Weld Immune vs. Weld Field Immune: What’s the difference? 

In today’s automotive plants and their tier suppliers, the weld cell is known to be one of the most hostile environments for sensors. Weld slag accumulation, elevated ambient temperatures, impacts by moving parts, and strong electromagnetic fields can all degrade sensor performance and cause false triggering. It is widely accepted that sensors will have a limited life span in most plants.

Poor sensor selection does mean higher failure rates which cause welders in all industries increased downtime, unnecessary maintenance, lost profits, and delayed delivery. There are many sensor features designed specifically to withstand these harsh welding environments and the problems that come along with them to combat this.

In the search for a suitable sensor for your welding application, you are sure to come across the terms weld immune and weld field immune. What do these words mean? Are they the same thing? And will they last in my weld cell?

Weld Immune ≠ Weld Field Immune

At first glance, it is easy to understand why someone may confuse these two terms or assume they are one and the same.

Weld field immune is a specific term referring to sensors designed to withstand strong electromagnetic fields. In some welding areas, especially very close to the weld gun, welders can generate strong magnetic fields. When this magnetic field is present, it can cause a standard sensor to perform intermittently, like flickering and false outputs.

Weld field immune sensors have special filtering and robust circuitry that withstand the influence of strong magnetic fields and avoid false triggers. This is also called magnetic field immune since they also perform well in any area with high magnetic noise.

On the other hand, weld immune is a broad term used to describe a sensor designed with any features that increase its performance in a welding application. It could refer to one or multiple sensor features, including:

    • Weld spatter resistant coatings
    • High-temperature resistance
    • Different housing or sensor face materials
    • Magnetic field immunity

A weld field immune sensor might be listed with the numerous weld immune sensors with special coatings and features, but that does not necessarily mean any of those other sensors are immune to weld fields. This is why it is always important to check the individual sensor specifications to ensure it is suitable for your application.

In an application where a sensor is failing due to impact damage or weld slag spatter, a steel face sensor with a weld resistant coating could be a great solution. If this sensor isn’t close to the weld gun and isn’t exposed to any strong magnetic fields, there is really no need for it to be weld field immune. The important features are the steel face and coating that can protect it against impact and weld slag sticking to it. This sensor would be classified as weld immune.

In another application where a sensor near the weld gun side of the welding procedure where MIG welding is performed, this location is subject to arc blow that can create a strong magnetic field at the weld wire tip location. In this situation, having a weld field immune sensor would be important to avoid false triggers that the magnetic field may cause. Additionally, being close to a MIG weld gun, it would also be wise to consider a sensor with other weld immune properties, like a weld slag resistant coating and a thermal barrier, to protect against high heat and weld slag.

Weld field immunity is just one of many features you can select when picking the best sensor for your application. Whether the issue is weld slag accumulation, elevated ambient temperatures, part impact, or strong electromagnetic fields, there are many weld immune solutions to consider. Check the placement and conditions of the sensors you’re using to decide which weld-immune features are needed for each sensor.

Click here for more on choosing the right sensor for your welding application.

 

Does Your Stamping Department Need a Checkup? Try a Die-Protection Risk Assessment

If you have ever walked through a stamping department at a metal forming facility, you have heard the rhythmic sound of the press stamping out parts, thump, thump. The stamping department is the heart manufacturing facility, and the noise you hear is the heartbeat of the plant. If it stops, the whole plant comes to a halt. With increasing demands for higher production rates, less downtime, and reduction in bad parts, stamping departments are under ever-increasing pressure to optimize the press department through die protection and error-proofing programs.

The die-protection risk assessment team

The first step in implementing or optimizing a die protection program is to perform a die-protection risk assessment. This is much like risk assessments conducted for safety applications, except they are done for each die set. To do this, build a team of people from various positions in the press department like tool makers, operators, and set-up teams.

Once this team is formed, they can help identify any incidents that could occur during the stamping operations for each die set and determine the likelihood and the severity of possible harm. With this information, they can identify which events have a higher risk/severity and determine what additional measures they should implement to prevent these incidents. An audit is possible even if there are already some die protection sensors in place to determine if there are more that should be added and verify the ones in place are appropriate and effective.

The top 4 die processes to check

The majority of quality and die protection problems occur in one of these three areas: material feed, material progression, and part- and slug-out detections. It’s important to monitor these areas carefully with various sensor technologies.

Material feed

Material feed is perhaps the most critical area to monitor. You need to ensure the material is in the press, in the correct location, and feeding properly before cycling the press. The material could be feeding as a steel blank, or it could come off a roll of steel. Several errors can prevent the material from advancing to the next stage or out of the press: the feed can slip, the stock material feeding in can buckle, or scrap can fail to drop and block the strip from advancing, to name a few. Inductive proximity sensors, which detect iron-based metals at short distances, are commonly used to check material feeds.

Material progression

Material progression is the next area to monitor. When using a progressive die, you will want to monitor the stripper to make sure it is functioning and the material is moving through the die properly. With a transfer die, you want to make sure the sheet of material is nesting correctly before cycling the press. Inductive proximity sensors are the most common sensor used in these applications, as well.

Here is an example of using two inductive proximity sensors to determine if the part is feeding properly or if there is a short or long feed. In this application, both proximity sensors must detect the edge of the metal. If the alignment is off by just a few millimeters, one sensor won’t detect the metal. You can use this information to prevent the press from cycling to the next step.

Short feed, long feed, perfect alignment

Part-out detection

The third critical area that stamping departments typically monitor is part-out detection, which makes sure the finished part has come out of the stamping

area after the cycle is complete. Cycling the press and closing the tooling on a formed part that failed to eject can result in a number of undesirable events, like blowing out an entire die section or sending metal shards flying into the room. Optical sensors are typically used to check for part-out, though the type of photoelectric needed depends on the situation. If the part consistently comes out of the press at the same position every time, a through-beam photo-eye would be a good choice. If the part is falling at different angles and locations, you might choose a non-safety rated light grid.

Slug-ejection detection

The last event to monitor is slug ejection. A slug is a piece of scrap metal punched out of the material. For example, if you needed to punch some holes in metal, the slug would be the center part that is knocked out. You need to verify that the scrap has exited the press before the next cycle. Sometimes the scrap will stick together and fail to exit the die with each stroke. Failure to make sure the scrap material leaves the die could affect product quality or cause significant damage to the press, die, or both. Various sensor types can ensure proper scrap ejection and prevent crashes. The picture below shows a die with inductive ring sensors mounted in it to detect slugs as they fall out of the die.

Just like it is important to get regular checkups at the doctor, performing regular die-protection assessments can help you make continuous improvements that can increase production rates and reduce downtime. Material feed, material progression, part-out and slug-out detection are the first steps to optimize, but you can expand your assessments to include areas like auxiliary equipment. You can also consider smart factory solutions like intelligent sensors, condition monitoring, and diagnostics over networks to give you more data for preventative maintenance or more advanced error-proofing. The key to a successful program is to assemble the right team, start with the critical areas listed above, and learn about new technologies and concepts that are becoming available to help you plan ways to improve your stamping processes.

Control Meets IIoT, Providing Insights into a New World

In manufacturing and automation control, the programmable logic controller (PLC) is an essential tool. And since the PLC is integrated into the machine already, it’s understandable that you might see the PLC as all that you need to do anything in automation on the manufacturing floor.

Condition monitoring in machine automation

For example, process or condition monitoring is emerging as an important automation feature that can help ensure that machines are running smoothly. This can be done by monitoring motor or mechanical vibration, temperature or pressure. You can also add functionality for a machine or line configuration or setup by adding sensors to verify fixture locations for machine configuration at changeovers.

One way to do this is to wire these sensors to the PLC and modify its code and use it as an all-in-one device. After all, it’s on the machine already. But there’s a definite downside to using a PLC this way. Its processing power is limited, and there are limits to the number of additional processes and functions it can run. Why risk possible complications that could impact the reliability of your control systems? There are alternatives.

External monitoring and support processes

Consider using more flexible platforms, such as an edge gateway, Linux, and IO-Link. These external sources open a whole new world of alternatives that provide better reliability and more options for today and the future. It also makes it easier to access and integrate condition monitoring and configuration data into enterprise IT/OT (information technology/operational technology) systems, which PLCs are not well suited to interface with, if they can be integrated at all.

Here are some practical examples of this type of augmented or add-on/retrofit functionality:

      • Motor or pump vibration condition monitoring
      • Support-process related pressure, vibration and temperature monitoring
      • Monitoring of product or process flow
      • Portable battery based/cloud condition monitoring
      • Mold and Die cloud-based cycle/usage monitoring
      • Product changeover, operator guidance system
      • Automatic inventory monitoring warehouse system

Using external systems for these additional functions means you can readily take advantage of the ever-widening availability of more powerful computing systems and the simple connectivity and networking of smart sensors and transducers. Augmenting and improving your control systems with external monitoring and support processes is one of the notable benefits of employing Industrial Internet of Things (IIoT) and Industry 4.0 tools.

The ease of with which you can integrate these systems into IT/OT systems, even including cloud-based access, can dramatically change what is now available for process information-gathering and monitoring and augment processes without touching or effecting the rudimentary control system of new or existing machines or lines. In many cases, external systems can even be added at lower price points than PLC modification, which means they can be more easily justified for their ROI and functionality.

IO-Link Benefits in Robotic Weld Cell Tooling

By Scott Barhorst

Working previously as a controls engineering manager in robotic welding, I have seen some consistent challenges when designing robotic weld cell systems.

For example, the pre-engineered-style welding cells I’ve worked with use many types of tooling. At the same time, space for tooling and cabling is limited, and so is the automation on board, with some using PLC function and others using a robot controller to process data.

One approach that worked well was to use IO-Link in the systems I designed. With its simple open fieldbus communication interface and digital transmission, it brought a number of benefits.

    1.  IO-Link’s digital signals aren’t affected by noise, so I could use smart sensors and connect them with unshielded 4-pin cables.
    2.  Expandability was easy, either from the Master block or by adding discrete I/O modules.
    3.  IO-Link can use the ID of the block to identify the fixture it is associated with to make sure the correct fixture is in the correct location.
    4.  Cabling is simplified with IO-Link, since the IO-Link Master can control both inputs, outputs, and control valve packs. That means that the only cables needed will be 24V power, Ethernet, weld ground (depending on the system), and air.
    5.  Fewer cables means less cost for cables and installation, cable management is improved, and there are fewer cables to run through a tailstock or turntable access hole.

One system I designed used 1 IO-Link Master block, 3 discrete I/O modules, and 1 SMC valve manifold controlled via IO-Link. This tooling had 16 clamps and 10 sensors, requiring 42 total inputs and control of 16 valves. The system worked very well with this setup!

An additional note: It’s good to think beyond the process at hand to how it might be used in the future. A system built on IO-Link is much more adaptable to different tooling when a change-over is needed. Click here to read more about how to use IO-Link in welding environments.

 

 

 

 

 

Add Depth to Your Processes With 3D Machine Vision

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

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

See For Yourself

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

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

How 3D Saves the Day

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

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

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

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

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.

Controls Architectures Enable Condition Monitoring Throughout the Production Floor

In a previous blog post we covered some basics about condition monitoring and the capability of smart IO-Link end-devices to provide details about the health of the system. For example, a change in vibration level could mean a failure is near.

This post will detail three different architecture choices that enable condition monitoring to add efficiency to machines, processes, and systems: in-process, stand-alone, and hybrid models.

IO-Link is the technology that enables all three of these architectures. As a quick introduction, IO-Link is a data communications technology at the device level, instead of a traditional signal communication. Because it communicates using data instead of signals, it provides richer details from sensors and other end devices. (For more on IO-Link, search the blog.)

In-process condition monitoring architecture

In some systems, the PLC or machine controller is the central unit for processing data from all of the devices associated with the machine or system, synthesizing the data with the context, and then communicating information to higher-level systems, such as SCADA systems.

The data collected from devices is used primarily for controls purposes and secondarily to collect contextual information about the health of the system/machine and of the process. For example, on an assembly line, an IO-Link photo-eye sensor provides parts presence detection for process control, as well as vibration and inclination change detection information for condition monitoring.

With an in-process architecture, you can add dedicated condition monitoring sensors. For example, a vibration sensor or pressure sensor that does not have any bearings on the process can be connected and made part of the same architecture.

The advantage of an in-process architecture for condition monitoring is that both pieces of information (process information and condition monitoring information) can be collected at the same time and conveyed through a uniform messaging schema to higher-level SCADA systems to keep temporal data together. If properly stored, this information could be used later for machine improvements or machine learning purposes.

There are two key disadvantages with this type of architecture.

First, you can’t easily scale this system up. To add additional sensors for condition monitoring, you also need to alter and validate the machine controller program to incorporate changes in the controls architecture. This programming could become time consuming and costly due to the downtime related to the upgrades.

Second, machine controllers or PLCs are primarily designed for the purposes of machine control. Burdening these devices with data collection and dissemination could increase overall cost of the machine/system. If you are working with machine builders, you would need to validate their ability to offer systems that are capable of communicating with higher-level systems and Information Technology systems.

Stand-alone condition monitoring architecture

Stand-alone architectures, also known as add-on systems for condition monitoring, do not require a controller. In their simplest form, an IO-Link master, power supply, and appropriate condition monitoring sensors are all that you need. This approach is most prevalent at manufacturing plants that do not want to disturb the existing controls systems but want to add the ability to monitor key system parameters. To collect data, this architecture relies on Edge gateways, local storage, or remote (cloud) storage systems.

 

 

 

 

 

 

The biggest advantage of this system is that it is separate from the controls system and is scalable and modular, so it is not confined by the capabilities of the PLC or the machine controller.

This architecture uses industrial-grade gateways to interface directly with information technology systems. As needs differ from machine to machine and from company to company as to what rate to collect the data, where to store the data, and when to issue alerts, the biggest challenge is to find the right partner who can integrate IT/OT systems. They also need to maintain your IT data-handling policies.

This stand-alone approach allows you to create various dashboards and alerting mechanisms that offer flexibility and increased productivity. For example, based on certain configurable conditions, the system can send email or text messages to defined groups, such as maintenance or line supervisors. You can set up priorities and manage severities, using concise, modular dashboards to give you visibility of the entire plant. Scaling up the system by adding gateways and sensors, if it is designed properly, could be easy to do.

Since this architecture is independent of the machine controls, and typically not all machines in the plant come from the same machine builders, this architecture allows you to collect uniform condition monitoring data from various systems throughout the plant. This is the main reason that stand-alone architecture is more sought after than in-process architecture.

It is important to mention here that not all of the IO-Link gateways (masters) available in the market are capable of communicating directly with the higher-level IT system.

Hybrid architectures for condition monitoring

As the name suggests, this approach offers a combination of in-process and stand-alone approaches. It uses IO-Link gateways in the PLC or machine controller-based controls architecture to communicate directly with higher-level systems to collect data for condition monitoring. Again, as in stand-alone systems, not all IO-Link gateways are capable of communicating directly with higher-level systems for data collection.

The biggest advantage of this system is that it does not burden PLCs or machine controllers with data collection. It creates a parallel path for health monitoring while devices are being used for process control. This could help you avoid duplication of devices.

When the devices are used in the controls loop for machine control, scalability is limited. By specifying IO-Link gateways and devices that can support higher-level communication abilities, you can add out-of-process condition monitoring and achieve uniformity in data collection throughout the plant even though the machines are from various machine builders.

Overall, no matter what approach is the best fit for your situation, condition monitoring can provide many efficiencies in the plant.

What is IO-Link? A Simple Explanation of the Universal Networking Standard

Famed physicist Albert Einstein once said, “If you can’t explain it simply, you don’t understand it well enough.” When the topic of IO-Link comes up, whether a salesperson or technical expert is doing the explaining, I always find it’s too much for the layman without a technical background to understand. To simplify this complex idea, I’ve created an analogy to something we use in our everyday lives: highways.  

Prior to the Federal Highway Act of 1956, each individual state, determined the rules of its state highway routes. This included everything from the width of the roads to the speed limits and the height of bridge underpasses — every aspect of the highways that were around at the time. This made long-distance travel and interstate commerce very difficult. It wasn’t until 1956 and the passage of President Eisenhower’s Federal Highway Act, that the rules became standard across the entire United States. Today, whether you’re in Houston, Boston or St. Louis, everything from the signage on the road to the speed limits and road markings are all the same. 

Like the standardization of national highway system, the IO-Link Consortium standardized the rules by which devices in automation communicate. Imagine your home as a controller, for example, the roads are cables, and your destination is a sensor. Driving your car to the store is analogous to a data packet traveling between the sensor and the controller.  

You follow the rules of the road, driving with a license and abiding by the speed limits, etc. Whether you’re driving a sedan, an SUV or a semitruck, you know you can reach your destination regardless of the state it’s in. IO-Link allows you to have different automation components from different suppliers, all communicating in sync unlike before, following a standard set of rules. This empowers the end user to craft a solution that fits his or her needs using sensors that communicate using the protocols set by the IO-Link Consortium. 

Choosing the Right Sensor for Your Welding Application

Automotive structural welding at tier suppliers can destroy thousands of sensors a year in just one factory. Costs from downtime, lost production, overtime, replacement time, and material costs  eat into profitability and add up to a big source of frustration for automated and robotic welders. When talking with customers, they often list inductive proximity sensor failure as a major concern. Thousands and thousands of proxes are being replaced and installations are being repaired every day. It isn’t particularly unusual for a company to lose a sensor on every shirt in a single application. That is three sensors a day  — 21 sensors a week — 1,100 sensors a year failing in a single application! And there could be thousands of sensor installations in an  automotive structural assembly line. When looking at the big picture, it is easy to see how this impacts the bottom line.

When I work with customers to improve this, I start with three parts of a big equation:

  • Sensor Housing
    Are you using the right sensor for your application? Is it the right form factor? Should you be using something with a coating on the housing? Or should you be using one with a coating on the face? Because sensors can fail from weld spatter hitting the sensor, a sensor with a coating designed for welding conditions can greatly extend the sensor life. Or maybe you need loading impact protection, so a steel face sensor may be the best choice. There are more housing styles available now than ever. Look at your conditions and choose accordingly.
  • Bunkering
    Are you using the best mounting type? Is your sensor protected from loading impact? Using a protective block can buffer the sensor from the bumps that can happen during the application.
  • Connectivity
    How is the sensor connected to the control and how does that cable survive? The cable is often the problem but there are high durability cable solutions, including TPE jacketed cables, or sacrificial cables to make replacement easier and faster.

When choosing a sensor, you can’t only focus on whether it can fulfill the task at hand, but whether it can fulfill it in the environment of the application.

For more information, visit Balluff.com

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.