Tire Manufacturing – IO-Link is on a Roll

Everyone working in the mobility industry knows that the tire manufacturing process is divided up into five areas throughout a large manufacturing plant.

    1. Mixing
    2. Tire prep
    3. Tire build
    4. Curing and molds
    5. Final inspection

Naturally,  conveyors, material handling, and AGV processes throughout the whole plant.

All of these areas have opportunities for IO-Link components, and there are already some good success stories for some of these processes using IO-Link.

A major opportunity for IO-Link can be found in the curing press area. Typically, a manufacturing plant will have about 75 – 100 dual cavity curing presses, with larger plants having  even more. On these tire curing presses are many inputs and outputs in analog signals. These signals can be comprised of pressure switches, sensors, pneumatic, hydraulic, linear positioning, sensors in safety devices, thermo-couples and RTD, flow and much more.

IO-Link provides the opportunity to have all of those inputs, outputs and analog devices connected directly to an IO-Link master block and hub topography. This makes it not only easier to integrate all of those devices but allows you to easily integrate them into your PLC controls.

Machine builders in this space who have already integrated IO-Linked have discovered how much easier it is to lay out their machine designs, commission the machines, and decrease their costs on machine build time and installations.

Tire manufacturing plants will find that the visual diagnostics on the IO-Link masters and hubs, as well as alarms and bits in their HMIs, will quickly help them troubleshoot device problems. This decreases machine downtime and delivers predictive maintenance capabilities.

Recently a global tire manufacturer getting ready to design the curing presses for a new plant examined the benefits of installing IO-Link and revealed a cost savings of more than $10,000 per press. This opened their eyes to evaluating IO-Link technology even more.

Tire Manufacturing is a perfect environment to present IO-Link products. Many tire plants are looking to upgrade old machines and add new processes, ideal conditions for IO-Link. And all industries are interested in ways to stretch their budget.

 

Error Proof Stamping Applications with Pressure Sensors

When improving product quality or production efficiency, manufacturing engineers typically turn to automation solutions to error proof and improve their application. In stamping applications, that often leads to adding sensors to help detect the presence of a material or a feature in a part being formed, for example, a hole in a part. In the stamping world, this can be referred to as “In-Die Sensing” or “Die Protection.” The term “Die Protection” is used because if the sensors do not see the material in the correct location when forming, then it could cause a die crash. The cost of a die crash can add up quickly. Not only is there lost production time, but also damage to the die that can be extremely costly to repair. Typically, several sensors are used throughout the die to look for material or features in the material at different locations, to make sure the material is present to protect the die. Manufacturing engineers tend to use photoelectric and/or inductive proximity sensors in these applications; however, pressure sensors are a cost-effective and straightforward alternative.

In today’s stamping applications, manufacturing engineers want to stamp parts faster while reducing downtime and scrap. One growing trend in press shops is the addition of nitrogen on the dies. By adding nitrogen-filled gas springs and/or nitrogen gas-filled lifters, the press can run faster and cycle parts through quicker.

Typically, the die is charged with nitrogen before the press starts running parts. Today, many stamping plants rely on an analog dial gauge (image 1) to determine if there is sufficient nitrogen pressure to operate safely. When a new die is set in the press, someone must look at the gauge and make sure it is correct before running the press. There is no type of signal or feedback from this gauge to the PLC or the press; therefore, no real error proofing method is in place to notify the operator if the pressure rating is correct or even present before starting the press. If the operator starts running the press without any nitrogen for the springs, then it will not cycle the material and can cause a crash.

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Another, likely more significant problem engineers face is a hole forming in one of the hoses while they are running. A very small hole in a hose may not be noticeable to the operator and may not even show up on the analog dial gauge. Without this feedback from the gauge, the press will continue to run and increase the likelihood that the parts will be stamped and be out of specification, causing unnecessary scrap. Scrap costs can be quite large and grow larger until the leak is discovered. Additionally, if the material cannot move through the press properly because of a lack of nitrogen pressure to the springs or lifters, it could cause material to back up and cause a crash.

By using a pressure sensor, you can set high and low pressure settings that will give an output when either of those is reached. The outputs can be discrete, analog, or IO-Link, and they can be tied to your PLC to trigger an alarm for the operator, send an alert to the HMI, or even stop the press. You can also have the PLC make sure pressure is present before starting the press to verify it was adequately charged with nitrogen during set up.

Adding an electronic pressure sensor to monitor the nitrogen pressure is a simple and cost-effective way to error proof this application and avoid costly problems.

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.

Adding a higher level of visibility to older automation machines

It’s never too late to add more visibility to an automation machine.

In the past, when it came to IO-Link opportunities, if the PLC on the machine was a SLC 500, a PLC-5, or worse yet, a controller older than I, there wasn’t much to talk about. In most of these cases, the PLC could not handle another network communication card, or the PLC memory was maxed, or it used a older network like DeviceNet, Profibus or ASi that was maxed. Or it was just so worn out that it was already being held together with hope and prayer. But, today we can utilize IIoT and Industry 4.0 concepts to add more visibility to older machines.

IIOT and Industry 4.0 have created a volume of products that can be utilized locally at a machine, rather than the typical image of Big Data. There are three main features we can utilize to add a level of visibility: Devices to generate data, low cost controllers to collect and analyze the data, and visualization of the data.

Data Generating Devices

In today’s world, we have many devices that can generate data outside of direct communication to the PLC.  For example, in an Ethernet/IP environment, we can put intelligent devices directly on the EtherNet/IP network, or we can add devices indirectly by using technologies like IO-Link, which can be more cost effective and provide the same level of data. These devices can add monitoring of temperature, flow, pressure, and positioning data that can reduce downtime and scrap. With these devices connected to an Ethernet-based protocol, data can be extracted from them without the old PLC’s involvement.  Utilizing JSON, OPC UA, MQTT, UDP and TCP/IP, the data can be made available to a secondary controller.

Linux-Based Controllers

An inexpensive Raspberry Pi could be used as the secondary controller, but Linux-based open controllers with industrial specifications for temperature, vibration, etc. are available on the market. These lower cost controllers can then be utilized to collect and analyze the data on the Ethernet protocol. With a Linux based “sandbox” system, many programming software packages could be loaded, i.e. Node-Red, Codesys, Python, etc., to create the needed logic.

Visualization of Data

Now that the data is being produced, collected and analyzed, the next step is to view the information to add the extra layer of visibility to the process of an older machine. Some of the programming software that can be loaded into the Linux-based systems, which have a form a visualization, like a dashboard (Node-Red) or an HMI feel (Codesys). This can be displayed on a low-cost monitor on the floor near the machine.

By utilizing the products used in the “big” concepts of IIOT and Industry 4.0, you can add a layer of diagnostic visualization to older machines, that allows for easier maintenance, reduced scrap, and predictive maintenance.

The Human Body as an Analogy for Automation

A machine’s automation system operates very much like the human body. Just as we humans perceive our surroundings using our sensory organs, a machine registers its surroundings using presence sensors, input devices, and measuring systems. It continually receives status information and command inputs, and its control network transports this information as input signals to the controller. The controller interprets these signals, makes a program decision, and responds by sending output signals to actuators and indicators. For example, it may send a signal to cylinder valves and motor drives to move the machine, or to stack lights to signal status and condition to the human operators.

A machine’s automation system is the technical counterpart to the actions of the human body:

  • Sight, taste, smell, touch – Vision, pressure, temperature, flow, photoelectric, inductive, capacitive, position/distance measurement sensors
  • Listening/reading – Vibration sensors, RFID tag readers
  • Nervous system – Control network, cables, connectors
  • Brain – Controller, PLC
  • Muscles – Valves, drives, motors
  • Voice – audio signaling devices, numerical output devices (RFID data to tag)
  • Body language (visual signals) – stack lights, display screens, indicator lights, panel meters

Check out the video below to dive deeper into the world of industrial automation and learn the similarities between a machine and the human body.

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Stay tuned for future posts that will cover the essentials of automation. To learn more about the Basics of Automation in the meantime, visit www.balluff.com.

Looking for some excellent online resources? Read this!

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I was trying to locate some information on capacitive sensors so naturally, I turned to the World Wide Web to see what I could find. As I was looking through the search engine results, I found a link to Sensors Magazine, and a two-part article on capacitive sensors that I highly recommend you read. Capacitive Sensor Operation Part 1: The Basics and Capacitive Sensor Operation Part 2: System Optimization do an excellent job in describing the basics through what you need to consider in applying capacitive sensors.

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Add Value with Smart Linear Position Sensors

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Way back when (in the sensor world, “way back when” = about 10 years), linear position sensors had to do only one thing: provide linear position feedback.  But these days, merely sensing linear position is not always enough.  In order to meet the needs of increasingly sophisticated applications, linear position sensors sometimes need to be able to provide advanced functionality.  Listed below are just a few of the advanced features that some of today’s linear position sensors offer.

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