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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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How IO-Link Sensors With Condition Monitoring Features Work With PLCs

As manufacturers continually look for ways to maximize productivity and eliminate waste, automation sensors are taking on a new role in the plant. Once, sensors were used only to provide detection or measurement data so the PLC could process it and run the machine. Today, sensors with IO-Link measure environmental conditions like temperature, humidity, ambient pressure, vibration, inclination, operating hours, and signal strength. By setting alarm thresholds, it’s possible to program the PLC to use the resulting condition monitoring data to keep machines running smoothly.

Real-time data for real-time response

A sensor with condition monitoring features allows a PLC to use real-time data with the same speed it uses a sensor’s primary process data. This typically requires setting an alarm threshold at the sensor and a response to those alarms at the PLC.

When a vibration threshold is set up on the sensor and vibration occurs, for example, the PLC can alert the machine operator to quickly check the area, or even stop the machine, to look for a product jam, incorrect part, or whatever may be causing the vibration. By reacting to the alarm immediately, workers can reduce product waste and scrap.

Inclination feedback can provide diagnostics in troubleshooting. Suppose a sensor gets bumped and no longer detects its target, for example. The inclination alarm set in the sensor will indicate after a certain degree of movement that the sensor will no longer detect the part. The inclination readout can also help realign the sensor to the correct position.

Detection of other environmental factors, including humidity and higher-than-normal internal temperatures, can also be set, providing feedback on issues such as the unwanted presence of water or the machine running hotter than normal. Knowing these things in real-time can stop the PLC from running, preventing the breakdown of other critical machine components, such as motors and gearboxes.

These alarm bits can come from the sensors individually or combined together inside the sensor. Simple logic, like OR and AND statements, can be set on the sensor in the case of vibration OR inclination OR temperature alarm OR humidity, output a discrete signal to pin 2 of the sensors. Then pin 2 can be fed back through the same sensor cable as a discrete alarm signal to the PLC. A single bit showing when an alarm occurs can alert the operator to look into the alarm condition before running the machine. Otherwise, a simple ladder rung can be added in the PLC to look at a single discrete alarm bit and put the machine into a safe mode if conditions require it.

In a way, the sensor monitors itself for environmental conditions and alerts the PLC when necessary. The PLC does not need to create extra logic to monitor the different variables.

Other critical data points, such as operating hours, boot cycle counters, and current and voltage consumption, can help establish a preventative and predictive maintenance schedule. These data sets are available internally on the sensors and can be read out to help develop maintenance schedules and cut down on surprise downtimes.

Beyond the immediate benefits of the data, it can be analyzed and trended over time to see the best use cases of each. Just as a PLC shouldn’t be monitoring each alarm condition individually, this data must not be gathered in the PLC, as there is typically only a limited amount of memory, and the job of the PLC is to control the machines.

This is where the IT world of high-level supervision of machines and processes comes into play. Part two of my blog will explore how to integrate this sensor data into the IT level for use alongside the PLC.

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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.

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

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

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

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

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

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

 

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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.

 

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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.

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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.

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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.

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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.

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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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