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.

Start Condition Monitoring With Vibration Sensors

IIOT (Industrial internet of things) has gained much traction and attraction in past years. With industries getting their assets online for monitoring purposes and new IO-Link sensors providing a ton of information on a single package, monitoring machines has become economically feasible.

Vibration is one of the most critical metrics regarding the health of machines, providing early detection of potential faults – before they cause damage or equipment failure. But since this is a relatively new field and use case, there is not much information about it. Most customers are confused about where to start. They want a baseline to begin monitoring machines and then finetune them to their use case.

“Vibration is one of the most critical metrics regarding the health of machines…”

One approach to solve this is to hire a vibration expert to determine the baseline and the best location to mount the vibration measuring sensor. Proper setup increases the threshold of getting into condition monitoring as a new user figures out the feasibility of such systems.

I direct my customers to this standardized baseline chart from ISO, so they can determine their own baselines and the best mounting positions for their sensors. The table shows the different standards for severity for different machine classes. These standards detail the baseline vibration and show the best place to mount the sensor based on the machine type.

Click here for more information on the benefits of condition monitoring.

 

Manufacturing Insights: Top Blogs From 2021

While last year was filled with challenges and unexpected changes for many industries, including manufacturing, it was not without positive achievements and insights. As we look forward to 2022, let’s not forget some topics that shaped 2021, including our five most-read blogs.

1. 5 Manufacturing Trends to Consider as You Plan for 2022

 

 

 

 

It’s that time of year again where we all start to forget the current year (maybe that’s OK) and start thinking of plans for the next – strategy and budget season! 2022 is only a few weeks away! I thought I’d share 5 insights I’ve had about 2022 that you might benefit from as you start planning for next year.

READ MORE>>

2. The Pros and Cons of Flush, Non-Flush and Semi-Flush Mounting


Inductive proximity sensors have been around for decades and have proven to be a groundbreaking invention for the world of automation. This type of technology detects the presence or absence of ferrous objects using electromagnetic fields. Manufacturers typically select which inductive sensor to use in their application based on their form factor and switching distance. Although, another important factor to consider is how the sensor will be mounted.

READ MORE>>

3. IO-Link Wireless – IO-Link with Even Greater Flexibility



In a previous blog entry, I discussed IO-Link SPE (Single-Pair Ethernet). SPE, in my opinion, has two great strengths compared to standard IO-Link: cable length and speed. With cable lengths of up to 100 meters and speed of 10 Mbps, compared to 20 meters and max baud rate of 230.4 Kbps, what could be out of reach?

READ MORE>>

4. How Condition Monitoring has Evolved and Its Role in IIoT

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

READ MORE>>

5. Lithium Ion Battery Manufacturing – RFID is on a Roll



With more and more consumers setting their sights on ‘Drive Electric,’ manufacturers must prepare themselves for alternative solutions to combustion engines. This change will no doubt require an alternative automation strategy for our electric futures.

READ MORE>>

Honorable Mention: Top 5 Insights From 2020

And, finally, for the sake of comparison, we can’t help but honorably mention last year’s look-back blog. The top five insights from 2020 include buying a machine vision system; data provided by IO-Link; changes in electrostatic sensing field by capacitive sensors; reducing the number of ethernet nodes on your network using IO-Link; and adding a higher level of visibility to older automation machines.

Read more>>

We appreciate your dedication to Automation Insights in 2021 and look forward to growth and innovation in 2022!

Is a Photoelectric Sensor Best for Your Label Detection Application?

Label detection is in every industry of manufacturing. Detecting the placement, orientation, color, or size of a label is critical to product quality and it can even be required for safety purposes. Contrary to what some believe, not every label detection application requires an expensive vision system. This article reviews some common applications that can be solved with just a photoelectric sensor.

As with any sensor application, it’s necessary to specifically tailor the systems for individual applications. In label detection, the label properties dictate the necessary sensor for the job. Using the right sensor will ensure accuracy to the manufacturing process by limiting the possibility of errors or misreads when placing or cutting off the label. The chance for mistakes decreases when labels are designed to have markings used as a point of reference for the sensor to recognize, telling the PLC programming that it is time to cut off or place the label. When looking into a label detection application, several photoelectric sensor types are available.

Through-beam fork sensors

A through-beam fork sensor has an emitter and a receiver built into the same housing which provides a consistent light beam that is simple to configure to many applications. For label detection, fork sensors have teach-in buttons to set the target and background so unique markings can trigger the sensor. This helps find an identification marker that can identify where to cut the label. For applications with consistent markings on different labels, the sensor would not need to be retaught if the color of the identification mark and the background are the same. The common use for these sensors is on flexible manufacturing lines because operators can reteach the sensor to recognize a new label with a different style and color in less than 60 seconds.

Contrast sensors

Providing a high level of accuracy to find labels in an assortment of products, contrast sensors can be taught to identify a target on many different material types, providing an advantage when working with three-dimensional objects. They provide background suppression, allowing for applications using transparent objects, such as glass and plastic and work by distinguishing between objects based on their gray values. This means contrast sensors are highly accurate when detecting objects with similar colors.  

Color sensors

Color sensors are a fantastic choice when working with labels with many different colors. A traditional color sensor can be taught to up to 7 different color parameters to distinguish one label type from the others. Manufacturers with multiple production lines that have labels with various colors can use just one color sensor to detect them all. The more advanced IO-Link-capable color sensors provide an abundance of opportunities to configure many different label types. Using color detection software, one color sensor can be taught up to 256 different color parameters. Users can configure each color setting for the label’s colors and the background.

When it comes to selecting the right sensor for your label detection, you have options. You need to consider the specifics of your application and choose the solution that ensures accuracy and quality during the manufacturing process. For more information about the Balluff photoelectric sensors, visit https://www.balluff.com/en-us/products/areas/A0001/groups/G0103/products/F01325?page=1&perPage=10&searchTerm=.

3 Easy Options to Get Started With IIoT in 2022

The Industrial Internet of Things (IIoT) may seem large, intimidating, and challenging to implement; however, new systems and solutions will eliminate the perceived barriers for entry. As we wrap up the year and make plans for 2022, now is a great time to resolve to modernize your facility.

Do you have a process, system or machine that has outlived its life expectancy for many years or even decades and isn’t up to current IIoT standards? Great news: you have several options for updating.

Traditional approach

The traditional approach allows you to use your current controller to output your information to your existing database. If you want to try IIoT on your current setup and your controller cannot be modified, a self-contained system will allow for ultimate flexibility. It will provide you with access to the data based off an extra layer of sensing with a focus on condition monitoring. This approach is the least expensive route, however, if database access is restricted the following options may be better choices.

Cloud-based current industry standard

A second option is to use a portable monitoring system that has a condition monitoring sensor. It is essentially five sensors in one package that can hook up to a system using the cellular network to report data to a secure cloud database. This approach is useful in remote locations or where local network access is limited. If you have a problem area, you can apply this temporarily to collect enough data, enabling you to implement predictive maintenance.

Local-based current industry standard

A local self-contained system is a great solution if a cloud database is not desired or allowed. Systems such as a Condition Monitoring Toolkit allow for recording of devices onto the local memory or USB drive. Additionally, multiple alarm set points can be emailed or extracted locally. This approach is best for testing existing machines to help with predictive maintenance, to improve a process, or even to prevent a failure.

All three of these options require data management and analysis to improve your processor and to remedy problematic areas. Using any of them is an opportunity to test the IIoT waters before fully diving in. Extrapolating the results into problem-solving solutions can allow you to expand IIoT to the rest of your facilities in a cost-effective manner.

Error-Free Assembly of Medical Components

A SUV and a medical device used in a lab aren’t very similar in their looks, but when it comes to manufacturing them, they have a lot in common. For both, factory automation is used to increase production volume while also making sure that production steps are completed precisely. Read on to learn about some ways that sensors are used in life science manufacturing.

Sensors with switching output

Automation equipment producers are creative builders of specialized machines, as each project differs somehow from previous ones. When it comes to automated processes in the lab and healthcare sectors where objects being processed or assembled are small, miniaturization is required for manufacturing equipment as well.  Weight reduction also plays an important role in this, since objects with a lower mass can be moved quickly with a smaller amount of force. By using light-weight sensors on automated grippers, they can increase the speed of actuator movements.

Conveyor system using photoelectric sensors for object detection

Photoelectric sensors are quite common in automated production because they can detect objects from a distance. Miniaturized photoelectric sensors are more easily placed in a production process that works with small parts. And photoelectric sensors can be used to detect objects that are made of many different types of material.

A common challenge for lab equipment is to detect clear liquids in clear vessels. Click here for a description of how specialized photoelectric sensors face this challenge.

Specialized photoelectric sensors for clear water detection

Image Processing

Within the last several years, camera systems have been used more frequently in the production of lab equipment. They are fast enough for high-speed production processes and support the use of artificial intelligence through interfaces to machine learning systems.

Identification

In any production setting, products, components and materials must be identified and tracked. Both optical identification and RFID technology are suitable for this purpose.

Sample analysis with industrial camera

Optical identification systems use a scanner to read one-dimensional barcodes or two-dimensional data matrix or QR codes and transmit the object information centrally to a database, which then identifies the object. The identification cost per object is pretty low when using a printed label or laser marking on the object.

When data must be stored directly on or with the object itself, often because the data needs to be changed or added to during the production process, RFID (Radio Frequency Identification) is the best choice. Data storage tags come in many different sizes and can store different amounts of data and have other features to meet specific needs. This decentralized data storage has advantages in fast production processes when there is a need for real-time data storage.

Data of RFID tag at pallet are read and written with RFID read/write head and transferred via bus module

There are numerous parallels between automation in the life science sector and general factory automation. While these manufacturing environments both have their own challenges, the primary automation task is the same: find the best sensor for your application requirements. Being able to choose from many types of sensors, with different sizes and characteristics, can make that job a lot easier. For more information about the life sciences industries, visit https://www.balluff.com/en-us/industries/life-science.

UHF RFID Versus UHF RTLS

Many companies new to UHF (Ultra High Frequency) RFID (Radio Frequency Identification) confuse it with UHF RTLS (Real Time Location Systems). While both indeed do use UHF RFID, they differ substantially in what they can actually do for you in your business.

Many companies new to UHF (Ultra High Frequency) RFID (Radio Frequency Identification) confuse it with UHF RTLS (Real Time Location Systems). While both indeed do use UHF RFID, they differ substantially in what they can actually do for you in your business.
UHF RFID

Standard UHF RFID systems can see multiple tags on equipment and products up to several meters away, if set up properly. With emphasis on “set up properly.” While UHF RFID works quite well, its unique characteristics require testing in the environment where it will be used to ensure success.

UHF RFID has several purposes:

    • To see if an item has passed a certain point, commonly known as a choke point. Examples of this are items being loaded on or off a trailer at a shipping door or items passing from one area to another in a plant.
    • To verify if something is within a certain area when using a scanning device, such as a handheld reader. If one is scanning shelves of parts or equipment, it will help locate those items.
    • To track usage of equipment in MIS systems.
    • The tags can also have data written to them if needed.

The big thing that UHF RFID cannot do is effectively track the exact location of something at any given time in a cost-effective manner. Generally, UHF RFID uses what are called passive tags for the antennas to read. These tags have no battery and get energized from the antenna signal. If you placed enough antennas all over a facility and enough of these tags, then you could possibly locate something within a certain proximity, but not exactly, and this is hardly cost effective.

UHF Real Time Location Systems (RTLSs)

RTLS, on the other hand, are specifically designed to pinpoint the location of anything with a tag or transponder on it. In fact, RTLS refers to any system that can accurately determine an item or person’s location. An important aspect of RTLS is how frequently assets must be tracked. This data can be used in different ways depending on the application. For example, some RTLS applications only need timestamps when an asset passes through an area, while others require much higher visibility, requiring constant updating of time data.

An ideal RTLS can accurately locate, track, and manage assets, inventory, or people, and help companies make knowledgeable decisions based on collected location data.

Like regular UHF RFID, RTLS can use passive or active tags (tags with batteries), but they use triangulation of multiple antennas to determine the location of an object or person. The strength of the signal at each antenna, combined with the software attached to the antennas, allows the identification of the location of an object or person within less than 1 meter.

The system you choose depends on the needs at your location. They both work quite well when implemented properly by trained professionals.

Also, due to the inherent properties of ultra-high frequencies used in UHF RFID technology and RTLS, you should perform a feasibility study that actually tests the system in the real world environment of the plant prior to implementing these systems in any application.

Food for Thought: Should a Fork Sensor be Your First Choice?

When it comes to reliability and accuracy, there is no optical sensing mode better than the through-beam photoelectric sensor. Its reliability is a result of the extraordinary levels of excess gain – the measurement of light energy above the level required for normal sensing. The more excess gain, the more tolerant of dirt, moisture and debris accumulating on the sensor.

Excess gain comparison

The accuracy of through-beams results from a tight, well-defined sensing area. This chart shows a comparison between the popular sensing modes.

When it comes to reliability and accuracy, there is no optical sensing mode better than the through-beam photoelectric sensor. Its reliability is a result of the extraordinary levels of excess gain – the measurement of light energy above the level required for normal sensing. The more excess gain, the more tolerant of dirt, moisture and debris accumulating on the sensor. The accuracy of through-beams results from a tight, well-defined sensing area. This chart shows a comparison between the popular sensing modes.

The sensing area starts with an emitted beam projected onto the receiver. The wider the emitted beam, the easier to align. Once aligned, you now have the effective beam which is basically the size of the emitter and receiver lens. The smaller the lens, the smaller the effective beam. Apertures can also be used to narrow down the effective beam.

Simple detection

A target is detected when it breaks the effective beam. The simple detection principle means these sensors can detect anything, regardless of color, texture, or reflectivity. They are generally used in applications that require a sensing range of 2mm to 100m! The simplicity of their operation and wide range make them a go-to detection solution across industries.

Fork sensor, effective beam_emitted beamTraditional through-beam sensors consist of two separate pieces which must be separately mounted and wired, and perfectly aligned to work. This can be inconvenient and time consuming. But for those applications that can use an opening from 5mm to 220mm, self-contained through-beam sensors, also called fork sensors, provide the usefulness of traditional through-beams without the trouble of alignment. With the emitter and receiver in one housing, they are automatically aligned and require only half the wiring effort.

Light types

Available in four different light types – red light, pinpoint red light, infrared and laser – they can detect even difficult and tiny parts. Red light and pinpoint red light are used for most applications, while laser light is used for small part detection, as small as 0.08 mm. Infrared improves detection efforts in dirty environments.

Through-beam sensors are a go-to solution for photoelectric applications, but with tough housings, various lighting options, and the ease of installation and alignment, fork sensors should be first on your list of photoelectric sensors to consider.

Zoning in on Explosive Atmospheres

Everybody wants to wake up in the morning and know they’re going to a safe workplace. A major safety concern among certain industries is the occurrence of fires and explosions. This makes for some of the most expansive safety codes and standards. This article is aimed at explaining hazardous area classification in simple terms for easy comprehension. Before we begin to classify hazardous areas, it is crucial to define what they are.

What is a hazardous area?

A hazardous area is a place in which an explosive atmosphere may occur in quantities requiring the implementation of special precautions to protect the health and safety of workers. Hazardous areas are classified into two major categories: gases/vapors and dusts.

Classification of hazardous areas

Both categories are further divided into three ATEX Zones, as directed by the European Union for protection against explosive atmospheres. Each zone indicates the frequency and duration an explosive atmosphere may be present. Hazardous areas involving gases/vapors are classified as follows:

    • Zone 0 is an area where an explosive atmosphere consisting of a mixture of air with flammable substances in the form of gas, vapor, or mist is present continuously for long periods or frequently (continuous hazard)
    • Zone 1 is an area where an explosive atmosphere is likely to occur in normal operation occasionally (intermittent hazard)
    • Zone 2 is an area where an explosive atmosphere is unlikely to occur in normal operating conditions, and if it does occur, it is likely to do so for a short period only (possible hazard)

Similarly, dusts classify into three different zones: Zones 20,  21, and  22, each representing identical meanings as their gas/vapor code counterparts, respectively. The gas station example below offers a real-world picture of these hazardous zones.

Gas station hazard zonesThe vessels containing the fuel underground and on the truck are classified as Zone 0 because these areas are continuously holding flammable substances. The gas pumps and any valve or opening into the gas containers are classified as Zone 1 because gas will be passing through intermittently — when a customer uses the pump or an employee fills the tanks. Zone 2 is the natural space or the natural environment. While fuel should not be exposed to the natural environment under normal operating conditions, it is possible. Spills, for example, can create a possible hazard for a short duration.

It’s important to note the European Union ATEX directive is not compliant with OSHA standards in the United States. While similar, the U.S. has its own classification system for identifying hazardous zones called the NEC Zone Classification System. See how the two systems compare here.

Safety

The more frequent an explosive gas or dust cloud is present, the more dangerous the zone. Therefore, companies practice ATEX zone reduction by implementing safety measures.

In areas with risk of explosion, accurate and reliable position detection is often relied on to complete tasks. Examples include monitoring hydraulic and pneumatic cylinders, checking hydraulically and pneumatically controlled valves, and level detection.

IO-Link: End to Analog Sensors

With most sensors now coming out with an IO-Link output, could this mean the end of using traditional analog sensors? IO-Link is the first IO technology standard (IEC 61131-9) for communications between sensors and actuators on the lower component level.

Analog sensors

A typical analog sensor detects an external parameter, such as pressure, sound or temperature, and provides an analog voltage or current output that is proportional to its measurement. The output values are then sent out of the measuring sensor to an analog card, which reads in the samples of the measurements and converts them to a digital binary representation which a PLC/controller can use. At both ends of the conversion, on the sensor side and the analog card side, however, the quality of the transmitted value can be affected. Unfortunately, noise and electrical interferences can affect the analog signals coming out of the sensor, degrading it over the long cable run. The longer the cable, the more prone to interference on the signal. Therefore, it’s always recommended to use shielded cables between the output of the analog sensor to the analog card for the conversion. The cable must be properly shielded and grounded, so no ground loops get induced.

Also, keep in mind the resolution on the analog card. The resolution is the number of bits the card uses to digitalize the analog samples it’s getting from the sensor. There are different analog cards that provide 10-, 12-, 14-, and 16-bit value representations of the analog signal. The more digital bits represented, the more precise the measurement value.

IO-Link sensor—less interference, less expensive and more diagnostic data

With IO-Link as the sensor output, the digital conversion happens at the sensor level, before transmission. The measured signal gets fed into the onboard IO-Link chipset on the sensor where it is converted to a digital output. The digital output signal is then sent via IO-Link directly to a gateway, with an IO-Link master chipset ready to receive the data. This is done using a standard, unshielded sensor cable, which is less expensive than equivalent shielded cables. And, now the resolution of the sensor is no longer dependent on the analog card. Since the conversion to digital happens on the sensor itself, the actual engineering units of the measured value is sent directly to the IO-Link master chipset of the gateway where it can be read directly from the PLC/controller.

Plus, any parameters and diagnostics information from the sensor can also be sent along that same IO-Link signal.

So, while analog sensors will never completely disappear on older networks, IO-Link provides good reasons for their use in newer networks and machines.

To learn about the variety of IO-Link measurement sensors available, read the Automation Insights post about ways measurement sensors solve common application challenges. For more information about IO-Link and measurement sensors, visit www.balluff.com.