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.

With Ethernet as the key technology for Industry 4.0 and digitalization, more and more devices will have Ethernet capabilities. Typical industrial Ethernet nodes on a plant floor could include PLC controllers, robots, I/O devices for sensors, actuators, flowmeters, transducers and manifolds. While, it’s great getting all the data and diagnostics of the entire manufacturing process, having every device connected via Ethernet has some downfalls. It can lead to larger Ethernet networks, which can mean more costs in hardware such as routers, switches and Ethernet cables, and some Ethernet software license costs are based on the number of Ethernet nodes being used in the network.

Also, as more Ethernet devices are added to a network, the Ethernet network itself can get more complex. Each individual Ethernet device requires an IP address. If an Ethernet node stopped working and needed to be replaced, an operator would need to know the previous IP address of the device and have quick access to the manual with instructions on how to assign the previous IP address to the new device. Someone must also manage the IP addresses on the network. There will need to be a list of the IP addresses on the network as well as the available ones, so when a new Ethernet device is added to the network, a duplicate address is not use

One way to reduce the number of Ethernet nodes while still getting device data and diagnostics is by using IO-Link for field device communications. IO-Link is an open point-to-point communication standard for sensors and actuators published by IEC (International Electrotechnical Commission) as IEC 61131-9. Since it’s fieldbus and manufacturer independent, there is a long list of manufacturer devices that come with IO-Link. Each IO-Link device can then be brought back to a single Ethernet node, through an IO-Link to Ethernet gateway. Since it’s open technology, there are also multiple manufacturers that make different IO-Link to industrial Ethernet gateways.

On the IO-Link to Ethernet gateway, each channel has an IO-Link master chipset. It is designed to automatically communicate and provide data as soon as an IO-Link device is connected to a port. So, there is no addressing or additional setup required. IO-Link is point to point, so it’s always a single IO-Link device connected to a single port on the gateway using a standard sensor cable. Depending on the number of IO-Link devices to be connected to a single Ethernet node, IO-Link gateways can come in 4, 8 or 16 device channels. This graphic (image 1) shows six IO-Link devices connected to a single 8-channel Ethernet gateway. This gateway then communicates back to the Ethernet PLC controller as a single IP address with a standard Ethernet cable. Without using IO-Link, this might require all six devices to be industrial Ethernet devices. Each device would have its own IP address to set up, along with six Ethernet cables going back to a 6-port managed switch before going to the PLC controller.

 

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Image 1: Six IO-Link devices connected to a single 8-channel Ethernet gateway.

IO-Link Devices Connected:

  1. Device I/O Hub used to connect to 16 standard discrete sensors/photoeyes.
  2. Valve Manifold used to control up to 24 coils.
  3. Visual Indicator Light
  4. RFID Processor System
  5. Pressure Sensor
  6. IO-Link to Standard Analog (0-10V or 4-20ma) Converter

Improve Error Proofing with IO-Link and IoT-Enabled Sensors

Though error-proofing sensors and poka yoke have been around for decades, continuing advancements related to the Industrial Internet of Things (IIoT) are making both more accessible and easier to maintain.

Balluff - The IO-Link Revolution!

Designed to eliminate product defects by preventing human errors or correcting them in real time, poka yoke has been a key to a lean manufacturing process since it was first applied to industrial applications in 1960. Today, error proofing relies far less on manual mechanisms and more on IoT-enabled error proofing sensors that connect devices and systems across the shop floor.

IoT is enabling immediate control of error-proofing devices such as sensors. This immediacy guards against error-proofing devices being bypassed, which has been a real problem for many years. Now, if a sensor needs adjustment it can be done remotely. A good example of this is with color sensors. When receiving sub-components from suppliers, colors can shift slightly. If the quality group identifies the color lot as acceptable but the sensor does not, often the color sensor is bypassed to keep production moving until someone can address it, creating a vulnerable situation. By using IoT-enabled sensors, the color sensor can be adjusted remotely at any time or from any location.

The detection of errors has been greatly improved by integrating sensors directly into the processes. This is a major trend in flexible manufacturing where poka yoke devices have to be adjusted on-the-fly based on the specific product version being manufactured. This means that buttons or potentiometers on discrete sensors are not adequate. Sensors must provide true data to the control system or offer a means to program them remotely. They must also connect into the traceability system, so they know the exact product version is being made. Connections like this are rapidly migrating to IO-Link. This technology is driving flexible manufacturing at an accelerated rate.

IO-Link enables sensors to process and produce enriched data sets. This data can then be used to optimize efficiencies in an automated process, increase productivity and minimize errors.

Additionally, the easily expandable architecture built around IO-Link allows for easy integrations of poka yoke and industrial identification devices. By keeping a few IO-Link ports open, future expansion is easy and cost effective. For poka yoke, it is important that the system can be easily expanded and that updates are cost-effective.

Using Data to Drive Plant Productivity

What is keeping us from boosting productivity in our plants to the next level? During a recent presentation on Industry 4.0 and IIoT, I was asked this question.

The single biggest thing, in my opinion, that is keeping us from boosting productivity to the next level is a lack of DATA. Specifically, data about the systems and the processes.

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Since the beginning of time, we have been hungry for efficiency. While early man invented more efficient methods to hunt and survive, today we are looking for ways to produce more efficiently in our plants with minimum or zero waste. After exhausting all the avenues for lean operations on plant procedures and our day-to-day activities, we are now looking at how we can recover from unanticipated downtime quickly. I am sure in future we will be seeking information on how can we prevent the downtime altogether.

There are plentiful of reasons for downtime. Just a few examples:

  1. Unavailability of labor – something we might be experiencing these days, when the COVID-19 pandemic has reduced some labor forces
  2. Unavailability of raw materials
  3. Unavailability of replacement components
  4. Unavailability of assets
  5. Failures in machines/components

In this list, the first two reasons, are beyond the scope of this blog’s intentions and frankly somewhat out of controls from the production standpoint.

The next two reasons, however, are process related and the last one is purely based on the choices we made. These three reasons, to a certain extent, can be reduced or eliminated.

If the downtime is process related, we can learn from them and improve our processes with so called continuous improvement initiatives. We can only do these continuous improvements based on observable factors (a.k.a. data) and we cannot improve our processes based on speculations. Well, I shouldn’t say “cannot”, but it will be more like a fluke or luck. It is apt to say “ what can’t be measured, can’t be improved!”

A good example for elaborating my point is change-over in the plant to produce a different product. Unless there is a good process in place for ensuring all the change-over points are properly addressed and all the change parts are correctly installed and replaced, the changeover time could and will likely lead to tremendous amounts of lost productivity. Secondly, if these processes are done manually and not automated, that is also a loss of productivity or, as I like to say, an area for continuous improvement to boost productivity based on observable facts. Sometimes, we take these manual change-overs as a fact of life and incorporate that time required as a part of “planned” downtime.  Of course, if you do change-overs once a year – it may be cost effective to keep the process manual even in today’s situation. But, if your plant has multiple short batch productions per day or per week, then automating the changeovers could significant boost productivity. The cost benefit analysis should help prove if it is continuous improvement or not.

Assets are an important part of the equation for smooth operations. An example would be molds in the stamping plant or cutting-deburring tools in metal working plants. If plants have no visibility or traceability of these important assets for location, shape or form, it could lead to considerable downtime. The calibration data of these tools or number of parts produced with the tool are also important pieces of data that needs to be maintained for efficient operations. Again, this is data about the system and the integration of these traceability initiatives in the existing infrastructure.

Failures in machines or components could cause severe downtime and are often considered as unavoidable. We tackle these failures in a two-step approach. First, we hunt for the problem when it is not obvious, and two, we find the replacement part in the store room to change it out quickly. And, as process improvement, we schedule preventative maintenance to inspect, lubricate and replace parts in our regular planned downtime.

The preventative maintenance is typically scheduled based on theoretical rate of failure. This is a good measure, especially for mechanical components, but, predictive or condition-based maintenance usually yields higher returns on productivity and helps keep plants running smooth. Again, predictive maintenance relies on data about the condition of the system or components. So, where is this data and how do we get to it?

Standardization of interfaces is another important component for boosting productivity. In my next blog, I will share how IO-Link as a technology can help address all of these challenges and boost productivity to the next level.

Are machine diagnostics overburdening our PLCs?

In today’s world, we depend on the PLC to be our eyes and ears on the health of our automation machines. We depend on them to know when there has been an equipment failure or when preventative maintenance is needed. To gain this level of diagnostics, the PLC must do more work, i.e. more rungs of code are needed to monitor the diagnostics supplied to the sensors, actuators, motors, drives, etc.

In terms of handling diagnostics on a machine, I see two philosophies. First, put the bare bones minimum in the PLC. With less PLC code, the scan times are faster, and the PLC runs more efficiently. But this version comes with the high probability for longer downtime when something goes wrong due to the lack of granular diagnostics. The second option is to add lots of diagnostic features, which means a lot of code, which can lessen downtime, but may throttle throughput, since the scan time of the PLC increases.

So how can you gain a higher level of diagnostics on the machine and lessen the burden on the PLC?

While we usually can’t have our cake and eat it too, with Industry 4.0 and IIoT concepts, you can have the best of both of these scenarios. There are many viewpoints of what these terms or ideas mean, but let’s just look at what these two ideas have made available to the market to lessen the burden on our PLCs.

Data Generating Devices Using IO-Link

The technology of IO-Link has created an explosion of data generating devices. The level of diversity of devices, from I/O, analog, temperature, pressure, flow, etc., provides more visibility to a machine than anything we have seen so far. Utilizing these devices on a machine can greatly increase visibility of the processes. Many IO-Link masters communicate over an Ethernet-based protocol, so the availability of the IO-Link device data via JSON, OPC UA, MQTT, UDP, TCP/IP, etc., provides the diagnostics on the Ethernet “wire” where more than just the PLC can access it.

Linux-Based Controllers

After using IO-Link to get the diagnostics on the Ethernet “wire,” we need to use some level of controller to collect it and analyze it. It isn’t unusual to hear that a Raspberry Pi is being used in industrial automation, but Linux-based “sandbox” controllers (with higher temperature, vibration, etc., standards than a Pi) are available today. These controllers can be loaded with Codesys, Python, Node-Red, etc., to provide a programming platform to utilize the diagnostics.

Visualization of Data

With IO-Link devices providing higher level diagnostic data and the Linux-based controllers collecting and analyzing the diagnostic data, how do you visualize it?  We usually see expensive HMIs on the plant floors to display the diagnostic health of a machine, but by utilizing the Linux-based controllers, we now can show the diagnostic data through a simple display. Most often the price is just the display, because some programming platforms have some level of visualization. For example, Node-Red has a dashboard view, which can be easily displayed on a simple monitor. If data is collected in a server, other visualization software, such as Grafana, can be used.

To conclude, let’s not overburden the PLC with diagnostic; lets utilize IIoT and Industry 4.0 philosophy to gain visibility of our industrial automation machines. IO-Link devices can provide the data, Linux-based controllers can collect and analyze the data, and simple displays can be used to visualize the data. By using this concept, we can greatly increase scan times in the PLC, while gaining a higher level of visibility to our machine’s process to gain more uptime.

What data can IO-Link provide?

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

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

Process Data

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

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

Process Data

Parameter Data

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

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

Parameter Data

Diagnostics or Event Data

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

Diagnostic and Event Data

Conclusion

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

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

automation pyramid

 

Increase Efficiencies and Add Value with Data

Industry 4.0 and the Industrial Internet of Things (IIoT) are very popular terms these days.  But they are more than just buzzwords; incorporating these concepts into your facility adds instant value.

Industry 4.0 and IIoT provide you with much needed data. Having information easily available regarding how well your machines are performing allows for process improvements and increased efficiencies. The need for increased efficiency is driving the industry to improve manufacturing processes, reduce downtime, increase productivity and eliminate waste.  Increased efficiency is necessary to stay competitive in today’s manufacturing market.  With technology continuing to advance and be more economical, it is more feasible than ever to implement increased efficiencies in the industry.

Industry 4.0 and IIoT are the technology concepts of smart manufacturing or the smart factory.  IIoT is at the core of this as it provides access to data directly from devices on the factory floor. By implementing a controls architecture with IO-Link and predictive maintenance practices through condition monitoring parameters from the devices on the machine, Industry 4.0 and IIoT is occurring.

Condition monitoring is the process of monitoring the condition of a machine through parameters.  In other words, monitoring a parameter that gives the condition of the machine or a device on the machine such as vibration, temperature, pressure, rate, humidity etc. in order to identify a significant change in condition, which indicates the possible development of a fault.  Condition monitoring is the primary aspect of predictive maintenance.

IO-Link is a point-to-point communication for devices which allows for diagnostics information without interfering with the process data. There are hundreds of IO-Link smart devices, which provide condition monitoring parameters for the health of the device and the health of the machine.  By utilizing capabilities of IO-Link for diagnostics the ability to gather large amounts of data directly from devices on the factory floor gives you more control over the machines efficiency.  Smart factory concepts are available today with IO-Link as the backbone of the smart machine and smart factory.

Dive into big data with confidence knowing you can gather the information you need with the smart factory concepts available today.

Sensor and Device Connectivity Solutions For Collaborative Robots

Sensors and peripheral devices are a critical part of any robot system, including collaborative applications. A wide variety of sensors and devices are used on and around robots along with actuation and signaling devices. Integrating these and connecting them to the robot control system and network can present challenges due to multiple/long cables, slip rings, many terminations, high costs to connect, inflexible configurations and difficult troubleshooting. But device level protocols, such as IO-Link, provide simpler, cost-effective and “open” ways to connect these sensors to the control system.

Just as the human body requires eyes, ears, skin, nose and tongue to sense the environment around it so that action can be taken, a collaborative robot needs sensors to complete its programmed tasks. We’ve discussed the four modes of collaborative operation in previous blogs, detailing how each mode has special safety/sensing needs, but they have common needs to detect work material, fixtures, gripper position, force, quality and other aspects of the manufacturing process. This is where sensors come in.

Typical collaborative robot sensors include inductive, photoelectric, capacitive, vision, magnetic, safety and other types of sensors. These sensors help the robot detect the position, orientation, type of objects, and it’s own position, and move accurately and safely within its surroundings. Other devices around a robot include valves, RFID readers/writers, indicator lights, actuators, power supplies and more.

The table, below, considers the four collaborative modes and the use of different types of sensors in these modes:

Table 1.JPG

But how can users easily and cost-effectively connect this many sensors and devices to the robot control system? One solution is IO-Link. In the past, robot users would run cables from each sensor to the control system, resulting in long cable runs, wiring difficulties (cutting, stripping, terminating, labeling) and challenges with troubleshooting. IO-Link solves these issues through simple point-to-point wiring using off-the-shelf cables.

Table 2.png

Collaborative (and traditional) robot users face many challenges when connecting sensors and peripheral devices to their control systems. IO-Link addresses many of these issues and can offer significant benefits:

  • Reduced wiring through a single field network connection to hubs
  • Simple connectivity using off-the-shelf cables with plug connectors
  • Compatible will all major industrial Ethernet-based protocols
  • Easy tool change with Inductive Couplers
  • Advanced data/diagnostics
  • Parametarization of field devices
  • Faster/simpler troubleshooting
  • Support for implementation of IIoT/Industry 4.0 solutions

IO-Link: an excellent solution for simple, easy, fast and cost-effective device connection to collaborative robots.

IO-Link reduces waste due to sensor failures

In the last two blogs we discussed about Lean operations and reducing waste as well as Selecting right sensors for the job and the environment that the sensor will be placed. Anytime a sensor fails and needs a replacement, it is a major cause of downtime or waste (in Lean philosophy). One of the key benefits of IO-Link technology is drastically reducing this unplanned downtime and replacing sensors with ease, especially when it comes to measurement sensors or complex smart sensors such as flow sensors, continuous position monitoring sensors, pressure sensors, laser sensors and so on.

When we think about analog measurement sensor replacement, there are multiple steps involved. First, finding the right sensor. Second, calibrating the sensor for the application and configuring its setpoints. And third, hope that the sensor is functioning correctly.

Most often, the calibration and setpoint configuration is a manual process and if the 5S processes are implemented properly, there is a good chance that the procedures are written down and accessible somewhere. The process itself may take some time to be carried out, which would hold up the production line causing undesired downtime. Often these mission critical sensors are in areas of the machine that are difficult to access, making replacing then, let alone configuring, a challenge.

IO-Link offers an inherent feature to solve this problem and eliminates the uncertainty that the sensor is functioning correctly. The very first benefit that comes with sensors enabled with IO-Link is that measurement or readings are in engineering units straight from the sensor including bar, psi, microns, mm, liters/min, and gallons/min. This eliminated the need for measurements to be scaled and adjusted in the programming to engineering units.

Secondly, IO-Link masters offer the ability to automatically reconfigure the sensors. Many manufacturers call this out as automatic device replacement (ADR) or parameter server functionality of the master. In a nutshell, when enabled on a specific port of the multi-port IO-Link master, the master port reads current configuration from the sensor and locks them in. From that time forward, any changes made directly on the sensor are automatically overwritten by these locked parameters. The locked parameters can be accessed and changed only through authorized users. When the time comes to replace the sensor, there is only one step that needs to happen: Find the replacement sensor of the same model and plug it in. That’s it!

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When the new sensor is plugged-in, the IO-Link master automatically detects that the replacement sensor does not have the correct parameters and automatically updates them on the sensor. Since the readings are directly in the units desired, there is no magic of scaling to fiddle with.

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It is also important to note, that in addition to the ADR feature, there may be parameters or settings on the sensors that alert you to possible near-future failure of the sensor. This lets you avoid unplanned downtime due to sensor failure. A good example would be a pressure sensor that sends an alert (event) message indicating that the ambient temperature is too high or a photo-eye alerting the re-emitted light value is down close to threshold – implying that either the lens is cloudy, or alignment is off.

To learn more about IO-Link check out our other blogs.

You have options when it comes to connecting your sensors

When it comes to connecting I/O in factory automation settings, there are many options one can choose to build an efficient and cost-effective system. This is one area where you can reduce costs while also boosting productivity.

Single Ended Cables and Hardwired I/O

It is common in the industry for single ended cables to be run from sensors to a controller input card in a centralized control cabinet. And while this method works, it can be costly for a number of reasons, including:

  • Flying leads on single ended cables are time consuming to prepare and wire
  • Wiring mistakes are often made leading to more time troubleshooting
  • I/O Cards for PLCs are expensive
  • Long cable runs to a centralized location add up quickly especially when dealing with analog devices which require expensive shielded cables
  • Lack of scalability and diagnostics

Double Ended Cables and Networked I/O

Using double ended cables along with network I/O blocks allows for a cost-effective solution to distribute I/O and increase up time. There are numerous benefits that come along with this sort of architecture. Some of these benefits are:

  • Reduced cabling — since I/O is distributed, only network cables need to be run back to the control cabinet reducing cost and cabinet size, and sensor cables are shortened since I/O blocks are machine mounted
  • Quicker build time since standard wiring is less labor intensive
  • Diagnostics allows for quicker trouble shooting, leading to lower maintenance costs and reduced downtime

IO-Link

Using IO-Link delivers all of the strengths of networked I/O as well as additional benefits:

  • I/O Hubs allow for scalability
  • Smart devices can be incorporated into your system
  • Parameterization capability
  • Increased diagnostics from intelligent devices
  • Reduced costs and downtime
  • Increased productivity

Inductive Coupling for non-contact connection

Many people are using inductive coupling technology to provide a non-contact connection for their devices. This method allows you to pass both power and signal across an air gap making it ideal for replacing slip rings or multi-pin connectors in many applications. This provides some great options for industry to gain benefits in these areas such as:

  • Reduced wear since there is no physical connection
  • Faster change over
  • Reduced downtime due to the elimination of damaged connector pins

For more information on connectivity and I/O architecture solutions please visit www.balluff.com.

IO-Link Makes Improving OEE in Format Change Easier than Ever

One of the primary applications in Packaging, Food & Beverage that is a huge area for improving overall equipment efficiency (OEE) is format change.  Buyers respond well to specialized or individualized packaging, meaning manufacturers need to find ways to implement those format changes and machine builders must make those flexible machines available.

IO-Link Makes Improving OEE in Format Change Easier than Ever_2

Today, thanks to IO-Link devices, including master blocks, hubs and linear position sensors, improving OEE on format change is more possible today than ever before. IO-Link offers capabilities that make it ideal for format change. It communicates:

  • Process data (control, cyclical communication of process status)
  • Parameter data (configuration, messaging data with configuration information)
  • Event data (diagnostics, communication from device to master including diagnostics/errors)

What is format change and how does it impact OEE?

Format change is the physical adjustments necessary to make to a machine when the product is altered in some way.  It could be a change in carton size, package size, package design, case size or a number of other modifications to the product or packaging.  The time to adjust the machine itself or the sensors on the machine can take anywhere from 30 minutes to an entire eight- hour shift.

Types of format changes to consider when seeking to improve your OEE:

Guided format change is when the operator is assisted or guided in making the change.  For example, having to move or slide a guide rail into a new position.  IO-Link linear position sensors can help guide the operator, so the position is exact every time. This reduces time by eliminating the need to go back and look at an HMI or cheat sheet to determine if everything is in the right position.

Change parts is when a part needs to be swapped out on the machine for the next production run.  An example of this is when the bag size on a bagger or vertical form fill and seal (VFFS) machine changes and the forming tube needs to be changed.  Having an RFID tag on the forming tube and a RFID reader on the machine allows for easy verification that the correct forming tube was put on the machine and only takes seconds.

Color Change is when the color of a pouch, package or container changes for the next production run like when a yogurt pouch changes color or design while the size and shape remain the same as previous production runs. Smart color photo electric sensors can change the parameters on the photo eye to detect the correct color of the new pouch occurs instantly upon changing the recipe on the machine.

Developing semi-automated or fully automated solutions can improve OEE in regard to format change by helping reduce the time needed to make the change and providing consistent and accurate positioning with the ability to automatically change parameters in the sensor.

Being smart, easy and universal, IO-Link helps simplify format change and provides the ability to change sensor parameters quickly and easily.

IO-Link Makes Improving OEE in Format Change Easier than Ever_1