health and the environment. These intelligent sensors can utilize IO-Link as a communication to transfer all this information via a gateway module (generally known as IO-Link master) to whomever wants to listen.

Figure 2: IO-Link enabled Balluff photo-eye

The new generation of SCADA systems can now collect information not only from PLCs about the process health, but also from individual devices. For example, a photo-eye can measure the intensity of the reflected light and provide an alert if the intensity drops beyond a certain level, indicating a symptom of pending failure. Or a power supply inside the cabinet providing an alert to the supervisory control about adverse conditions due to increase temperature or humidity in the cabinet. These types of alerts about the symptoms help maintenance prevent unplanned downtime on the plant floor and make factories run more efficiently with reduced scrap, reduced down-time and reduced headaches.

Figure 3: The Next Generation Condition Monitoring

There are many different condition monitoring architectures that can be employed, and we will cover that in my next blog.

Which Photoelectric Sensor Should I Be Using?

There are many variations within the category of photoelectric sensors, so how do you select the best sensor for your application? Below, I will discuss the benefits of different types of photoelectric sensors and sensing modes.

Through Beam

Through beam sensors consist of an emitter and a receiver. The emitter produces a beam of light, while the receiver identifies whether that light is present or not. So, when an object breaks the beam, an output is triggered by the receiver. Some of the advantages of using the simple through beam technology is that, unlike some of the other photoelectric sensors, it doesn’t matter the color, texture or transparency of your target.

Retroreflective

What if you would like to have a through beam sensor, but don’t have enough room for two sensor heads in your application? Retroreflective sensors have an emitter and receiver within one housing and use a high-quality reflector to reflect the light beam back to the sensor head. This allows for easy connection of just one sensor head, but it doesn’t have the range of your typical through beam sensor. When using these types of sensors, you must factor in how small or reflective your target material is. If you are trying to sense a highly reflective material, then the light reflected back to the receiver could cause the sensor to think an object is present. If you are having these problems, but still want to use a retroreflective sensor, then you should consider versions with a polarizing lens. These lenses make the sensors insensitive to interference with shiny, reflective material.

Fork

Fork sensors include the transmitter and receiver in one housing, and they are already aligned. This saves time and energy during set up. Fork sensors are fantastic for small component and detail detection.

Diffuse

If you don’t have room for a sensor head on each side of your application or even a reflector, or you have had trouble with the alignment of a retroreflective sensor, a diffuse sensor may be a good choice. Diffuse sensors use technology to be able reflect light off the material and back to the sensor. This eliminates the need for a second device or reflector. This significantly reduces set up. You can simply place your target material in front of the sensor and teach it to that point. Once your object reaches that point, the light will be reflected back to the sensor, producing the output. While they are simpler to install, they also have a shorter range compared to through beam sensors and may be affected by your material’s color or the reflectivity or your background… Unless, you have a diffuse sensor with background suppression.

Background Suppression

Diffuse sensors have an emitter and receiver in one housing. In diffuse sensors with background suppression, the emitter and receiver are at a fixed angle so that they intersect at the position of your target material. This will help narrow the operating area (area in which your target material will be entering) and not let reflective material in the background have an influence in your detection.

Conclusion

Photoelectric sensors are simple to use when you need non-contact detection of a material’s presence, color, distance, size or shape, and with their various types, housing and sizes, you can find one that is ideal for your application.

Is IO-Link with Single Pair Ethernet the Future?

20 meters.

That is the maximum distance between an IO-Link master port and an IO-Link device using a standard prox cable.  Can this length be extended?  Sure, there are IO-Link repeaters you can use   to lengthen the distance, but is there an advantage and is it worth the headache?

I hope you like doing some math, because the maximum distance is based on the baud rate of the IO-Link device, the current consumption of the IO-Link device and finally the cross section of the conductors in the cabling.  Now throw all that into a formula and you can determine the maximum distance you can achieve.  Once that is calculated, are you done? No.  Longer cables and repeaters add latency to the IO-Link data transfer, so you may need to slow down the IO-Link master’s port cycle time due to the delay.

Luckily, there is a better and easier solution than repeaters and the sacrifice of the data update rate — Single Pair Ethernet (SPE).

SPE is being discussed in all the major communication special interest groups, so it makes sense that its being discussed within the IO-Link Consortium.  Why?  A couple of key factors: cable lengths and updated speeds.  By using SPE, we gain the Ethernet cable length advantage. So, instead of being limited to 20 meters, your IO-Link cabling could stretch to 100 meters!  Imagine the opportunities that opens in industrial applications.  It is possible that even longer runs will be achievable.  With 10 Mbit/s speed, to start, the update rate between IO-Link devices and the IO-Link master could be less than 0.1 millisecond.

Latency has been the Achilles heal in using IO-Link in high-speed applications, but this could eliminate that argument. It will still be IO-Link, the point-to-point communication protocol (master-to-device), but the delivery method would change. Using SPE would require new versions of IO-Links masters, with either all SPE ports or a combination of SPE and standard IO-Link ports. The cabling would also change from our standard prox cables to hybrid cables, containing a single twist Ethernet pair with two additional conductors for 24 volts DC.  We may even see some single channel converts, that convert standard IO-Link to SPE and vice versa.

There likely would have been pushback if this was discussed just five or ten years ago, but today, with new technology being released regularly, I doubt we see much resistance. We consumers are ready for this. We are already asking for the benefits of SPE and IO-Link SPE may be able to provide those advantages.

For more information, visit www.balluff.com.

Increasing Productivity in the Injection Molding Process

Part of calculating the productivity in an injection molding operation is to figure out the maximum number of items you’d be able to produce if everything worked perfectly. Unfortunately, “everything working perfectly” is not something you often see in manufacturing. How can you get closer to that ideal number? One answer lies in a little sensor which can monitor environmental conditions vital to your operation. With it you can reduce your machine downtime and the amount of scrap you produce.

Condition monitoring sensors seem to be taking the automation world by storm. These sensors take various measurements including temperature, ambient pressure, relative humidity, and vibration. They report the data digitally, which makes it easy to track performance. What used to require several sensors now requires only one.

Monitor humidity in plastic granule drying process

Following the plastic injection molding process from beginning to end we can see the usefulness of this one sensor. Plastic granules need to be dried before they go into the machine. If the moisture level is too high, it can cause splay marks to show up on the final product, which then has to be scrapped. This can be costly and can extend lead times if it is not detected early on. The condition monitoring sensor can track ambient humidity so you can stop that problem in its tracks before it creates waste and increases overhead.

Monitor temperature in the injection molding process

One of the biggest variables to any injection molding process is temperature. Some common temperature-related issues in injection molding include blistering, burn marks, degradation of the polymer used, stringiness, and warping. These are caused by temperature variations that cause the resin to be too hot or too cold. Condition monitoring sensors can detect swings in temperature to prevent products having to be scrapped.

Monitor vibration to detect mechanical wear

It’s clear that condition monitoring sensors can helpfully measure environmental factors, but what about mechanical wear? Vibration sensors can monitor mechanical wear on bearings, linear drives, gearboxes and much more by plotting vibration data. It’s even more effective if they measure vibration on more than one axis so you can see the direction of vibration and not just the overall amount. This way you can be proactive and plan your maintenance in advance instead of being in a constant reactive state, trying to patch problems as they come up. Using vibration data gathered by a condition monitoring sensor, you can avoid the costly consequences of unscheduled downtime.

In conclusion there are many different applications that condition monitoring sensors can be used for in injection molding operations. By tracking a variety of different measurements including vibration, temperature, and humidity, you will be able to improve the efficiency and productivity of your entire operation by using this one compact sensor. It provides a low-cost solution so that you can reduce the scrap that is cutting into your profits. And reduce the amount of downtime that causes so many unnecessary headaches. Put these smart sensors to work for you.

How RFID Can Error-Proof Appliance Assembly

Today, appliance manufactures are using RFID more frequently for error proofing applications and quality control processes.

Whether the appliance assembly process is automatic or semiautomatic, error-proofing processes using RFID are as important as the overall assembly processes. Now, RFID systems can be used to tell a PLC how well things are moving, and if the products and parts are within spec. This information is provided as an integral part of each step in the manufacturing process.

RFID systems installed throughout the manufacturing process provide a way of tracking not only what has happened, but what has gone right. RFID records where something has gone wrong, and what needs to be done to correct the problem.

Appliance manufacturers often need to assemble different product versions on the same production line. The important features of each part must be identified, tracked and communicated to the control system. This is most effectively done with an RFID system that stores build data on a small RFID tag attached to a build pallet. Before assembly begins, the RFID tag is loaded with the information that will instruct all downstream processes the correct parts that need to be installed.

Each part that goes into the appliance also has a RFID tag attached to it. As the build pallet moves down the assembly conveyor to each station, the tag on the build pallet is read to determine what assembly and error proofing steps are required. Often, this is displayed on an HMI for the operator. If the assembly requires testing, the results of those tests can be loaded into the data carrier for subsequent archiving. The operator scans the tag on each part as it is being installed. That data is then written to the tag on the build pallet. For example, in the washing machine assembly process, the washing machine body sits on the build pallet, and as it moves from station to station, the operators install different components like electronic boards, wiring harnesses, and motors. As each one of these components is installed, its RFID tag is scanned to make sure it is the correct part. If they install the wrong part, the HMI will signal the error.

RFID technology can also be used to reduce errors in the rework process. RFID tags, located on either on the assembly or the pallet, store information on what has been done to the appliance and what needs to be done. When an unacceptable subassembly reaches the rework area, the RFID tag provides details for the operator on what needs to be corrected. At the same time, the tag can signal a controller to configure sensors and tools, such as torque wrenches, to perform the corrective operations.

These are just a few examples of how appliance manufactures are using RFID for error proofing.

For more information, visit https://www.balluff.com/local/us/products/product-overview/rfid/.

Machine Vision: 5 Simple Steps to Choose the Right Camera

The machine vision and industrial camera market is offering thousands of models with different resolutionssizes, speeds, colors, interfaces, prices, etc. So, how do you choose? Let’s go through 5 simple steps which will ensure easy selection of the right camera for your application. 

1.  Defined task: color or monochrome camera  

2.  Amount of information: minimum of pixels per object details 

3.  Sensor resolution: formula for calculating the image sensor 

4.  Shutter technology: moving or static object 

5.  Interfaces and camera selector: lets pick the right model 

STEP 1 – Defined task  

It is always necessary to start with the size of the scanned object (X, Y), or you can determine the smallest possible value (d) that you want to distinguish with the camera.

For easier explanation, you can choose the option of solving the measurement task. However, the basic functionality can be used for any other applications.

In the task, the distance (D) between the centers of both holes is determined with the measurement accuracy (d). Using these values, we then determine the parameter for selecting the right image sensor and camera.

Example:
Distance (D) between 2 points with measuring accuracy (d) of 0.05 mm. Object size X = 48 mm (monochrome sensor, because color is not relevant here)

Note: Monochrome or color?
Color sensors use a Bayer color filter, which allows only one basic color to reach each pixel. The missing colors are determined using interpolation of the neighboring pixels. Monochrome sensors are twice as light sensitive as color sensors and lead to a sharper image by acquiring more details within the same number of pixels. For this reason, monochrome sensors are recommended if no color information is needed.

STEP 2 – Amount of information

Each type of application needs a different size of information to solve. This is differentiated by the minimum number of pixels. Lets again use monochrome options.

Minimum of pixels per object details

  • Object detail measuring / detection       3
  • Barcode line width                                           2
  • Datamatrix code module width                4
  • OCR character height                                    16

Example:
The measuring needs 3 pixels for the necessary accuracy (object detail size d). As necessary accuracy (d) which is 0.05 mm in this example, is imaged on 3 pixels.

Note:
Each characteristic or application type presupposes a minimum number of pixels. It avoids the loss of information through sampling blurs.

STEP 3 – Sensor resolution

We already defined the object size as well as resolution accuracy. As a next step, we are going to define resolution of the camera. It is simple formula to calculate the image sensor.

S = (N x O) / d = (min. number of pixels per object detail x object size) / object detail size

Object size (O) can be describe horizontally as well as vertically. Some of sensors are square and this problem is eliminated 😊

Example:
S = (3 x 48 mm) / 0.05 mm = 2880 pixels

We looked at the available image sensors and the closest is a model with resolution 3092 x 2080 => 6.4Mpixels image sensor.

Note:
Pay attention to the format of the sensor.

For a correct calculation, it is necessary to check the resolution, not only in the horizontal but also in the vertical axis.

 

STEP 4 – Shutter technology

Global shutter versus rolling shutter.

These technologies are standard in machine vision and you are able to find hundreds of cameras with both.

Rolling shutter: exposes the motive line-by-line. This procedure results in a time delay for each acquired line. Thus, moving objects are displayed blurrily in the resulting motive through the generated “object time offset” (compare to the image).

Pros:

    • More light sensitive
    • Less expensive
    • Smaller pixel size provides higher resolution with the same image format.

Cons:

    • Image distortion occurs on moving objects

Global shutter: used to get distortion-free images by exposing all pixels at the same time.

Pros:

    • Great for fast processes
    • Sharp images with no blur on moving objects.

Cons:

    • More expensive
    • Larger image format

Note:
The newest rolling shutter sensors have a feature called global reset mode, which starts the exposure of all rows simultaneously and the reset of each row is released simultaneously, also. However, the readout of the lines is equal to the readout of the rolling shutter: line by line.

This means the bottom lines of the sensor will be exposed to light longer! For this reason, this mode will only make sense, if there is no extraneous light and the flash duration is shorter or equal to the exposure time.

STEP 5 – Interfaces and camera selector

Final step is here:

You must consider the possible speed (bandwidth) as well as cable length of camera technology.

USB2
Small, handy and cost-effective, USB 2.0 industrial cameras have become integral parts in the area of medicine and microscopy. You can get a wide range of different variants, including with or without housings, as board-level or single-board, or with or without digital I/Os.

USB3/GigE Vision
Without standards every manufacturer does their own thing and many advantages customers learned to love with the GigE Vision standard would be lost. Like GigE Vision, USB3 Vision also defines:

    • a transport layer, which controls the detection of a device (Device Detection)
    • the configuration (Register Access)
    • the data streaming (Streaming Data)
    • the handling of events (Event Handling)
    • established interface to GenICam. GenICam abstracts the access to the camera features for the user. The features are standardized (name and behavior) by the standard feature naming convention (SFNC). Additionally, it is possible to create specific features in addition to the SFNC to differentiate from other vendors (quality of implementation). In contrast to GigE Vision, this time the mechanics (e.g. lockable cable connectors) are part of the standard which leads to a more robust interface.

I believe that these five points will help you choose the most suitable camera. Are you still unclear? Do not hesitate to contact us or contact me directly: I will be happy to consult your project, needs or any questions.