Reducing Assembly Line Mistakes With the Error Proofing Platform Station

About 18 months ago, one of the major automotive companies came to the Indicon Conference looking for a way to decrease mistakes on the assembly line. They found a solution in a concept named the Error Proofing Platform Station (EPP).

How it works

The EEP works by using a bar code reader, in this case a scanner, to verify that the correct parts are being used in the assembly process. The scanner connects to an RS232-to-digital-converter module, and from there to an IO-Link networking block which enables two-way communication of information with the PLC. IO-Link blocks can connect hundreds of devices, versus traditional blocks that can only connect eight to sixteen devices. This greatly simplifies the hardware, cabling and installation costs.

EEP station design

The overall design of this EPP station grabbed the automotive company’s attention for several reasons.  It is effective both in its simplicity as well as the small footprint that it takes up. The design of the components allows it to sit on the plant floor instead of having to be installed in a cabinet like previous designs. They especially liked the wiring design where a single cable goes from the IO-Link block at is managed by a single IP address back to the PLC. Should one of the devices fail, you simply replace a single cable or device and move on.

The old days of unwinding the cables and spending hours trying to decipher which cable goes to which device are gone.

The current roll-out has been at four separate plants with plans for 10 more in the next four years. Expansion of this innovation is being targeted toward the other major manufacturers.

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.

IO-Link Safety: What It Is and Isn’t

Comparing “IO-Link” and “Safety” to “IO-Link Safety”

There are many I/O blocks that have “IO-Link” and “Safety” in their descriptions, which can cause some confusion about which safety features they include. Here’s an overview of different safety-named blocks and how they compare to IO-Link Safety.

Safety Network Blocks

These blocks have I/O ports that use Pin 4 and Pin 2 as OSSD signals (safety ports). OSSD—output switching signal devices—send 24-volt signals over two wires to confirm that a device is operating in a safe condition. If 0 volts are detected in either signal, besides their safety-checking 0-volt pulses, it’s read as a safety event that signals the machine to go into a safe state. Safety network blocks are only for standard (non-network) safety devices. These blocks communicate directly back to a Safety Controller over safety protocols like CIP Safety, PROFIsafe, etc. These blocks typically can monitor between 8-16 standard safety devices. There is no intelligence built into the safety devices.

Safety Network Blocks with IO-Link

Blocks in this category usually have a mixture of I/O ports on them. The ports can range from standard I/O to standard IO-Link communication, and in addition, include ports that use Pin 4 and Pin 2 as OSSD signals (safety ports). These blocks communicate over the safety protocols with only a few ports to connect standard (non-network) safety devices. There is some versatility with these blocks since you can wire standard sensors, IO-Link devices, and safety devices to it. The drawback is, you will always run short of the port style you need and, in the end, use more blocks to cover either the safety or IO-Link needs of the application. There is no intelligence built into the safety devices.

Safety over IO-Link Blocks

In this system/architecture, there are standard IO-Link Masters communicating to the Safety PLCs/Controllers over standard protocols like EtherNet/IP, PROFINET, etc. Connected to the IO-Link Ports of these Masters are Safety over IO-Link devices, currently limited to only Safety over IO-Link hubs. The Safety PLCs/Controllers communicate via safety protocols like PROFIsafe to the standard IO-Link Master, and then using the IO-Link communication channel, they bridge the gap to the Safety over the IO-Link hub via the “black channel.” These Safety over IO-Link hub’s ports use Pin 4 and Pin 2 as OSSD signals (safety ports), so standard (non-network) safety devices can be connected. This system provided a “gap filler” while IO-Link Safety was being developed. In this system/architecture, the standard IO-Link Masters allowed standard IO-Link devices and Safety over IO-Link hubs to be connected to any ports. This brought even more versatility to an application and the beginnings of the benefits of IO-Link. Still, there is no intelligence built into the safety devices.

IO-Link Safety

IO-Link Safety adds a safety communication layer to IO-Link. The difference between this and Safety over IO-Link is that this safety layer applies to both the IO-Link Master and IO-Link Safety devices. Within a CIP Safety or PROFIsafe network, the safety communication protocol has top priority over standard EtherNet/IP or PRIFONET data if both are existing on the same physical network. The same is true for IO-Link Safety: both standard and safety IO-Link protocols can exist on the same physical cable between the IO-Link Master ports and IO-Link Safety devices, with IO-Link Safety carrying the top priority. For a deep dive into the IO-Link Safety protocol, I suggest visiting the IO-Link Consortium’s website at io-link.com. In this system/architecture, you have IO-Link Safety Masters, which communicate to the Safety PLCs/Controllers over safety protocols like CIP Safety, PROFIsafe, etc. The ports on the Masters can utilize Pin 4 and Pin 2 as OSSD signals (safety ports), so standard (non-network) safety devices can be connected. Pin 4 can also be used to carry standard IO-Link and IO-Link Safety communication to standard IO-Link devices and IO-Link Safety devices, respectively. This allows for the most versatile safety solution in the market–IO-Link Safety Masters that can accept standard (non-network) safety devices, standard IO-Link devices, and IO-Link Safety devices. Intelligence in the IO-Link Safety devices is now available.

Benefits of IO-Link Safety

    • IO-Link Safety devices are fieldbus neutral: you just need to specify the IO-Link Safety Master to match the Safety PLCs/Controllers protocol.
    • IO-Link Safety Master port versatility: standard (non-network) safety devices, standard IO-Link devices, and IO-Link Safety devices can be connected.
    • Parameter storage: standard IO-Link and IO-Link Safety device’s parameters can be stored for ease of device replacement.
    • Smart IO-Link Safety device data: more data available, like internal temperature, humidity, number of cycles, power consumption, diagnostics, etc.
    • Simplified wiring: IO-Link Safety devices are still connected to the IO-Link Master port with a standard 3 to 4 conductor cable.
    • IIoT fit: IO-Link Safety gives more visibility to upper-level systems like SCADA, allowing safety device-level monitoring.

I am looking forward to seeing how quickly IO-Link Safety will be accepted, with how IO-Link numbers have skyrocketed over the last few years. The future looks great for IO-Link with IO-Link Safety, IO-Link Wireless and in the future, Single-Pair Ethernet (SPE). With all these new capabilities, what application can’t IO-Link support?

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.

Using Guided Format Change to Improve Changeover and Productivity

Long before Covid, we were seeing an increase in the number of packaging SKUs. In 2019, Packaging Digest reported an estimated 42% increase in SKUs in the food and beverage industry.

Since Covid, there has been a further explosion of new packaging sizes, especially in the food and beverage marketplace. Food manufacturers have gotten very creative. Instead of raising prices due to the higher costs of goods, for example, they can reduce the size of product packages while keeping the consumer prices the same.

Many of today’s production machines are not equipped to changeover as quickly and as accurately to meet the demand of the marketplace. Manufacturers now face the challenge of “semi-automating” their existing machines, as opposed to procuring new machines or adding expensive motors to existing machines. One solution is to digitalize change points on existing machines.

Companies are looking to reduce the amount of time and the mistakes that occur when doing product changeovers. Allowing for operator guidance and position measurement can reduce your time and enhance your accuracy of those changeover events. Measurements are then tied to the recipe and the operator becomes the prime mover.

Guided Format Change

There are lots of technologies out there for helping with guided format change, such as automated position measurement, machine position, distance measurement, linear measurement, and digitalized rotary encoders.


As you are likely quite aware, there are often scales, marks, etc., written onto machines that don’t provide the greatest degree of accuracy. Introducing digitalized position and distance sensing can help you reduce time and limit errors during changeovers.

Change Part Identification

The other side of changeover is change part identification. Quite often during this process parts on the machine must be exchanged. Using the wrong change part can result in mistakes, waste, and delays, and can even damage existing machines.

Technologies, such as RFID, can help ensure the correct change part is chosen and added to the machine. During a recipe change, the operator can then validate that all the correct parts are installed before the startup of the next product run.

Guided format change is a cost-effective way to reduce changeover time and increase productivity either by retrofitting your existing machines or even new machines.

Sensor Mounting Made Easy

So, you’ve figured out the best way to detect the product shuttle paddle in your cartoning/packaging machine needs a visible red laser distance sensor. It’s taken some time to validate that this is the right sensor and it will be a reliable, long-term solution.

But then you realize there are some mechanical issues involved with the sensor’s placement and positioning that will require a bit of customization to mount it in the optimal location. Now things may have just become complicated. If you can’t design the additional mounting parts yourself, you’ll have to find someone who can. And then you have to deal with the fabrication side. This all takes time and more effort than just buying the sensor.

Or does it?

Off-the-shelf solutions

It doesn’t have to be that complex. There are possible off-the-self solutions you can consider that will make this critical step of providing a reliable mounting solution – possibly as straightforward as choosing the right sensor. Multiple companies offer sensor mounting systems that accommodate standard sensor brackets. Over the years, companies have continued to develop new mounting brackets for many of their sensor products, from photoelectric sensors and reflectors to proximity sensors to even RFID heads and linear transducers.

So it’s only natural to take that one step further and create a mounting apparatus and system that not only provides a mounting bracket, but also a stable platform that incorporates the device’s mounting bracket with things like stand-off posts, adjustable connection joints, and mounting bases. Such a flexible and extensive system can solve mounting challenges with parts you can purchase, instead of having to fabricate.

Imagine in the example above you need to mount the laser distance sensor off the machine’s base and offset it in a way that doesn’t interfere with the other moving parts of the cartoner. Think of these mounting systems and parts as a kind of Erector Set for sensing devices. You can piece together the required mounting bracket with a set of brace or extension rods and a mounting base that raises the sensor up and off the machine base and even angles it to allow for pointing at the target in the most optimal way.

The following are some mounting solutions for a variety of sensors:

These represent only a small number of different ways to mix and match sensor device brackets and mounting components to find a solid, reliable and off-the-shelf mounting solution for your next mounting challenge. So before considering the customization route, next time take a look at what might already be out there for vendors. It could make your life a lot simpler.

Industrial Machinery Failure Types and Implications for Maintenance Approaches

Industrial machinery can fail in many different ways and for many different reasons. For critical and/or expensive equipment, it is a major challenge to find a way to detect potential failures before they happen and to take action to prevent or minimize the effects. Closely tied to this is the tradeoff between the cost of detection and the cost of failure. We discussed some of these tradeoffs in the blog “Condition Monitoring & Predictive Maintenance: Cost-Benefit Tradeoffs.”

When assessing how equipment might fail, several industry studies* have identified six primary failure types which may be considered:

    • Type A: Lower probability of failure in early- and mid-life of the asset, with a dramatic increase in probability of failure in late-life. This is typical for mechanical devices, such as engines, fans, compressors, and machines.
    • Type B: Higher initial probability of failure when the asset is new, with a much lower/steady failure probability over the rest of the asset’s life. This is often the profile for electronic devices such as computers, PLCs, etc.
    • Type C: Lower initial probability of failure when the asset is new, with an increase to a steady failure probability in mid- and late-life. These are often devices with high stress work conditions, such as pressure relief valves.
    • Type D: Consistent probability of failure throughout the asset life, similar failure probability in early-, mid- and late-life. This can cover many types of industrial machines, often with stable, proven design and components.
    • Type E: Higher probability of failure in early- and late-life, a lower and constant probability of failure in mid-life (often called a “bathtub curve”). This can be devices that “settle in” after a wear-in period and then experience higher failures at the end of life, such as bearings.
    • Type F: Lower probability of failure when new, with a gradual increase over time and without the steep increase in failure probability at the end of life of Type A. This is often typical where age-based wear is steady and gradual in equipment such as turbine engines and structural components (pressure vessels, beams, etc.).

Age-related and non-age-related failures

These six failure types fall into two categories: age-related and non-age-related failures. The studies show that 15-30% of failures are age-related (Types A, E & F) and 70-85% of failures are non-age-related (Types B, C & D). The age-related failures have a clear correlation between the age of the asset and the likelihood of failure. In these cases, preventative maintenance at regular time-based intervals may be appropriate and cost-effective. The non-age-based failures are more “random,” due to improper design/installation, operator error, quality issues, machine overuse, etc. In these cases, preventative maintenance will likely not prevent failure and may waste time and money on unnecessary maintenance.

Table is based on data from studies conducted by United Airlines (1978), Broberg (1973), U.S. Navy (1993 MSDP) and U.S. Navy (2001 SUBMEPP) and ARC Consulting

The fact that approximately 80% of failures are non-age-related has major implications for manufacturers trying to decide on a maintenance approach. The traditional preventative-maintenance approach is not likely to address these failures and may even cause failures when improperly done. It is therefore important to consider a more proactive approach, such as condition-based monitoring or predictive maintenance, especially for assets that are critical to the process and/or expensive.

Preventative maintenance and regular inspection may be a good approach for assets more likely to experience age-based failures in Types A, E, and F. These include fans, bearings, and structural components – and in many cases, the cost of condition monitoring or predictive maintenance may not be worth the cost. But for critical components or equipment, such as bearings on an expensive milling machine or transfer line, it may be worthwhile to apply condition monitoring or predictive maintenance.

And when the assets are more likely to experience non-age-related failures (Types B, C, and D), the proactive approaches are better. Many industrial machines and industrial control/motion components fall into this category, and condition monitoring or predictive maintenance can significantly reduce preventative maintenance costs and unplanned failures while improving machine uptime and Overall Equipment Effectiveness.

You can use this information to improve your maintenance operations. Start by considering your maintenance approach(es), especially for your most critical assets:

    • Are they more likely to experience age-related failures or non-age-related failures?
    • Should you change your maintenance approach to be more proactive?
    • What components and indicators should you measure?

We’ll discuss ideas on how to assess your equipment for condition monitoring/predictive maintenance and what you might measure in separate blogs.

* Studies conducted by United Airlines (1978), Broberg (1973), U.S. Navy (1993 MSDP) and U.S. Navy (2001 SUBMEPP)

Choosing Sensors Suitable for Automation Welding Environments

Standard sensors and equipment won’t survive for very long in automated welding environments where high temperatures, flying sparks and weld spatter can quickly damage them. Here are some questions to consider when choosing the sensors that best fit such harsh conditions:

    • How close do you need to be to the part?
    • Can you use a photoelectric sensor from a distance?
    • What kind of heat are the sensors going to see?
    • Will the sensors be subject to weld large weld fields?
    • Will the sensors be subject to weld spatter?
    • Will the sensor interfere with the welding process?

Some solutions include using:

    • A PTFE weld spatter resistant and weld field immune sensor
    • A high-temperature sensor
    • A photoelectric diffuse sensor with a glass face for better resistance to weld spatter, while staying as far away as possible from the MIG welding application

Problem, solution

A recent customer was going through two sensors out of four every six hours. These sensors were subject to a lot of heat as they were part of the tooling that was holding the part being welded. So basically, it became a heat sink.

The best solution to this was to add water jackets to the tooling to help cool the area that was being welded. This is typically done in high-temperature welding applications or short cycle times that generate a lot of heat.

    • Solution 1 was to use a 160 Deg C temp sensor to see if the life span would last much longer.
    • Solution 2 was to use a plunger prob mount to get more distance from the weld area.

Using both solutions was the best solution. This increased the life to one week of running before it was necessary to replace the sensor. Still better than two every 6 hours.

Taking the above factors into consideration can make for a happy weld cell if time and care are put into the design of the system. It’s not always easy to get the right solution as some parts are so small or must be placed in tight areas. That’s why there are so many choices.

Following these guidelines will help significantly.

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.