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Using MQTT Protocol for Smarter Automation

In my previous blog post, “Edge Gateways to Support Real-Time Condition Monitoring Data,” I talked about the importance of using an edge gateway to gather the IoT data from sensors in parallel with a PLC. This was because of the large data load and the need to avoid interfering with the existing machine communications. In this post, I want to delve deeper into the topic and explain the process of implementing an edge gateway.

Using the existing Ethernet infrastructure

One way to collect IoT data with an edge gateway is by using the existing Ethernet infrastructure. With most devices already communicating on an industrial Ethernet protocol, an edge gateway can gather the data on the same physical Ethernet port but at a separate software-defined number associated to a network protocol communication.

Message Queue Telemetry Transport (MQTT)

One of the most commonly used IoT protocols is Message Queue Telemetry Transport (MQTT). It is an ISO standard and has a dedicated software Ethernet port of 1883 and 8883 for secure encrypted communications. One reason for its popularity is that it is designed to be lightweight and efficient. Lightweight means that the protocol requires a minimum coding and it uses low-bandwidth connections.

Brokers and clients

The MQTT protocol defines two entities: a broker and client. The edge gateway typically serves as a message broker that receives client messages and routes them to the appropriate destination clients. A client is any device that runs an MQTT library and connects to an MQTT broker.

MQTT works on a publisher and subscriber model. Smart IoT devices are set up to be publishers, where they publish different condition data as topics to an edge gateway. Other clients, such as PC and data centers, can be set up as subscribers. The edge gateway, serving as a broker receives all the published data and forwards it only to the subscribers interested in that topic.

One client can publish many different topics as well as be a subscriber to other topics. There can also be many clients subscribing to the same topic, making the architecture flexible and scalable.

The edge gateway serving as the broker makes it possible for devices to communicate with each other if the device supports the MQTT protocol. MQTT can connect a wide range of devices, from sensors to actuators on machines to mobile devices and cloud servers. While MQTT isn’t the only way to gather data, it offers a simple and reliable way for customers to start gathering that data with their existing Ethernet infrastructures.

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Automated Welding With IO-Link

IO-Link technologies have been a game-changer for the welding industry. With the advent of automation, the demand for increasingly sophisticated and intelligent technologies has increased. IO-Link technologies have risen to meet this demand. Here I explain the concepts and benefits of I-O Link technologies and how they integrate into automated welding applications.

What are IO-Link technologies?

IO-Link technologies refer to an advanced communication protocol used in industrial automation. The technology allows data transfer, i.e., the status of sensors, actuators, and other devices through a one-point connection between the control system and individual devices. Also, it enables devices to communicate among themselves quickly and efficiently. IO-Link technologies provide real-time communication, enabling continuous monitoring of devices to ensure optimal performance.

Benefits of IO-Link technologies

    • Enhanced data communication: IO-Link technologies can transfer data between the control system and sensors or devices. This communication creates an open and transparent network of information, reflecting the real-time status of equipment and allowing for increased reliability and reduced downtime.
    • Cost-efficiency: IO-Link technologies do not require complicated wiring and can significantly reduce material costs compared to traditional hardwired solutions. Additionally, maintenance is easier and more efficient with communication between devices, and there is less need for multiple maintenance employees to manage equipment.
    • Flexibility: With IO-Link technologies, the control system can control and monitor devices even when not attached to specific operator workstations. It enables one control system to manage thousands of devices without needing to rewrite programming to accommodate different machine types.
    • Real-time monitoring: IO-Link technologies provide real-time monitoring of devices, allowing control systems to monitor failures before they occur, making it easier for maintenance teams to manage the shop floor.

How are IO-Link technologies used in automated welding applications?

Automated welding applications have increased efficiencies and continuity in processes, and IO-Link technologies have accelerated these processes further. Automated welding applications have different stages, and each step requires real-time monitoring to ensure the process is efficient and effective. IO-Link technologies have been integrated into various parts of the automated welding process, some of which include:

    1. Positioning and alignment: The welding process starts with positioning and aligning materials such as beams, plates, and pipes. IO-Link sensors can detect the height and gap position of the material before the welding process begins. The sensor sends positional data to the control system as a feedback loop, which then adjusts the positioning system using actuators to ensure optimal weld quality.
    2. Welding arc monitoring: The welding arc monitoring system is another critical application for IO-Link technologies. Monitoring the arc ensures optimal weld quality and runs with reduced interruptions. IO-Link temperature sensors attached to the welding tip help control and adjust the temperature required to melt and flow the metal, ensuring that the welding arc works optimally.
    3. Power supply calibration: IO-Link technologies are essential in calibrating the power output of welding supplies, ensuring consistent quality in the welding process. Detectors attached to the power supply record the energy usage, power output and voltage levels, allowing the control system to adjust as necessary.
    4. Real-time monitoring and alerting: Real-time monitoring and alerting capabilities provided by IO-Link technologies help to reduce downtime where machine health is at risk. The sensors monitor the welding process, determining if there are any deviations from the set parameters. They then communicate the process condition to the control system, dispatching alerts to maintenance teams if an issue arises.

Using IO-Link technologies in automated welding applications has revolutionized the welding industry, providing real-time communication, enhanced data transfer, flexibility, and real-time monitoring capabilities required for reliable processes. IO-Link technologies have been integrated at various stages of automated welding, including positioning and alignment, welding arc monitoring, power supply calibration, and real-time monitoring and alerting. There is no doubt that the future of automated welding is bright. With IO-Link technologies, the possibilities are endless, forging ahead to provide more intelligent, efficient, and reliable welding applications.

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Demystifying Machine Learning

Machine learning can help organizations improve manufacturing operations and increase efficiency, productivity, and safety by analyzing data from connected machines and sensors, machine. For example, its algorithms can predict when equipment will likely fail, so manufacturers can schedule maintenance before problems occur, thereby reducing downtime and repair costs.

How machine learning works

Machine learning teaches computers to learn from data – to do things without being specifically told how to do them. It is a type of artificial intelligence that enables computers to automatically learn or improve their performances by learning from their experiences.

machine learning stepsImagine you have a bunch of toy cars and want to teach a computer to sort them into two groups: red and blue cars. You could show the computer many pictures of red and blue cars and say, “this is a red car” or “this is a blue car” for each one.

After seeing enough examples, the computer can start to guess which group a car belongs in, even if it’s a car that it hasn’t seen before. The machine is “learning” from the examples you show to make better and better guesses over time. That’s machine learning!

Steps to translate it to industrial use case

As in the toy car example, we must have pictures of each specimen and describe them to the computer. The image, in this case, is made up of data points and the description is a label. The sensors collecting data can be fed to the machine learning algorithm in different stages of the machine operation – like when it is running optimally, needs inspection, or needs maintenance, etc.

Data taken from vibration, temperature or pressure measures, etc., can be read from different sensors, depending on the type of machine or process to monitor.

In essence, the algorithm finds a pattern for each stage of the machine’s operation. It can notify the operator about what must be done given enough data points when it starts to veer toward a different stage.

What infrastructure is needed? Can my PLC do it?

The infrastructure needed can vary depending on the algorithm’s complexity and the data volume. Small and simple tasks like anomaly detection can be used on edge devices but not on traditional automation controllers like PLCs. Complex algorithms and significant volumes of data require more extensive infrastructure to do it in a reasonable time. The factor is the processing power, and as close to real-time we can detect the machine’s state, the better the usability.

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Using Guided Changeover to Reduce Maintenance Costs, Downtime

A guided changeover system can drastically reduce the errors involved with machine operation, especially when added to machines using fully automated changeovers. Processing multiple parts and recipes during a production routine requires a range of machines, and tolerances are important to quantify. Only relying on the human element is detrimental to profits, machine maintenance, and production volumes. Implementing operator assistance to guide visual guidance will reveal inefficiencies and allow for vast improvements.

Removing human error

Unverified manual adjustments may cause machine fatigue or failure. In a traditional manual changeover system, the frequency of machine maintenance is greater if proper tolerances are not observed at each changeover. Using IO-Link can remove the variable of human error with step-by-step instructions paired with precise sensors in closed-loop feedback. The machine can start up and run only when all parts are in the correct position.

Preventative maintenance and condition monitoring

Preventative maintenance is achievable with the assistance of sensors, technology, and systems. Using condition monitoring for motors, pumps and critical components can help prevent the need for maintenance and notably improve the effectiveness of maintenance with custom alerts and notifications with a highly useful database and graphing function.

A repeatable maintenance routine based on condition monitoring data and using a system to guide machine changeover will prolong machine life and potentially eliminate downtime altogether.

For more, read this real-world application story, including an automated format change to eliminate human error, reduce waste and decrease downtime.

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Understanding Image Processing Standards and Their Benefits

In the industrial image processing world, there are standards – GenICam, GigE Vision, and USB3 Vision – that are similar to the USB and Ethernet standards used in consumer products. What do these image processing standards mean, and what are their benefits?

The GenICam standard, which is maintained by the European Machine Vision Association (EMVA), serves as a base for all the image processing standards. This standard abstracts the user access to the features of a camera and defines the Standard Feature Naming Convention (SFNC) that all manufacturers use so that common feature names are used to describe the same functions.

Additionally, manufacturers can add specific “Quality of Implementation” features outside of the SFNC definitions to differentiate their products from ones made by other manufacturers. For example, a camera can offer specific features like frame average, flat field correction, logic gates, etc. GenICam/GigE Vision-based driver and software solutions from other manufacturers can also use these features without any problem.

“On-the-wire” standards

USB3 Vision and GigE Vision are “on-the-wire” interfaces between the driver and the camera. These standards are maintained by the Automated Imaging Association (AIA). You are probably familiar with “on-the-wire” standards and their advantages if you have used plug-and-play devices like USB memory sticks, USB mice, or USB hard disks. They work together without any problem, even if they are made by different manufacturers. It’s the same thing with GenICam/GigE Vision/USB3 Vision-based driver/software solutions. The standards define a transport layer, which controls the detection of a device, configuration (register access), data streaming (device detection), and event handling, and connects the interface to GenICam (Figure 1).

USB3 Vision builds on the GigE Vision standard by including accessories like cables. The mechanics are part of the standard and defines lockable cable interfaces, as one example. This creates a more robust interface for manufacturing environments.

Are standards a must-have?

Technically, standards aren’t necessary. But they make it possible to use products from multiple manufacturers and make devices more useful in the long term. For a historical comparison, look at USB 2.0 cameras and GigE Vision. USB 2.0 industrial cameras were introduced in 2004 and only worked with proprietary drivers (Figure 2) between the client and Vision Library/SDK and between the driver and camera. Two years later, Gigabit Ethernet cameras were introduced with the GigE Vision image processing standard, which didn’t require proprietary drivers to operate.

In the case of a system crash, users of the USB 2.0 cameras wouldn’t know whether the proprietary driver or the software library was to blame, which made them difficult to support. During the decision phase of selecting sensors and support, the customer had to keep the product portfolio in mind to meet their specifications. Afterward, the application was implemented and only worked with the proprietary interfaces of the manufacturer. In case of future projects or adaptions –for example, if a new sensor was required –it would have been necessary for the manufacturer to offer this sensor. Otherwise, it was necessary to change the manufacturer, which meant that a new implementation of the software was necessary as well. In contrast, flexibility is a big advantage with Gigabit Ethernet cameras and GigE Vision: GigE Vision-compliant cameras can be used interchangeably without regard to the manufacturer.

Despite this obvious benefit, USB cameras are more prevalent in certain image processing fields like medicine, given that the applications define the camera’s sensor resolution, image format and image frequency (bandwidth), and the environment for the purpose of cable length, frame grabber, or digital camera solution. With such tightly-defined requirements, USB cameras solve the challenges of these applications.

It’s hard to believe, but a few years ago, there weren’t any standards in the image processing market. Each manufacturer had its own solution. These times are gone – the whole market has pulled together, to the benefit of customers. Because of the standards, the interaction between hardware, driver, and software delivers the experience of a uniform piece. The quality of the market is improved. For the customer, it is easier to make product decisions since they are not locked into one company’s portfolio. With standards-compliant products, the customer can always choose the best components, independent of the company. With GenICam as a base, the image processing market offers the best interface for every application, either with GigE Vision or USB3 Vision.

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IO-Link Changeover: ID Without RFID – Hub ID

When looking at flexible manufacturing, what first comes to mind are the challenges of handling product changeovers. It is more and more common for manufacturers to produce multiple products on the same production line, as well as to perform multiple operations in the same space.

Accomplishing this and making these machines more flexible requires changing machine parts to allow for different stages in the production cycle. These interchangeable parts are all throughout a plant: die changes, tooling changes, fixture changes, end-of-arm tooling, and more.

When swapping out these interchangeable parts it is crucial you can identify what tooling is in place and ensure that it is correct.

ID without RFID

When it comes to identifying assets in manufacturing today, typically the first option companies consider is Radio-Frequency Identification (RFID). Understandably so, as this is a great solution, especially when tooling does not need an electrical connection. It also allows additional information beyond just identification to be read and written on the tag on the asset.

It is more and more common in changeover applications for tooling, fixtures, dies, or end-of-arm tooling to require some sort of electrical connection for power, communication, I/O, etc. If this is the case, using RFID may be redundant, depending on the overall application. Let’s consider identifying these changeable parts without incurring additional costs such as RFID or barcode readers.

Hub ID with IO-Link

In changeover applications that use IO-Link, the most common devices used on the physical tooling are IO-Link hubs. IO-Link system architectures are very customizable, allowing great flexibility to different varieties of tooling when changeover is needed. Using a single IO-Link port on an IO-Link master block, a standard prox cable, and hub(s), there is the capability of up to: 

    • 30 Digital Inputs/Outputs or
    • 14 Digital Inputs/Outputs and Valve Manifold Control or
    • 8 Digital Inputs/Outputs and 4 Analog Voltage/Current Signals or
    • 8 Analog Input Signals (Voltage/Current, Pt Sensor, and Thermocouple)

When using a setup like this, an IO-Link 1.1 hub (or any IO-Link 1.1 device) can store unique identification data. This is done via the Serial Number Parameter and/or Application Specific Tag Parameter. They act as a 16- or 32-byte memory location for customizable alphanumeric information. This allows for tooling to have any name stored within that memory location. For example, Fixture 44, Die 12, Tool 78, EOAT 123, etc. Once there is a connection, the controller can request the identification data from the tool to ensure it is using the correct tool for the upcoming process.

By using IO-Link, there are a plethora of options for changeover tooling design, regardless of various I/O requirements. Also, you can identify your tooling without adding RFID or any other redundant hardware. Even so, in the growing world of Industry 4.0 and the Industrial Internet of Things, is this enough information to be getting from your tooling?

In addition to the diagnostics and parameter setting benefits of IO-Link, there are now hub options with condition monitoring capabilities. These allow for even more information from your tooling and fixtures like:

    • Vibration detection
    • Internal temperature monitoring
    • Voltage and current monitoring
    • Operating hours counter

Flexible manufacturing is no doubt a challenge and there are many more things to consider for die, tooling and fixture changes, and end-of-arm tooling outside of just ID. Thankfully, there are many solutions within the IO-Link toolbox.

For your next changeover, I recommend checking out Non-Contact Inductive Couplers Provide Wiring Advantages, Added Flexibility and Cost Savings Over Industrial Multi-Pin Connectors for a great solution for non-contact connectivity that can work directly with Hub ID.

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Reducing Assembly Line Mistakes With the Error Proofing Platform Station

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

How it works

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

EEP station design

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

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

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

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IO-Link Safety: What It Is and Isn’t

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

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

Safety Network Blocks

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

Safety Network Blocks with IO-Link

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

Safety over IO-Link Blocks

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

IO-Link Safety

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

Benefits of IO-Link Safety

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

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

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Choosing Sensors Suitable for Automation Welding Environments

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

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

Some solutions include using:

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

Problem, solution

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

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

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

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

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

Following these guidelines will help significantly.

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Capacitive, the Other Proximity Sensor

What is the first thing that comes to mind if someone says “proximity sensor?” My guess is the inductive sensor, and justly so because it is the most used sensor in automation today. There are other technologies that use the term proximity in describing the sensing mode, including diffuse or proximity photoelectric sensors that use the reflectivity of the object to change states and proximity mode of ultrasonic sensors that use high-frequency sound waves to detect objects. All these sensors detect objects that are in close proximity to the sensor without making physical contact. One of the most overlooked or forgotten proximity sensors on the market today is the capacitive sensor.

Capacitive sensors are suitable for solving numerous applications. These sensors can be used to detect objects, such as glass, wood, paper, plastic, or ceramic, regardless of material color, texture, or finish. The list goes on and on. Since capacitive sensors can detect virtually anything, they can detect levels of liquids including water, oil, glue, and so forth, and they can detect levels of solids like plastic granules, soap powder, sand, and just about anything else. Levels can be detected either directly, when the sensor touches the medium, or indirectly when it senses the medium through a non-metallic container wall.

Capacitive sensors overview

Like any other sensor, there are certain considerations to account for when applying capacitive, multipurpose sensors, including:

1 – Target

    • Capacitive sensors can detect virtually any material.
    • The target material’s dielectric constant determines the reduction factor of the sensor. Metal / Water > Wood > Plastic > Paper.
    • The target size must be equal to or larger than the sensor face.

2 – Sensing distance

    • The rated sensing distance, or what you see in a catalog, is based on a mild steel target that is the same size as the sensor face.
    • The effective sensing distance considers mounting, supply voltage, and temperature. It is adjusted by the integral potentiometer or other means.
    • Additional influences that affect the sensing distance are the sensor housing shape, sensor face size, and the mounting style of the sensor (flush, non-flush).

3 – Environment

    • Temperatures from 160 to 180°F require special considerations. The high-temperature version sensors should be used in applications above this value.
    • Wet or very humid applications can cause false positives if the dielectric strength of the target is low.
    • In most instances, dust or material buildup can be tuned out if the target dielectric is higher than the dust contamination.

4 – Mounting

    • Installing capacitive sensors is very similar to installing inductive sensors. Flush sensors can be installed flush to the surrounding material. The distance between the sensors is two times the diameter of the sensing distance.
    • Non-flush sensors must have a free area around the sensor at least one diameter of the sensor or the sensing distance.

5 – Connector

    • Quick disconnect – M8 or M12.
    • Potted cable.

6 – Sensor

    • The sensor sensing area or face must be smaller or equal to the target material.
    • Maximum sensing distance is measured on metal – reduction factor will influence all sensing distances.
    • Use flush versions to reduce the effects of the surrounding material. Some plastic sensors will have a reduced sensing range when embedded in metal. Use a flush stainless-steel body to get the full sensing range.

These are just a few things to keep in mind when applying capacitive sensors. There is not “a” capacitive sensor application – but there are many which can be solved cost-effectively and reliably with these sensors.