Magnetic Field Positioning Systems for Reliable, Accurate and Repeatable Absolute Position Feedback

Magnetic field positioning systems are increasingly popular due to their ability to provide reliable, accurate, and repeatable absolute position feedback.

These systems use magnetic field sensors to get a larger range of feedback across a pneumatic cylinder – a great alternative to traditional cylinder prox switches that may not work well in certain applications. They also allow for continuous monitoring of piston position in tight spaces, providing feedback in the form of analog voltage, current output, and IO-Link interface. And in many cases, these systems can replace the need for a linear transducer, making them a cost-effective solution for many industries.

One of the key benefits of magnetic field positioning systems is their versatility. They can be used in a wide range of industrial applications, such as:

    • Ultrasonic welding to validate set height with position feedback
    • Nut welding to verify set height with position feedback
    • Dispensing
    • Gripping for position feedback for different parts
    • Liner position indicators

While using these sensors greatly improves productivity in areas where prox sensors cannot provide the reliability needed, when selecting the magnetic field position system, it is important to consider the application requirements. The accuracy and feedback speed, for example, may vary depending on the application.

Magnetic field position systems are also available in different lengths. If the standard length does not meet requirements, you can choose a non-contact type that can be mounted on a slide with a magnetic trigger.

Overall, magnetic field positioning systems are an excellent choice for any industry that requires reliable, accurate, and repeatable absolution position feedback. With their versatility and flexibility, they are sure to improve productivity and efficiency in a wide range of applications.

Choosing the Right Sensor for Measuring Distance

Distance-measuring devices help with positioning, material flow control, and level detection. However, there are several options to consider when it comes to choosing the correct sensor technology to measure distance. Here I’ll cover the three most commonly used types in the industrial automation world today, including photoelectric, ultrasonic, and inductive.

Photoelectric sensors

Photoelectric sensors use a light source, such as a laser or light-emitting diode, to reflect the light off an object’s surface to calculate the distance between the face of the sensor and the object itself. The two basic principles for how the sensor calculates the distances are the time of flight (TOF) and triangulation.

    • Time of flight photoelectric distance measurement sensors derive the distance measurement based on the time it takes the light to travel from the sensor to the object and return. These sensors are used to measure over long distances, generally in the range between 500 millimeters and up to 5 meters, with a resolution between 1 to 5 millimeters, depending on the sensor specifications. Keep in mind that this sensor technology is also used in range-finding equipment with a much greater sensing range than traditional industrial automation sensors.

    • In the triangulation measurement sensor, the sensor housing, light source, and light reflection form a triangle. The distance measurement is based on the light reflection angle within its sensing range with high accuracy and resolution. These sensors have a much smaller distance measurement range that is limited to between 20 and 300 millimeters, depending on the sensor specifications.

The pros of using photoelectric distance measurement sensors are the range, accuracy, repeatability, options, and cost. The main con for using photoelectric sensors for distance measurement is that they are affected by dust and water, so it is not recommended to use them in a dirty environment. The object’s material, surface reflection, and color also affect its performance.

Photoelectric distance measurement sensors are used in part contouring, roll diameter measurement, the position of assemblies, thickness detection, and bin-level detection applications.

Ultrasonic sensors

Ultrasonic distance sensors work on a similar principle as photoelectric distance sensors but instead of emitting light, they emit sound waves that are too high for humans to hear, and they use the time of flight of reflecting sound wave to calculate the distance between the object and the sensor face. They are insensitive to the object’s material, color, and surface finish. They don’t require the object or target to be made of metal like inductive position sensors (see below). They can also detect transparent objects, such as clear bottles or different colored objects, that photoelectric sensors would have trouble with since not enough light would be reflected back to reliably determine the distance of an object. The ultrasonic sensors have a limited sensing range of approximately 8 meters.

A few things to keep in mind that negatively affect the ultrasonic sensor is when the object or target is made of sound-absorbing material, such as foam or fabric, where the object absorbs enough soundwave emitted from the sensor making the output unreliable. Also, the sensing field gets progressively larger the further away it gets from the sensing face, thus making the measurement inaccurate if there are multiple objects in the sensing field of the sensor or if the object has a contoured surface. However, there are sound-focusing attachments that are available to limit the sensing field at longer distances making the measurements more accurate.

Inductive sensors

Inductive distance measurement sensors work on the same principle as inductive proximity sensors, where a metal object penetrating the electromagnetic field will change its characteristics based on the object size, material, and distance away from the sensing face. The change of the electromagnetic field detected by the sensor is converted into a proportional output signal or distance measurement. They have a quick response time, high repeatability, and linearity, and they operate well in harsh environments as they are not affected by dust or water. The downside to using inductive distance sensors is that the object or target must be made of metal. They also have a relatively short measurement range that is limited to approximately 50 millimeters.

Several variables exist to consider when choosing the correct sensor technology for your application solution, such as color, material, finish, size, measurement range, and environment. Any one of these can have a negative effect on the performance or success of your solution, so you must take all of them into account.

Choosing a Contactless Sensor to Measure Objects at a Distance

Three options come to mind for determining which contactless sensor to use when measuring objects at a distance: photoelectric sensors, ultrasonic sensors, and radar detection. Understanding the key differences among these types of technologies and how they work can help you decide which technology will work best for your application.

Photoelectric sensor

The photoelectric sensor has an emitter that sends out a light source. Then a receiver receives the light source. The common light source LED (Light Emitting Diodes), has three different types:

    • Visible light (usually red light) has the shortest wavelength, but allows for easy installment and alignment as the light can be seen.
    • Lasers are amplified beams that can deliver a large amount of energy over a distance into a small spot, allowing for precise measurement.
    • Infrared light is electromagnetic radiation with wavelengths longer than visible light, generally making them invisible to the humans. This allows for infrared to be used in harsher environments that contain particles in the air.

Along with three types of LEDs, are three models of photoelectric sensors:

    • The retro-reflective sensor model includes both an emitter and receiver in one unit and a reflector across from it. The emitter sends the light source to the reflector which then reflects the light back to the receiver. When an object comes between the reflector and the emitter, the light source cannot be reflected.
    • The through-beam sensor has an emitter and receiver in two separate units installed across from the emitter. When an object breaks the light beam, the receiver cannot receive the light source.
    • The diffuse sensor includes an emitter and receiver built into one unit. Rather than having a reflector installed across from it the light source is reflective off the object back to the receiver.

The most common application for photoelectric sensors is in detecting part presence or absence. Photoelectric sensors do not work well in environments that have dirt, dust, or vibration. They also do not perform well with detecting clear or shiny objects.

Ultrasonic sensor

The ultrasonic sensor has an emitter that sends a sound wave at a frequency higher than what a human can hear to the receiver.  The two modes of an ultrasonic sensor include:

    • Echo mode, also known as a diffused mode, has an emitter and receiver built into the same unit. The object detection works with this mode is that the emitter sends out the sound wave, the wave then bounces off the target and returns to the receiver. The distance of an object can be determined by timing how long it takes for the sound wave to bounce back to the receiver.
    • The second type of mode is the opposed mode. The opposed mode has the emitter and receiver as two separate units. Object detection for this mode works by the emitter will be set up across from the receiver and will be sending sound waves continuously and an object will be detected once it breaks the field, similarly to how photoelectric sensors work.

Common applications for ultrasonic sensors include liquid level detection, uneven surface level detection, and sensing clear or transparent objects. They can also be used as substitutes for applications that are not suitable for photoelectric sensors.

Ultrasonic sensors do not work well, however, in environments that have foam, vapors, and dust. The reason for this is that ultrasonic uses sound waves need a medium, such as air, to travel through. Particles or other obstructions in the air interfere with the sound waves being produced. Also, ultrasonic sensors do not work in vacuums which don’t contain air.

Radar detection

Radar is a system composed of a transmitter, a transmitting antenna, a receiving antenna, a receiver, and a processor. It works like a diffuse mode ultrasonic sensor. The transmitter sends out a wave, the wave echoes off an object, and the receiver receives the wave. Unlike a sound wave, the radar uses pulsed or continuous radio waves. These wavelengths are longer than infrared light and can determine the range, angle, and velocity of objects. radar also has a processor that determines the properties of the object.

Common applications for radar include speed and distance detection, aircraft detection, ship detection, spacecraft detection, and weather formations. Unlike ultrasonic sensors, radar can work in environments that contain foam, vapors, or dust. They can also be used in vacuums. Radio waves are a form of electromagnetic waves that do not require a transmission medium to travel. An application in which radar does not perform well is detecting dry powders and grains. These substances have low dielectric constants, which are usually non-conductive and have low amounts of moisture.

Choosing from an ultrasonic sensor, photoelectric sensor, or radar comes down to the technology being used. LEDs are great at detecting part presences and absence of various sizes. Sound waves are readily able to detect liquid levels, uneven surfaces, and part presence. Electromagnetic waves can be used in environments that include particles and other substances in the air. It also works in environments where air is not present at all. One technology is not better than the other; each has its strengths and its weaknesses. Where one cannot work, the others typically can.

Shedding Light on Different Types of Photoelectric Sensors

Photoelectric sensors have been around for more than 50 years and are used in everyday things – from garage door openers to highly automated assembly lines that produce the food we eat and the cars we drive.

The correct use of photoelectric sensors in a manufacturing process is important to ensure machines can perform their required actions. Over the years they have evolved into many different forms.

But, how do you know which is the right sensor for your application?  Let’s take a quick look at the different types and why you would choose one over another for your needs.

Diffuse sensors

    • Ideal for detecting contrast differences, depending on the surface, color, and material
    • Detects in Light-On or Dark-On mode, depending on the target
    • Economical and easy to mount and align, thanks to visible light beams
    • Shorter ranges as compared to retroreflective and through-beam sensors
    • IR (Infrared) light beams available for better detection in harsh environments
    • Laser light versions are available for more precise detection when needed
    • Mounting includes only one electrical device

Diffuse sensor with background suppression

    • Reliable object detection with various operating ranges, and independent of surface, color, and material
    • Detects objects against very similar backgrounds – even if they are very dark against a bright background
    • Almost constant scanning range even with different reflectance
    • Only one electrical device without reflectors or separate receivers
    • Good option if you cannot use a through-beam or retroreflective sensor
    • With red light or the laser red light that is ideally suited for detecting small parts

Retroreflective sensors

    • Simple alignment thanks to generous mounting tolerances
    • Large reflectors for longer ranges
    • Reliable detection, regardless of surface, color, and material
    • Polarized light filters are available to assist with detecting shiny objects
    • Mounting includes only one electrical device, plus a reflector
    • Most repeatable sensor for clear object detection; light passes through clear target 2X’s giving a greater change in light received by the sensor

Through-beam sensors

    • Ideal for positioning tasks, thanks to excellent reproducibility
    • Most reliable detection method for objects, especially on conveyor applications
    • Extremely resistant to contamination and suitable for harsh environments
    • Ideally suited for large operating ranges
    • Transmitter and receiver in separate housings

Fork sensors

    • Different light types (red light, infrared, laser)
    • Robust metal housing
    • Simple alignment to the object
    • High optical resolution and reproducibility
    • Fork widths in different sizes with standardized mounting holes
    • Identical mechanical and optical axes
    • The transmitter and receiver are firmly aligned to each other, yielding high process reliability

The next time you need to choose a photoelectric sensor for your manufacturing process, consider these features of each type to ensure the sensor is performing optimally in your application.

Capacitive, the Other Proximity Sensor

What is the first thing that comes to mind if someone says “proximity sensor?” My guess is the inductive sensor, and justly so because it is the most used sensor in automation today. There are other technologies that use the term proximity in describing the sensing mode, including diffuse or proximity photoelectric sensors that use the reflectivity of the object to change states and proximity mode of ultrasonic sensors that use high-frequency sound waves to detect objects. All these sensors detect objects that are in close proximity to the sensor without making physical contact. One of the most overlooked or forgotten proximity sensors on the market today is the capacitive sensor.

Capacitive sensors are suitable for solving numerous applications. These sensors can be used to detect objects, such as glass, wood, paper, plastic, or ceramic, regardless of material color, texture, or finish. The list goes on and on. Since capacitive sensors can detect virtually anything, they can detect levels of liquids including water, oil, glue, and so forth, and they can detect levels of solids like plastic granules, soap powder, sand, and just about anything else. Levels can be detected either directly, when the sensor touches the medium, or indirectly when it senses the medium through a non-metallic container wall.

Capacitive sensors overview

Like any other sensor, there are certain considerations to account for when applying capacitive, multipurpose sensors, including:

1 – Target

    • Capacitive sensors can detect virtually any material.
    • The target material’s dielectric constant determines the reduction factor of the sensor. Metal / Water > Wood > Plastic > Paper.
    • The target size must be equal to or larger than the sensor face.

2 – Sensing distance

    • The rated sensing distance, or what you see in a catalog, is based on a mild steel target that is the same size as the sensor face.
    • The effective sensing distance considers mounting, supply voltage, and temperature. It is adjusted by the integral potentiometer or other means.
    • Additional influences that affect the sensing distance are the sensor housing shape, sensor face size, and the mounting style of the sensor (flush, non-flush).

3 – Environment

    • Temperatures from 160 to 180°F require special considerations. The high-temperature version sensors should be used in applications above this value.
    • Wet or very humid applications can cause false positives if the dielectric strength of the target is low.
    • In most instances, dust or material buildup can be tuned out if the target dielectric is higher than the dust contamination.

4 – Mounting

    • Installing capacitive sensors is very similar to installing inductive sensors. Flush sensors can be installed flush to the surrounding material. The distance between the sensors is two times the diameter of the sensing distance.
    • Non-flush sensors must have a free area around the sensor at least one diameter of the sensor or the sensing distance.

5 – Connector

    • Quick disconnect – M8 or M12.
    • Potted cable.

6 – Sensor

    • The sensor sensing area or face must be smaller or equal to the target material.
    • Maximum sensing distance is measured on metal – reduction factor will influence all sensing distances.
    • Use flush versions to reduce the effects of the surrounding material. Some plastic sensors will have a reduced sensing range when embedded in metal. Use a flush stainless-steel body to get the full sensing range.

These are just a few things to keep in mind when applying capacitive sensors. There is not “a” capacitive sensor application – but there are many which can be solved cost-effectively and reliably with these sensors.

Converting Analog Signals to Digital for Improved Performance

We live in an analog world, where we experience temperatures, pressures, sounds, colors, etc., in seemingly infinite values. There are infinite temperature values between 70-71 degrees, for example, and an infinite number of pressure values between 50-51 psi.

Sensors today continue to use analog circuitry to measure a natural process, but more often, the electrical analog signal is then converted to a digital (binary) signal.

How a signal is converted from analog to digital?

A variety of mechanical and electrical transducer technologies, such as Bourdon tube, piezoresistive, manometers, strain gages, and capacitive can be found in a typical pressure sensor. Any one of these can be used to sense pressure and convert the physical pressure into an analog electrical signal. The analog output continuously varies as the pressure rises and lowers. For many sensors of the past, the story ends here. The sensor works well if certain precautions are met, but enhanced features are limited. This sensor would be comprised of electrical components, such as diodes, capacitors, op-amps, and resistors, with typical signal outputs of 0-5VDC, 0-10VDC, +/- 10V, 4-20mA, 0-20mA, etc.

Analog output sensors provide an infinitely varying signal and converting it to digital cannot improve the accuracy of the measured value. Nor will it increase the amount of information we receive from the natural world. So why do we do it?

Why convert to digital signals?

There are several good reasons for converting analog to digital signals. Analog uses more power than digital and it’s more difficult to encrypt, decode, or synchronize. Analog outputs also have a slow rate of transmission. But typically, the biggest reasons are that analog signals weaken and pick up electrical noise as they traverse, and they’re difficult to process and store.

Noises and transmission rates

Electrical energy from motors, contactors, and other electrical devices can become induced into the sensor’s analog electronics, creating noise on the signal. Analog amplifiers can increase the signal strength to extend transmission distances, but it also amplifies the induced noise. The transmission of digital signals, on the other hand, is faster and has negligible distortion. And although a digital signal may need an amplifier for long lengths, too, digital regeneration can more easily correct any 0/1 errors and amplify the signal without amplifying any noise.

Converting a continuously variable signal into 1s and 0s

An analog-to-digital converter (ADC) is an integrated circuit that performs the conversion. While this process includes many important steps, and there are several popular techniques, each has three main processes: sampling, quantizing, and encoding.

Sampling is a process used to select a subset of values from a larger set. In our case, we are starting with an infinite set of values from the analog signal and want to capture a snapshot of the signal at certain time intervals. With a sampling rate of 500Hz, the ADC will grab and hold a value from the analog signal 500 times per second.

Once the signal is sampled, it is quantized. This involves mapping the sample from a set of infinite signal values down to a finite number of values. If there were 100 available increments for quantizing a 0-5vdc signal, for example, the infinite output would now be reduced to 100 available signal level choices with 0 volts mapping as 0, 2.5 volts mapping as 50, and 5 volts as 99.

Lastly, the quantized signal level is encoded to binary form, where it can benefit from the processing, storage, and transmission advantages that come with a digital signal. A quantized level of 50, encoding with an 8-bit processor, would be 00011001, equating to a 2.5vdc signal.

In actual practice, we do not use 100 increments to quantize. The ADC, which is based on the number of bits within the processor within the ADC chip, determines the amount of quantizing increments or levels. Eight bits provide 256 increments. Twelve bits provide 4096 increments or steps, as it is also referred.

Is 12 bits worth of increments (4096 steps) enough resolution?

5VDC /4096 steps = .00122V/step or 1.22mV/step

In most applications, a small step of 1.22mV is acceptable. The original analog signal is now sampled at a specific time, and an increment closest to the value is chosen as the signal level. The quantizing process in this case will round the infinite analog value that was sampled to the nearest multiple of 1.22mV.

The output signal is now a square wave, rather than the original sinusoidal. The peak of each square wave is always the same amplitude, with the peak of the wave representing a “1” and the trough or zero amplitude being a “0.”

The sensor output, now digitized, is capable of further processing, offering enhanced product features such as faster transmission rates, negligible distortion, and the ability to communicate to advanced systems such as IO-Link.

A digital to analog converter (DAC) can convert the signal back to analog, but complete restoration is no longer possible due to the samples taken only at specific times, and the quantizing step rounding off to the nearest increment.

So, the next time you see a spec sheet that says “12-bit resolution,” rest assured you are working with a sensor that has some enhanced capabilities.

Inductive Sensors and Their Unlimited Uses in Automation

Inductive sensors (also known as proximity sensors or proxes) are the most commonly used sensors in mechanical engineering and industrial automation. When they were invented in the 1960s, they marked a milestone in the development of control systems. In a nutshell, they generate an electromagnetic field that reacts to metal targets that approach the sensor head. They even work in harsh environments and can solve versatile applications.

There are hardly any industrial machines that work without inductive sensors. So, what can be solved with one, two, three, or more of them?

What can you do with one inductive sensor?

Inductive sensors are often used to detect an end position. This could be in a machine for end-of-travel detection, but also in a hydraulic cylinder or a linear direct drive as an end-of-stroke sensor. In machine control, they detect many positions and trigger other events. Another application is speed monitoring with a tooth wheel.

What can you do with two inductive sensors?

By just adding one more sensor you can get the direction of rotational motion and take the place of a more expensive encoder. In a case where you have a start and end position, this can also be solved with a second inductive sensor.

What can you do with three inductive sensors?

In case of the tooth wheel application, the third sensor can provide a reference signal and the solution turns into a multiturn rotary encoder.

What can I do with four inductive sensors and more?

For multi-point positioning, it may make sense to switch to a measurement solution, which can also be inductive. Beyond that, an array of inductive sensors can solve identification applications: In an array of 2 by 2 sensors, there are already 16 different unique combinations of holes in a hole plate. In an array of 3 by 3, it would be 512 combinations.

Detecting Liquid Media and Bubbles Using Optical Sensors

In my line of work in Life Sciences, we often deal with liquid media and bubble detection evaluation through a vessel or a tube. This can be done by using the absorption principle or the refraction principle with through-beam-configured optical sensors. These are commonly embedded in medical devices or lab instruments.

This configuration provides strong benefits:

    • Precise sensing
    • Ability to evaluate liquid media
    • Detect multiple events
    • High reliability

How does it work?

The refraction principle is based on the media’s refraction index. It uses an emitted light source (Tx) that is angled to limit the light falling on the receiver (Rx, Figure 1). When the light passes through a liquid, refraction causes the light to focus on the receiver as a beam (known as a “beam-make” configuration). All liquids and common vessel materials (silicon, plastic, glass, etc.) have a known refraction index. These sensors will detect those refraction differences and output a signal.

The absorption principle is preferred when a media’s absorption index is high. First, a beam is established through a vessel or tube (Figure 2). Light sources in the 1500nm range work best for aqueous-based media such as water. As a high absorption index liquid enters the tube, it will block the light (known as a beam-break configuration). The sensor detects this loss of light.

Discrete on-off signals are easily used by a control system. However, by using the actual light value information (commonly analog), more data can be extracted. This is becoming more popular now and can be done with either sensing principle. By using this light-value information, you can differentiate between types of media, measure concentrations, identify multiple objects (e.g., filter in an IV and the media) and much more.

There is a lot to know about through-beam sensors, so please leave a comment below if you have questions on how you can benefit from this technology.

Evolution of Pneumatic Cylinder Sensors

Today’s pneumatic cylinders are compact, reliable, and cost-effective prime movers for automated equipment. They’re used in many applications, such as machinery, material handling, assembly, robotics, and medical. One challenge facing OEMs, integrators and end users is how to detect reliably whether the cylinder is fully extended, retracted, or positioned somewhere in between before allowing machine movement.

A widely used method for cylinder position detection is to attach magnetically actuated switches or sensors to the sides of the cylinder using brackets, or by inserting them into a slot extruded into the body of the cylinder. Magnetic field sensors detect an internal magnet that is mounted on the moving piston through the aluminum cylinder wall.

The selection of which type of magnetic sensors to use depends on your application needs and specific data requirements.

Magnetic Sensor Types

Reed switches

The reed switch is the most simplistic and most often used end-of-stroke sensor available on the market. It consists of two flattened ferromagnetic nickel and iron reed elements enclosed in a hermetically sealed glass tube. The tube aids in minimizing contact arcing and prevents moisture from getting to the switch elements. As an axially aligned magnet approaches the switch element, the reed elements are magnetized and attracted together completing the circuit.

AMR and GMR sensors

Most cylinder manufacturers and OEMs use electronic sensors with either magnetoresistive technology (AMR) or giant magnetoresistive (GMR). Both versions are based on a change in resistance. One advantage of these sensors is that they will work with the axially magnetized magnet and, in some cases, the radially magnetized magnet. GMR sensors can be physically smaller than the AMR sensors. They are more sensitive, more precise and have a better hysteresis. Versions exist that provide reverse polarity protection, overload protection, and short circuit protection.

The initial cost of an AMR or GMR sensor may be slightly more than a reed sensor, however, this cost is increasingly less, especially if you figure the cost of downtime when the reed switch fails. AMR and GMR sensors are also three-wire devices, unlike the two-wire reed switches. In the end, the AMR and GMR sensors are the better solution since there are no moving parts and they typically last much longer than the reed switch.

Position detection sensors for both C-slots and T-slots

Pneumatic cylinders typically have either a C-slot or T-slot feature in the extrusion of the cylinder body. Many sensor housings have these same housing profiles and the sensor can either be dropped into the slot from above and tightened with a screw or slid in from the end of the cylinder provided there is no end plate. For round cylinders or tie rod cylinders, additional brackets are available that can use either a C-slot or T-slot sensor. This allows for commonality of sensors for end users and OEMs to meet the needs of many applications and reduce the number of sensor part numbers and inventory.

Today, there are more options than ever for piston position detection in pneumatic cylinders, including different housing styles to meet the cylinder extrusions. Also available are two sensors – one for extended and one for retracted – that share a single, four-pin connection. These magnetic sensors are also available now with weld field immunity for harsh welding applications.

Technology has advanced as well. Now cylinder sensors can be taught to trigger at certain points along the travel of the piston. The user simply moves the piston to a desired location and presses a button to set the switching location. This teachable sensor can also be connected to IO-Link, allowing up to eight switching points for flexibility in several applications.

Over the years, many users have abandoned reed switches, due to their failure rate, in favor of mechanical or inductive sensors to detect pneumatic cylinder position. AMR and GMR sensors are smaller, faster, easy to integrate, and are much more reliable. With the vast improvements in sensor technology, AMR and GMR sensors should now be considered the primary solution for detecting cylinder position.

Add Depth to Your Processes With 3D Machine Vision

What comes to mind first when you think of 3D? Cheap red and blue glasses? Paying extra at a movie theater? Or maybe the awkward top screen on a Nintendo 3DS? Neither industrial machine vision nor robot guidance likely come to mind, but they should.

Advancements in 3D machine vision have taken the old method of 2D image processing and added literal depth. You become emerged into the application with true definition of the target—far from what you get looking at a flat image.

See For Yourself

Let’s do an exercise: Close one eye and try to pick up an object on your desk by pinching it. Did you miss it on the first try? Did things look foreign or off? This is because your depth perception is skewed with only one vision source. It takes both eyes to paint an accurate picture of your surroundings.

Now, imagine what you can do with two cameras side by side looking at an application. This is 3D machine vision; this is human.

How 3D Saves the Day

Robot guidance. The goal of robotics is to emulate human movements while allowing them to work more safely and reliably. So, why not give them the same vision we possess? When a robot is sent in to do a job it needs to know the x, y and z coordinates of its target to best control its approach and handle the item(s). 3D does this.

Part sorting. If you are anything like me, you have your favorite parts of Chex mix. Whether it’s the pretzels or the Chex pieces themselves, picking one out of the bowl takes coordination. Finding the right shape and the ideal place to grab it takes depth perception. You wouldn’t use a robot to sort your snacks, of course, but if you need to select specific parts in a bin of various shapes and sizes, 3D vision can give you the detail you need to select the right part every time.

Palletization and/or depalletization. Like in a game of Jenga, the careful and accurate stacking and removing of parts is paramount. Whether it’s for speed, quality or damage control, palletization/ depalletization of material needs 3D vision to position material accurately and efficiently.

I hope these 3D examples inspire you to seek more from your machine vision solution and look to the technology of the day to automate your processes. A picture is worth a thousand words, just imagine what a 3D image can tell you.