Pressure-Rated Inductive Sensors Add Security in Mobile Equipment

Manufacturers of mobile equipment have long understood the benefits of replacing mechanical switches with the non-contacting technology of inductive sensors.  Inductive sensors provide wear-free position feedback in a sealed housing suitable for demanding environments.  But some applications may require a different approach if potential mounting issues or sensing ranges are a concern.  For instance, as the mobile machine ages and bushings wear due to typical daily operations, the sensing air gap between the linkage to be sensed and the sensor face may increase beyond the sensor’s optimum working range.   If this scenario is possible, periodic maintenance will be required to adjust the sensor mounting to compensate for the increasing wear.  Another consideration is the mounting bracket itself, and the likelihood of misalignment due to physical contact.

Many off road applications requiring sensor feedback involve hydraulic cylinders.  If these cases, a pressure-rated inductive sensor installed inside a cylinder or valve may be the better design choice.  Pressure-rated inductive sensors are offered with a variety of discrete outputs with numerous housing styles and connections.  Utilizing non-contact switching, stainless steel housings, and sealed to pressures up to 500 Bar, the sensors are designed to provide reliable feedback under the harsh conditions of off highway applications.

Mounting a pressure-rated inductive sensor into a cylinder or valve is straightforward, and very similar to the preparation of a hydraulic port:

      1. the sensor is threaded into the cylinder wall
      2. the sensing air gap is set
      3. the provided nut locks down the sensor
      4. a cable or connector is attached.

Day-to-day wear of the machine no longer affects the sensing gap and the sensor benefits from the additional protection of being installed into the cylinder, avoiding mounting mishaps and is better protected from external damage.

An outrigger application is a good example of the added benefits of using a pressure-rated inductive sensor.  Outriggers are used in cranes, firetrucks, aerial devices, and other mobile machines to provide lateral stability.  Mechanical switches and standard inductive sensors are used to denote when the outrigger is fully raised, lowered, etc.  A standard external sensor will do a good job as long as the mounting is intact and the sensing gap is within the proper range.  But a pressure-rated inductive sensor mounted internally into the hydraulic cylinder takes the worry out of those potential failure scenarios.

Applications with locking cylinders should also be considered.  Many locking cylinder applications are associated with a safety feature, where feedback that the cylinder is locked is critical.  An example would be the rear hatch of a refuse truck.  Occasionally, a worker may need to get inside the rear of a refuse truck.  With the rear hatch raised hydraulically, there’s a possibility that the rear hatch closes with gravity.  Positive feedback that the cylinder is locked is reassuring.

Therefore to reduce downtime caused by wear, to eliminate the misalignment of a mounting bracket, or to ensure your locking cylinder is absolutely locked, consider going “internal” to increase the quality and security of your application.

Implement a Smart Factory Using Available Technologies

What is a Smart Factory?

The term smart factory describes a highly digitalized and connected system where machines and equipment using sensor technology improves processes through monitoring, automation, and optimization. The wealth of data enables predictive maintenance and an increase in productivity through planning and decreased downtime.

The smart factory’s core building blocks are various intelligent sensors that provide a critical measure for the machine’s health, such as temperature, vibration, and pressure. This data combined with production, information, and communication technologies forms the backbone of what many refer to as the next industrial revolution, i.e., Industry 4.0.

The technologies that make the Industrial Internet of things or Industry 4.0 possible have always been available for the information technology domain. The same technology and software can be used to implement the next generation of industries.

How would I go about implanting these technologies?

The prerequisite to implementing any smart factory is using a sensor(s) with the ability to provide sensing information and to monitor its health. For example, an optical laser sensor can measure distance and monitor the beam’s strength reflected, alerting that the glass window might be foggy or dirty. These sensors are readily available in the market as most IO-Link sensors come with the diagnostics inbuilt. However, it varies from vendor to vendor.

The second step is getting the data from the operational technology side to the information technology level. The industrial side of things uses PLCs for control, which should be left alone as the single source of control for security reasons and efficiency. However, most IO-Link-enabled network blocks can tap into this data in read-only mode using JSON (JavaScript Object Notation) or a REST API.  With the IO-Link consortium officially formalizing the REST API, we will see more and more vendors adopting it as a feature for their network blocks

The final step is using this data to visualize and optimize the process. There are various SCADA and MES software systems that make it possible to do this without much development. But for maximum customizability, it’s recommended to build a stack that fits your needs and provides the option to scale. There are very mature open-source software options and applications that have been in used in the IT world for decades now and transfer seamlessly to the industrial side.

A data visualization of the current and amperage of an IO-Link device

The stack I have personally used and seen other companies implement is Grafana as a dashboarding software, InfluxdB as a time-series database, telegraf as a collector, and Mosquitto as MQTT broker.

The possibilities for expansion are limitless, leaving the option to add another service like TensorFlow for some analytics.

All of these are deployed as container services using Docker, another open-source project. This helps for easy deployment and maintenance.

A demonstration of this stack can be seen at the following link

https://balluff.app

Username and password are both “balluff” (all lowercase).

Top 5 Insights from 2020

With a new year comes new innovation, experience and insights. Before we jump into new topics for this year, let’s not forget some of the hottest topics from last year. Below are the five most popular blogs from our site in 2020.

1. Buying a Machine Vision System? Focus on Capabilities, Not Cost

Gone are the days when an industrial camera was used only to take a picture and send it to a control PC. Machine vision systems are a much more sophisticated solution. Projects are increasingly demanding image processing, speed, size, complexity, defect recognition and so much more…

READ MORE>>

2. 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…

READ MORE>>

3. Do Your Capacitive Sensors Ignore Foam & Condensation for True Level Detection?

Capacitive sensors detect any changes in their electrostatic sensing field. This includes not only the target material itself, but also application-induced influences such as condensation, foam, or temporary or permanent material build-up. High viscosity fluids can cause extensive delays in accurate point-level detection or cause complete failure due to the inability of a capacitive sensor to compensate for the material adhering to the container walls…

READ MORE>> 

4. Reduce the Number of Ethernet Nodes on Your Network Using IO-Link

Manufacturers have been using industrial Ethernet protocols as their controls network since the early 1990s. Industrial Ethernet protocols such as Ethernet/IP, ProfiNet, and Modbus TCP were preferred over fieldbus protocols because they offered the benefits of higher bandwidth, open connectivity and standardization, all while using the same Ethernet hardware as the office IT network. Being standard Ethernet also allows you to remotely monitor individual Ethernet devices over the network for diagnostics and alarms, delivering greater visibility of the manufacturing data…

READ MORE>>

5. Adding a higher level of visibility to older automation machines

It’s never too late to add more visibility to an automation machine. In the past, when it came to IO-Link opportunities, if the PLC on the machine was a SLC 500, a PLC-5, or worse yet, a controller older than I, there wasn’t much to talk about. In most of these cases, the PLC could not handle another network communication card, or the PLC memory was maxed, or it used a older network like DeviceNet, Profibus or ASi that was maxed. Or it was just so worn out that it was already being held together with hope and prayer. But, today we can utilize IIoT and Industry 4.0 concepts to add more visibility to older machines…

READ MORE>>

We appreciate your dedication to Automation Insights in 2020 and look forward to growth and innovation in 2021!

Which 3D Vision Technology is Best for Your Application?

3D machine vision. This is such a magical combination of words. There are dozens of different solutions on the market, but they are typically not universal enough or they are so universal that they are not sufficient for your application. In this blog, I will introduce different approaches for 3D technology and review what principle that will be the best for future usage.

Bonus:  I created a poll asking professionals what 3D vision technology they believe is best and I’ve shared the results.

Triangulation

One of the most used technologies in the 3D camera world is triangulation, which provides simple distance measurement by angular calculation. The reflected light falls incident onto a receiving element at a certain angle depending on the distance. This standard method relies on a combination of the projector and camera. There are two basic variants of the projections — models with single-line structure and 2-dimensional geometric pattern.

A single projected line is used in applications where the object is moving under the camera. If you have a static object, then you can use multiple parallel lines that allow the evaluation of the complete scene/surface. This is done with a laser light shaped into a two-dimensional geometric pattern (“structured light”) typically using a diffractive optical element (DOE). The most common patterns are dot matrices, line grids, multiple parallel lines, and circles.

Structured light

Another common principle of 3D camera technology is the structured light technique. System contains at least one camera (it is most common to use two cameras) and a projector. The projector creates a narrow band of light (patterns of parallel stripes are widely used), which illuminate the captured object. Cameras from different angles observe the various curved lines from the projector.

Projecting also depends on the technology which is used to create the pattern. Currently, the three most widespread digital projection technologies are:

  • transmissive liquid crystal,
  • reflective liquid crystal on silicon (LCOS)
  • digital light processing (DLP)

Reflective and transparent surfaces create challenges.

Time of Flight (ToF)

For this principle, the camera contains a high-power LED which emits light that is reflected from the object and then returns to the image sensor. The distance from the camera to the object is calculated based on the time delay between transmitted and received light.

This is really simple principle which is used for 3D applications. The most common wavelength used is around 850nm. This is called near infrared range, which is invisible for human and eye safety.

This is an especially great use since the camera can standardly provide 2D as well as 3D picture in the same time.

An image sensor and LED emitter are used as an all-in-one product making it simple to integrate and easy to use. However, a negative point is that the maximum resolution is VGA (640 x 480) and  for Z resolution expect +/- 1cm. On the other hand, it is an inexpensive solution with modest dimensions.

Likely applications include:

  • mobile robotics
  • door controls
  • localization of the objects
  • mobile phones
  • gaming consoles (XBOX and Kinect camera) or industrial version Azure Kinect.

Stereo vision

The 3D camera by stereo vision is a quite common method that typically includes two area scan sensors (cameras). As with human vision, 3D information is obtained by comparing images taken from two locations.

The principle, sometimes called stereoscopic vision, captures the same scene from different angles. The depth information is then calculated from the image pixel disparities (difference in lateral position).

The matching process, finding the same information with the right and left cameras, is critical to data accuracy and density.

Likely applications include:

  • Navigation
  • Bin-picking
  • Depalletization
  • Robotic guidance
  • Autonomous Guiding Vehicles
  • Quality control and product classification

I asked my friends, colleagues, professionals, as well as competitors, on LinkedIn what is the best 3D technology and which technology will be used in the future. You can see the result here.

As you see, over 50% of the people believe that there is no one principle which can solve each task in 3D machine vision world. And maybe that’s why machine vision is such a beautiful technology. Many approaches, solutions and smart people can bring solutions from different perspectives and accesses.

Using Long-Range RFID for Metal Stamping Die Identification

Using incorrect dies for metal stamping operations can result in lost time and production as well as severe damage to the presses and a risk to human lives.

In recent years, there was a case where the use of the incorrect die caused catastrophic press damage resulting in significant downtime and, because the press was so large, it had to be cut up before it could be removed and replaced. These types of occurrences can prove disastrous to the survival of a company.

When not in use, dies are generally stored in specified storage areas. Often, the die is in the wrong place, and the crane operator needs to know what he/she is retrieving for the next process in the correct die.

To help ensure that these types of errors do not occur, some manufacturers use long-range UHF RFID technology. This can ensure that the correct dies are chosen when they are staged outside of a press. And with handheld devices, it can help the operator find the correct die in storage if it has been misplaced.

Since long-range UHF RFID technology allows the verification of the correct dies from as little as one foot away to as far as several meters, it can be used in both large and small stamping presses. The long-range allows the reader antennas to be placed in strategic locations where the correct readings will be possible but in positions where they will not be damaged by the operation of the press and dies.

I recently assisted with a metal stamping operation that first brought this idea to my attention. This manufacturer was having the problem of the wrong dies being staged for installation into the press. So far, none of the dies had made it past the staging area and into the press. Still, the possibility of that happening was clearly present, and they were experiencing lost production due to having to remove the incorrect die and find the correct one.

The manufacturer wanted to interlock the press so that if the incorrect dies were not in place, the machine would not be able to run. He also wanted to know ahead of time of a wrong die so that it could be replaced promptly to not impact production.

The solution we developed was to place multiple reader antennas at multiple staging locations at the press and interlock the RFID reads with the PLC that controlled the press.

Additionally, he incorporated handheld readers to help find misplaced dies in the storage area.

This solution required testing and tuning of the UHF RFID system to ensure that all die RFID tags were being read when the dies were staged. But once this was completed, it proved to work effectively and reduce the errors and downtime.

It should be noted that due to the physics of UHF RFID technology versus other types of RFID technology, implementing long-range UHF RFID systems in any application should be preceded by a feasibility study that tests the system in the real world environment of the plant.

Be Driven by Data and Decrease Downtime

Being “driven by data” is simply the act of making decisions based on real data instead of guessing or basing them on theoretical outcomes. Why one should do that, especially in manufacturing operations, is obvious. How it is done is not always so clear.

Here is how you can use a sensor, indicator light, and RFID to provide feedback that drives overall quality and efficiency.

 

Machine Condition Monitoring

You’ve heard the saying, “if it ain’t broke, don’t fix it.” However, broken machines cause downtime. What if there was a way to know when a machine is getting ready to fail, and you could fix it before it caused downtime? You can do that now!

The two main types of data measured in manufacturing applications are temperature and vibration. A sudden or gradual increase in either of these is typically an indicator that something is going wrong. Just having access to that data won’t stop the machine from failing, though. Combined with an indicator light and RFID, the sensor can provide real-time feedback to the operator, and the event can be documented on the RFID tag. The machine can then be adjusted or repaired during a planned maintenance period.

Managing Quality – A machine on its way to failure can produce parts that don’t meet quality standards. Fixing the problem before it affects production prevents scrap and rework and ensures the customer is getting a product with the quality they expect.

Managing Efficiency– Unplanned downtime costs thousands of dollars per minute in some industries. The time and resources required to deal with a failed machine far exceed the cost of the entire system designed to produce an early warning, provide indication, and document the event.

Quality and efficiency are the difference makers in manufacturing. That is, whoever makes the highest quality products most efficiently usually has the most profitable and sustainable business. Again, why is obvious, but how is the challenge. Hopefully, you can use the above data to make higher quality products more efficiently.

 

More to come! Here are the data-driven topics I will cover in my next blogs:

  • Part inspection and data collection for work in process
  • Using data to manage molds, dies, and machine tools

Tag, You’re It: Choosing the Right Type of Tags for Your RFID System

Many companies have already discovered the benefits of implementing RFID into their systems. Traceability within the manufacturing process provides a competitive advantage of both efficiency and profitability. RFID tags are a major component of this technology. But it’s important to select the correct type for your specific application. These tags are classified into categories based on how they obtain power and how they use that power. The three categories are as follows:

  • Passive tags
  • Semi-passive tags
  • Active tags

Understanding the difference between these can help narrow down your decision when looking into implementing RFID systems to your process.

Passive tags do not have their own power source. The tag receives power only when the RFID reader is in range. These tags are limited since the power supplied is minimal. The biggest advantages of passive tags are that they are small and inexpensive. They can be useful in specific applications where space is limited. Also, if the environment in which the tag is being placed is harsh, the passive tag may be a good option because it can be cheaply replaced if damaged. Since these tags do not generate power, their read distance of just a few inches to about two feet is much shorter than others. Passive tags are also limited to the amount of data storage they possess. Depending on the application this can be an advantage or disadvantage.

Semi-Passive tags, as the name implies, are similar to passive tags in that they do not have an active transmitter. They still require an RFID interrogator to be in range for the device to work, although the semi-passive tags have their own battery to power the IC. If you are looking for longer read ranges than the passive tag, this could be an option. Since the read range of the passive sensor is solely based on how far away the interrogator can power the device and not the signals coming in, adding a battery unit to the semi-passive tags increases this distance. These distances can range up to 100 feet. Another advantage is the amount of data they can store. These added features do come with added costs. The onboard power supply also makes these tags larger and heavier. The electronics inside the tag are susceptible to harsh environments like high or low temperatures, resulting in shorter lifespans.

Active tags have both a battery and transmitter built within their housings. The typical read range is again increased to around 300 to 750 feet depending on the battery power and the antenna. This allows the tags to store more data with their increased memory capacity. Active tags display the most configurability in comparison to passive and semi-passive tags. They can be set up to conserve battery power when the interrogator is out of range and respond only when the reader is within range. They can also be set up as a beacon, which is when the tag does not wait until it receives a signal from the interrogator. Instead, the active tag can be configured to send the information in set time intervals. Since active tags contain an active transmitter, they can contribute to radio noise. They are also more expensive and usually larger in size and weight due to the increased electronics within its housing.

It’s important when selecting a tag for your RFID system to consider the application needs and the advantages and disadvantages of these different options.

Machine Vision: A Twenty-first Century Automation Solution

Lasers, scanners, fingerprint readers, and face recognition is not just science fiction anymore.  I love seeing technology only previously imagined become reality through necessity and advances in technology.  We, as a world economy, need to be able to verify who we are and ensure transitions are safe, and material and goods are tracked accurately.  With this need came the evolution of laser barcode readers, fingerprint identification devices, and face ID on your phone.  Similar needs have pushed archaic devices to be replaced within factory automation for data collection.

When I began my career in control engineering the 1990s high tech tools were limited to PLCs, frequency drives, and HMIs. The quality inspection data these devices relied on was collected mostly through limit switches and proximity sensors.  Machine vision was still in it’s expensive and “cute” stage.  With the need for more information, seriously accurate measurement, machining specs, and speed; machine vision has evolved, just like our personal technology has, to fill the needs of the modern time.

Machine vision has worked its way into the automation world as a need to have rather than a nice to have.  With the ability to stack several tools and validations on top of each other, within a fraction of a second scan we now have the data our era needs to stay competitive.  Imagine an application requiring you to detect several material traits, measure the part, read a barcode for tracking, and validate  a properly printed logo screened onto the finished product.  Sure, you could use several individual laser sensors, barcode readers and possibly even a vision sensor all working in concert to achieve your goal.  Or you could use a machine vision system to do all the above easily with room to grow.

I say all of this because there is still resistance in the market to move to machine vision due to historical high costs and complexity.  Machine Vision is here to stay and ready for your applications today.  Think of it this way.  How capable would you think a business is they took out a carbon copy credit card machine to run a payment for you?  Well, think of this before you start trying to solve applications with several sensors.  Take advantage of the technology at your fingertips; don’t hold on to nostalgia.

Industry 4.0: What It Is and How It Improves Manufacturing

Industry 4.0 is a common buzzword that is thrown around along with IIoT and Process visualization but what does that mean and how is it integrated into a manufacturing process? Industry 4.0 refers to the fourth industrial revolution. The first dealing with mechanization and the use of steam and water power, the second referring to mass production using assembly lines and electrical power, and the third referring to automated production and the use of computers and robots. Industry 4.0 takes us a step beyond that to smart factories that include automation and machine learning. Again, buzzwords that can be hard to visualize.

A commonplace example of this would be self-driving cars. They are autonomous because they don’t need a person operating them and they take, in real time, information about their surroundings and use that to determine a course of action. But how can this type of technology affect a manufacturing process?

Industry 4.0 requires data to be analyzed. This is where IO-Link comes into play. With IO-Link, you are able to get information from a sensor more than than just an output signal when it detects a part. A photoelectric sensor is a good example of this. The basic way a photoelectric sensor works an output is given depending on the amount of light being received. If the sensor happens to be in a dirty/dusty environment, there could be dirt collecting on the lens or floating in the air which effects the amount of light being received. An IO-Link (smart) sensor can not only fire an output when detection occurs but can give information about the real time gain of the sensor (how much light is being received). If the gain drops below a certain amount because of dirt on the lens or in the air, it can send another signal to the controller indicating the change in gain.

Now that we have more data, what are we going to do with it?

We now have all of this data coming from different parts of the machine, but where does it go and what do we do with it? This is where process visualization comes into play. We are able to take real time data from a machine and upload it to a database or system that we can monitor outside of the plant floor. We can know if a machine is running properly without having to physically see the machine. The information can also give us indications about when something might fail so preventative maintenance can take place and reduce downtime.

As more manufacturing processes are becoming automated, machines are becoming more and more complex. A machine might be needed to run 6-7 different lines rather than just 1 or 2 which can involve things like tool change or settings changes. Then, more checks need to be in place, so the right process is running for the right part. Industry 4.0 is how we are able to gather all this information and use it to increase efficiency and productivity.

Adding Smart Condition Monitoring Sensors to Your PLC Control Systems Delivers Data in Real Time

Condition monitoring of critical components on machines delivers enormous benefits to productivity in a plant.  Rather than have a motor, pump, or compressor unexpectedly fail and the machine be inoperable until a replacement part is installed, condition monitoring of those critical pieces on the machine can provide warning signs that something is about to go terribly wrong. Vibration measurements on rotating equipment can detect when there is imbalance or degrade on rolling bearing elements. Temperature measurements can detect when a component is getting overheated and should be cooled down. Other environmental detections such as humidity and ambient pressure can alert someone to investigate why humidity or pressure is building up on a component or in an area. These measurement points are normally taken by specific accelerometers, temperature probes, humidity and pressure sensors and then analyzed through high end instruments with special analysis software. Typically, these instruments and software are separate from the PLC controls system. This means that even when the data indicates a future potential issue, steps need to be taken separately to stop the machine from running.

Using smart condition monitoring sensors with IO-Link allows these measured variables and alarms to be available directly onto the PLC system in real time. Some condition monitoring sensors now even have microprocessors onboard that immediately analyze the measured variables. The sensor can be configured for the measurement limit thresholds of the device it’s monitoring so that the sensor can issue a warning or alarm through the IO-Link communications channel to the PLC once those thresholds have been hit. That way, when a warning condition presents itself, the PLC can react immediately to it, whether that means sending an alert on a HMI, or stopping the machine from running altogether until the alarmed component is fixed or replaced.

Having the condition monitoring sensor on IO-Link has many advantages. As an IEC61131-9 standard, IO-Link is an open standard and not proprietary to any manufacturer. The protocol itself is on the sensor/actuator level and fieldbus independent. IO-Link allows the condition monitoring sensor to connect to Ethernet/IP, Profinet & Profibus, CC-Link & CC-Link IE Field, EtherCAT and TCP/IP networks regardless of PLC. Using an IO-Link master gateway, multiple smart condition monitoring sensors and other IO-Link devices can be connected to the controls network as a single node.

The picture above shows two condition monitoring sensors connected to a single address on the fieldbus network. In this example, a single gateway allows up to eight IO-Link condition monitoring sensors to be connected.

Through IO-Link, the PLC’s standard acyclic channel can be used to setup the parameters of the measured alarm conditions to match the specific device the sensor is monitoring. The PLC’s standard cyclic communications can then be used to monitor the alarm status bits from the condition monitoring sensor.  When an alarm threshold gets hit, the alarm status bit goes high and the PLC can then react in real time to control the machine. This relieves the burden of analyzing the sensor’s condition monitoring data from the PLC as the sensor is doing the work.