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Why Choose an IO-Link Ecosystem for Your Next Automation Project?

By now we’ve all heard of IO-Link, the device-level communication protocol that seems magical. Often referred to as the “USB of industrial automation,” IO-Link is a universal, open, and bi-directional communication technology that enables plug-and-play device replacement, dynamic device configuration, centralized device management, remote parameter setting, device level diagnostics, and uses existing sensor cabling as part of the IEC standard accepted worldwide.

But what makes IO-Link magical?

If the list above doesn’t convince you to consider using IO-Link on your next automation project, let me tell you more about the things that matter beyond its function as a communications protocol.

Even though these benefits are very nice, none of them mean anything if the devices connected to the network don’t provide meaningful, relevant, and accurate data for your application.

Evolution of the IO-Link

IO-Link devices, also known as “smart devices,” have evolved significantly over the years. At first, they were very simple and basic, providing data such as the status of your inputs and outputs and maybe giving you the ability to configure a few basic parameters, such as port assignment as an input or an output digitally over IO-Link. Next, came the addition of functions that would improve the diagnostics and troubleshooting of the device. Multi-functionality followed, where you have one device under one part number, and can configure it in multiple modes of operation.

Nothing, however, affected the development of smart devices as much as the introduction of IIoT (Industrial Internet of Things) and the demand for more real-time information about the status of your machine, production line, and production plant starting at a device level. This demand drove the development of smart devices with added features and benefits that are outside of their primary functions.

Condition monitoring

IO-Link supplies both sensor/actuator details and secure information
IO-Link supplies both sensor/actuator details and secure information

One of the most valuable added features, for example, is condition monitoring. Information such as vibration, humidity, pressure, voltage and current load, and inclination – in addition to device primary function data – is invaluable to determine the health of your machine, thus the health of your production line or plant.

IO-Link offers the flexibility to create a controls architecture independent of PLC manufacturer or higher-level communications protocols. It enables you to:

    • use existing low-cost sensor cabling
    • enhance your existing controls architecture by adding devices such as RFID readers, barcode and identification vision sensors, linear and pressure transducers, process sensors, discrete or analog I/O, HMI devices, pneumatic and electro-mechanical actuators, condition monitoring, etc.
    • dynamically change the device configuration, auto-configure devices upon startup, and plug-and-play replacement of devices
    • enable IIOT, predictive maintenance, machine learning, and artificial intelligence

There is no other device-level communications protocol that provides as many features and benefits and is cost-effective and robust enough for industrial automation applications as IO-Link.

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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.

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Know Your RFID Frequency Basics

In 2008, I purchased my first toll road RFID transponder, letting me drive through and pay my toll without stopping at a booth. This was my first real-life exposure to RFID, and it was magical. Back then, all I knew was that RFID stood for “radio frequency identification” and that it exchanged data between a transmitter and receiver using radio waves. That’s enough for a highway driver, but you’ll need more information to use RFID in an industrial automation setting. So here are some basics on what makes up an RFID system and the uses of different radio frequencies.

At a minimum, an RFID system comprises a tag, an antenna, and a processor. Tags, also known as data carriers, can be active or passive. Active tags have a built-in power source, and passive tags are powered by the electromagnetic field emitted by the antenna and are dormant otherwise. Active tags have a much longer range than passive tags. But passive tags are most commonly used in industrial RFID applications due to lower component costs and no maintenance requirements.

Low frequency (LF), high frequency (HF), ultra-high frequency (UHF)

The next big topic is the different frequency ranges used by RFID: low frequency (LF), high frequency (HF), and ultra-high frequency (UHF). What do they mean? LF systems operate at a frequency range of 125…135 kHz, HF systems operate at 13.56 MHz, and UHF systems operate at a frequency range of 840…960 MHz. This tells you that the systems are not compatible with each other and that you must choose the tag, antenna, and processor unit from a single system for it to work properly. This also means that the LF, HF, and UHF systems will not interfere with each other, so you can install different types of RFID systems in a plant without running a risk of interference or crosstalk issues between them or any other radio communications technology.

 

Choosing the correct system frequency?

How do you choose the correct system frequency? The main difference between LF/HF systems and UHF systems is the coupling between the tags and the antenna/processor. LF and HF RFID systems use inductive coupling, where an inductive coil on the antenna head is energized to generate an inductive field. When a tag is present in that inductive field, it will be energized and begin communications back and forth. Using the specifications of the tag and the antenna/processor, it is easy to determine the read/write range or the air gap between the tag and the antenna head.

The downside of using LF/HF RFID technology based on inductive coupling is that the read/write range is relatively short, and it’s dependent on the physical size of the coils in the antenna head and the tag. The bigger the antenna and tag combination, the greater the read/write distance or the air gap between the antenna and the tag. The best LF and HF RFID uses are in close-range part tracking and production control where you need to read/write data to a single tag at a time.

UHF RFID systems use electromagnetic wave coupling to transmit power and data over radio waves between the antenna and the tag. The Federal Communications Commission strictly regulates the power level and frequency range of the radio waves, and there are different frequency range specifications depending on the country or region where the UHF RFID system is being used. In the United States, the frequency is limited to a range between 902 and 928MHz. Europe, China, and Japan have different operating range specifications based on their regulations, so you must select the correct frequency range based on the system’s location.

Using radio waves enables UHF RFID systems to achieve a much greater read/write range than inductive coupling-based RFID systems. UHF RFID read/write distance range varies based on transmission power, environmental interference, and the size of the UHF RFID tag, but can be as large as 6 meters or 20 feet. Environmental interferences such as metal structures or liquids, including human bodies, can deflect or absorb radio waves and significantly impact the performance and reliability of a UHF RFID system. UHF RFID systems are great at detecting multiple tags at greater distances, making them well suited for traceability and intralogistics applications. They are not well suited for single tag detection applications, especially if surrounded by metal structures.

Because of the impact an environment has on UHF signals, it is advisable to conduct a full feasibility study by the vendor of the UHF RFID system before the system solution is purchased to ensure that the system will meet the application requirements. This includes bringing in the equipment needed, such as tags, antennas, processors, and mounting brackets to the point of use to ensure reliable transmission of data between the tag and the antenna and testing the system performance in normal working conditions. Performing a feasibility study reduces the risk of the system not meeting the customer’s expectations or application requirements.

Selecting an industrial RFID system

There are other factors to consider when selecting an industrial RFID system, but this summary is a good place to start:

    • Most industrial RFID applications use passive RFID tags due to their lower component costs and no battery replacement needs.
    • For applications requiring short distance and single tag detection, LF or HF RFID systems are recommended.
    • For applications where long-distance and multi-tag detection is needed, UHF RFID systems are recommended.
    • If you are considering UHF, a feasibility study is highly recommended to ensure that the UHF RFID system will perform as intended and meet your requirements.

Click here to browse our library of Automation Insights blogs related to RFID.

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How Vibration Measurement Saves Manufacturers Time and Money

Vibration is all around us. We can feel it and we can hear it. Some vibrations we find pleasant, such as music that we like to listen to, and some vibrations we find unpleasant such as scratching fingernails across the chalkboard. Humans also can predict when something is about to fail or determine when something needs our attention based on the vibrations we can feel or hear in our surroundings. An example almost anyone can relate to is when you are driving or riding in a car and the tires are out of balance or are damaged. In addition to the audible noise, you can feel the vibration through the steering wheel and the chassis of the car. Frequency and amplitude of the vibration typically increase as you speed up, and often amplify your worry as well. This can push you to find the cause of the vibration and fix it.

This same principle can be used in a manufacturing plant environment, which is what makes monitoring vibration so important. Without it, machines break down and stop, costing you time, and money. We all know that one maintenance guru that has a special gift of being able to determine what is happening with a machine based on its vibration feedback, the one who can place his hand on a machine, or hear the machine speak to him, and determine what is wrong with it.

However, using this institutional knowledge isn’t full-proof and it can introduce additional variables in the mix; sometimes resulting in wasted parts, labor, unplanned machine downtime, loss of production, etc. And as tenured staff retires and is replaced with less experienced staff, it has become even more important to remove the human element from the equation and properly capture the data to determine the root cause of mechanical issues. But how? By equipping machines with a monitoring system, the machine can then continuously monitor itself. And when the variables exceed the preset acceptable thresholds, the machine can act based on predetermined actions set by the OEM manufacturer or the maintenance team.

There are many monitoring systems on the market today that vary in complexity and cost. More complex systems include sensors, cables, data acquisition cards, computers, analysis software, data base, cloud subscription, and paid service contracts to pinpoint exact condition of the equipment or asset that is being monitored. This type of system or service is very costly, and in most cases, it is cost prohibitive to be used on non-critical equipment or assets. However, there are lower cost solutions that may not be able to pinpoint what has failed but can tell you when something wrong with the machine that needs to be examined by the maintenance technician. Such devices can be easily integrated into an existing controls architecture and can provide continuous condition monitoring of the machine or asset. Practice of continuous condition monitoring of machines can save the company valuable time and money by reducing unscheduled machine downtime, eliminating wasted parts and time for unnecessary scheduled maintenance, improving total OEE (Overall Equipment Effectiveness) of the machine, and increasing production. This all leads to increased profits.

Because there are more and more solutions available in the market today, there are few things you need to consider when choosing the right solution for your application:

  • Overall cost of implementation – hardware, software, and any installation costs?
  • Is the solution proprietary? Hardware, software, or communications?
  • Is there an annual service contract(s)? Subscriptions?
  • Does the machine/asset require periodic or continuous monitoring?
  • Quality of data? Do you need to know the exact failure point or is knowing that the machine is operating outside of its specified parameters good enough?
  • Can the system be easily expanded for the future state?
  • Are there any additional features that can aid in analyzing the condition of the machine such as pressure, temperature, humidity?

Knowing what you need and want ahead of time will help you better choose the correct solution for your application without wasting money and time on unnecessary features and functions.

 

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Improve OEE, Save Costs with Condition Monitoring Data

When it comes to IIOT (Industrial Internet of Things) and the fourth industrial revolution, data has become exponentially more important to the way we automate machines and processes within a production plant. There are many different types of data, with the most common being process data. Depending on the device or sensor, process data may be as simple as the status of discrete inputs or outputs but can be as complex as the data coming from radio frequency identification (RFID) data carriers (tags). Nevertheless, process data has been there since the beginning of the third industrial revolution and the beginning of the use of programmable logic controllers for machine or process control.

With new advances in technology, sensors used for machine control are becoming smarter, smaller, more capable, and more affordable. This enables manufacturers of those devices to include additional data essential for IIOT and Industry 4.0 applications. The latest type of data manufacturers are outputting from their devices is known as condition monitoring data.

Today, smart devices can replace an entire system by having all of the hardware necessary to collect and process data, thus outputting relative information directly to the PLC or machine controller needed to monitor the condition of assets without the use of specialized hardware and software, and eliminating the need for costly service contracts and being tied to one specific vendor.

A photo-electric laser distance sensor with condition monitoring has the capability to provide more than distance measurements, including vibration detection. Vibration can be associated with loose mechanical mounting of the sensor or possible mechanical issues with the machine that the sensor is mounted. That same laser distance sensor can also provide you with inclination angle measurement to help with the installation of the sensor or help detect when there’s a problem, such as when someone or something bumps the sensor out of alignment. What about ambient data, such as humidity? This could help detect or monitor for moisture ingress. Ambient pressure? It can be used to monitor the performance of fans or the condition of the filter elements on electrical enclosures.

Having access to condition monitoring data can help OEMs improve sensing capabilities of their machines, differentiating themselves from their competition. It can also help end users by providing them with real time monitoring of their assets; improving overall equipment efficiency and better predicting  and, thereby, eliminating unscheduled and costly machine downtime. These are just a few examples of the possibilities, and as market needs change, manufacturers of these devices can adapt to the market needs with new and improved functions, all thanks to smart device architecture.

Integrating smart devices to your control architecture

The most robust, cost effective, and reliable way of collecting this data is via the IO-Link communication protocol; the first internationally accepted open, vendor neutral, industrial bi-directional communications protocol that complies with IEC61131-9 standards. From there, this information can be directly passed to your machine controller, such as PLC, via fieldbus communication protocols, such as EtherNET/Ip, ProfiNET or EtherCAT, and to your SCADA / GUI applications via OPC/UA or JSON. There are also instances where wireless communications are used for special applications where devices are placed in hard to reach places using Bluetooth or WLAN.

In the fast paced ever changing world of industrial automation, condition monitoring data collection is increasingly more important. This data can be used in predictive maintenance measures to prevent costly and unscheduled downtime by monitoring vibration, inclination, and ambient data to help you stay ahead of the game.

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How to Take Advantage of IO-Link Parameter Data

IO-Link data packets contain parameter data of an IO-Link slave device that is acyclic and is only transferred when read or write is requested by the machine controller. Having parameter data available on a device is not new or groundbreaking; however, the main advantage of IO-Link parameter data is that it is directly accessible by the machine controller, and it is dynamic, meaning you do not have to take the device offline to change its parameters or configuration. Parameter data determines how flexible or configurable an IO-Link slave device is. Its content will be different from device to device and manufacturer to manufacturer, a differentiator when choosing the right device for your application. We all know that not all IO-Link devices are created equal.

So how can you take advantage of parameter data?

Automatic machine configuration

Imagine if your machine could automatically configure itself upon first power-up? Yes, it is possible. Because IO-Link parameter data is accessible by the machine controller, i.e., the PLC or PAC, one can write a routine/program that first verifies the correct device is connected to the correct port of the IO-Link master, request a parameter read, compare the parameter content to the desired configuration in the program, and overwrite the current device parameter set if necessary. Why would someone do this? Well, if you are an OEM machine builder building ten of the same machines for one end customer, it would be a worthwhile investment in programming development to have IO-Link devices configured automatically. This method would eliminate the need for manual machine parameterization and result in cost savings. Examples of typical configuration would be changing the pin assignment of an IO-Link freely configurable discrete input/output hub as an input or an output, machine home position or offset of an IO-Link linear transducer, set points of an IO-Link pressure transducer, set points of an IO-Link laser distance sensor, and so on.

Recipe change

Another way to take advantage of IO-Link parameter data is to have the machine controller automatically change device configuration based on recipe change. This would eliminate the need for an operator to manually change device parameters, thus saving time and minimizing human error, especially if the device is not easily accessible by a human.

Maintenance

Having direct access to device parameters by the machine controller also enables OEMs to simplify their machines’ serviceability. For component replacement, all the maintenance personnel would have to replace a damaged device with a new device and walk away, eliminating the need for specialized training, software, or hardware.

Some manufacturers add special functions to their IO-Link masters to enable automatic backup and restoration of IO-Link slave device parameters, making replacement of components as easy as plug and play. This function would eliminate the need for OEMs to create custom programs or logic in their PLCs to restore parameter sets on a device automatically.

How to

So how would I do this? Because parameter data is accessible by the machine controller, implementation of auto configuration differs based on what brand of controller you are using. I will mention a few of the most popular.

  • Allen Bradley – For the Allen Bradley family of PLCs, you would use an explicit  instruction to read and write IO-Link device parameters.
  • Siemens -For the Siemens family of PLCs, you would use a standard function block named “FB_IOL_CALL”.

As you can see, every PLC or machine controller manufacturer and their flavor of IDE (Integrated Development Environment) will have their unique way of accessing IO-Link device parameter set. It is best to consult with both manufacturers and review IO-Link devices and PLCs to better understand how to set the read and write parameters of an IO-Link slave device.

Conclusion

Having direct access to device parameters and being able to change them without taking the device offline or needing special software or hardware, and implement it at a device level is game-changing. It opens doors for time and cost savings in design, integration, operation, and serviceability of machines. It is different from what we are used to, so don’t be afraid to think outside of the box and jump in with both feet.

 

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What data can IO-Link provide?

As an application engineer, one of the most frequent questions I get asked by the customers is “What is IO-Link and what data does it contain?”.

Well, IO-Link is the first worldwide accepted sensor communication protocol to be adopted as an international standard IEC61131-9. It is an open standard, and not proprietary to one manufacturer. It uses bi-directional, single line serial communications to transfer data between the machine controller and sensors/actuators. No other communication protocol is manufacturer and fieldbus independent, and yet provides this level of communication down to the sensor/actuator level. It provides the user with three different data types: process data, parameter data, and diagnostics or event data.

Process Data

Process data of an IO-Link smart device is considered the latest state of that device. Containing both input and output data, process data is cyclically exchanged between IO-Link master and IO-Link slave device (i.e. sensor or actuator). The time interval or data update rate solely depends on amount of data, 1 to 32 bytes, and speed at which an IO-Link slave device communicates. IO-Link standard (IEC61131-9) defines three different communications speeds; COM1 is set to 4.8kBaud (slowest), COM2 is set to 38.4kBaud and COM3 is set to 230.4kBaud (fastest). Depending on the device, process data may contain status of inputs or outputs of remote I/O hub, position feedback of linear transducers, pressure feedback from pressure transducers, information from am RFID (Radio Frequency Identification) reader, and so on. For more information about process data content, refresh rate, and data mapping, one should reference an IO-Link slave device datasheet or user manual.

Lastly, process data is then buffered in memory of the IO-Link master device and passed to the controller via a specific fieldbus at request packet interval. Request packet interval is set in the controller settings.

Process Data

Parameter Data

Parameter data contains information and parameters specific to the IO-Link slave device. This data is exchanged acyclically, which means that it is requested from the IO-Link master or controller and not time based. Parameters can be read from a specific device or written to. Parameter data is primarily used for device configuration, or verification. A key advantage of IO-Link is that it gives the controller the full access to IO-Link slave device parameters, down to a sensor/actuator level. This means that your controller, PLC or PC based, can change the configuration of an IO-Link’s slave device dynamically without taking the device off line, and without use of proprietary cabling or configuration software.

Typical use of parameter data is for automatic machine configuration, recipe change, process tuning, maintenance, and easy component replacement.

Parameter Data

Diagnostics or Event Data

Diagnostic data provides the controller with events that affect the operation and performance of the IO-Link smart device. Content can vary depending on the device used, and the manufacturer. IO-Link smart devices can provide crucial data such as load, temperature, stress level, overload and short circuit diagnostics, error codes, configuration or parameter issues, access issues, etc., as part of diagnostic or event data. The event code size is 2 bytes, and in hexadecimal data format. This information can then be interpreted by the controller/user using a lookup table or IODD (I/O Device Description) file. User manual will have diagnostic data table that can be used as a reference.

Diagnostic and Event Data

Conclusion

In conclusion, IO-Link enables a plug-and-play relationship between the controller and the devices on the machine. Using IO-Link data, the controller can automatically recognize and configure an IO-Link slave device that is connected to its network. Process and diagnostic data provide continuous feedback on machine status and health down to a sensor level — the lowest level of the automation pyramid.

Keep in mind that the content of process data is specific to the device and will vary from device to device, and manufacturer to manufacturer. This makes IO-Link data one of the main differentiators between smart devices and their manufacturers. Luckily, IO-Link is an open standard, and fieldbus and manufacturer independent, so you can mix and match devices best suited for your application without worrying about device compatibility, special cabling, or third-party configuration software packages.

automation pyramid