How Condition Monitoring has Evolved and Its Role in IIoT

In recent years, as IIoT and Industry 4.0 have become part of our everyday vocabulary, we’ve also started hearing more about condition monitoring, predictive maintenance (PdM) and predictive analytics. Sometimes, we use these terms interchangeably as well. Strictly speaking, condition monitoring is a root that enables both predictive maintenance and predictive analytics. In today’s blog we will brush up a little on condition monitoring and explore its lineage.

Equipment failures have been around since the beginning of time. Over the years, through observation (collecting data) and brute-force methods, we learned that from time-to-time every piece of equipment needs some TLC. Out of this understanding, maintenance departments came to existence, and there we started having experts that could tell based on touch, smell and noise what is failing or what has gone wrong.

Figure 1: Automation Pyramid

Then we started automating the maintenance function either as a preventative measure (scheduled maintenance) or through some automated pieces of equipment that would collect data and provide alerts about a failure. We proudly call these SCADA systems – Supervisory Control and Data Acquisition. Of course, these systems did not necessarily prevent failures, but help curtail them.  If we look at the automation pyramid, the smart system at the bottom is a PLC and all the sensors are what we call “dumb sensors”. So, that means, whatever information the SCADA system gets would be filtered by the PLC. PLCs were/have been/ and are always focused on the process at hand; they are not data acquisition equipment. So, the data we receive in the SCADA system is only as good as the PLC can provide. That means the information is primarily about processes. So, the only alerts maintenance receives is when the equipment fails, and the process comes to a halt.

With the maintenance experts who could sense impending failures becoming mythological heroes, and  SCADA systems that cannot really tell us the story about the health of the machines, once again, we are looking at condition monitoring with a fresh set of eyes.

Sensors are at the grass root level in the automation pyramid, and until the arrival of IO-Link technology, these sensors were solely focused on their purpose of existence; object detection, or measurement of some kind. The only information one could gather from these sensors was ON/OFF or a signal of 4-20mA, 0-10V, and so on. Now, things are different, these sensors are now becoming pretty intelligent and they, like nosy neighbors, can collect more information about their own health and the environment. These intelligent sensors can utilize IO-Link as a communication to transfer all this information via a gateway module (generally known as IO-Link master) to whomever wants to listen.

Figure 2: IO-Link enabled Balluff photo-eye

The new generation of SCADA systems can now collect information not only from PLCs about the process health, but also from individual devices. For example, a photo-eye can measure the intensity of the reflected light and provide an alert if the intensity drops beyond a certain level, indicating a symptom of pending failure. Or a power supply inside the cabinet providing an alert to the supervisory control about adverse conditions due to increase temperature or humidity in the cabinet. These types of alerts about the symptoms help maintenance prevent unplanned downtime on the plant floor and make factories run more efficiently with reduced scrap, reduced down-time and reduced headaches.

Figure 3: The Next Generation Condition Monitoring

There are many different condition monitoring architectures that can be employed, and we will cover that in my next blog.

Improve OEE, Save Costs with Condition Monitoring Data

When it comes to IIOT (Industrial Internet of Things) and the fourth industrial revolution, data has become exponentially more important to the way we automate machines and processes within a production plant. There are many different types of data, with the most common being process data. Depending on the device or sensor, process data may be as simple as the status of discrete inputs or outputs but can be as complex as the data coming from radio frequency identification (RFID) data carriers (tags). Nevertheless, process data has been there since the beginning of the third industrial revolution and the beginning of the use of programmable logic controllers for machine or process control.

With new advances in technology, sensors used for machine control are becoming smarter, smaller, more capable, and more affordable. This enables manufacturers of those devices to include additional data essential for IIOT and Industry 4.0 applications. The latest type of data manufacturers are outputting from their devices is known as condition monitoring data.

Today, smart devices can replace an entire system by having all of the hardware necessary to collect and process data, thus outputting relative information directly to the PLC or machine controller needed to monitor the condition of assets without the use of specialized hardware and software, and eliminating the need for costly service contracts and being tied to one specific vendor.

A photo-electric laser distance sensor with condition monitoring has the capability to provide more than distance measurements, including vibration detection. Vibration can be associated with loose mechanical mounting of the sensor or possible mechanical issues with the machine that the sensor is mounted. That same laser distance sensor can also provide you with inclination angle measurement to help with the installation of the sensor or help detect when there’s a problem, such as when someone or something bumps the sensor out of alignment. What about ambient data, such as humidity? This could help detect or monitor for moisture ingress. Ambient pressure? It can be used to monitor the performance of fans or the condition of the filter elements on electrical enclosures.

Having access to condition monitoring data can help OEMs improve sensing capabilities of their machines, differentiating themselves from their competition. It can also help end users by providing them with real time monitoring of their assets; improving overall equipment efficiency and better predicting  and, thereby, eliminating unscheduled and costly machine downtime. These are just a few examples of the possibilities, and as market needs change, manufacturers of these devices can adapt to the market needs with new and improved functions, all thanks to smart device architecture.

Integrating smart devices to your control architecture

The most robust, cost effective, and reliable way of collecting this data is via the IO-Link communication protocol; the first internationally accepted open, vendor neutral, industrial bi-directional communications protocol that complies with IEC61131-9 standards. From there, this information can be directly passed to your machine controller, such as PLC, via fieldbus communication protocols, such as EtherNET/Ip, ProfiNET or EtherCAT, and to your SCADA / GUI applications via OPC/UA or JSON. There are also instances where wireless communications are used for special applications where devices are placed in hard to reach places using Bluetooth or WLAN.

In the fast paced ever changing world of industrial automation, condition monitoring data collection is increasingly more important. This data can be used in predictive maintenance measures to prevent costly and unscheduled downtime by monitoring vibration, inclination, and ambient data to help you stay ahead of the game.

Be Driven by Data and Decrease Downtime

Being “driven by data” is simply the act of making decisions based on real data instead of guessing or basing them on theoretical outcomes. Why one should do that, especially in manufacturing operations, is obvious. How it is done is not always so clear.

Here is how you can use a sensor, indicator light, and RFID to provide feedback that drives overall quality and efficiency.

 

Machine Condition Monitoring

You’ve heard the saying, “if it ain’t broke, don’t fix it.” However, broken machines cause downtime. What if there was a way to know when a machine is getting ready to fail, and you could fix it before it caused downtime? You can do that now!

The two main types of data measured in manufacturing applications are temperature and vibration. A sudden or gradual increase in either of these is typically an indicator that something is going wrong. Just having access to that data won’t stop the machine from failing, though. Combined with an indicator light and RFID, the sensor can provide real-time feedback to the operator, and the event can be documented on the RFID tag. The machine can then be adjusted or repaired during a planned maintenance period.

Managing Quality – A machine on its way to failure can produce parts that don’t meet quality standards. Fixing the problem before it affects production prevents scrap and rework and ensures the customer is getting a product with the quality they expect.

Managing Efficiency– Unplanned downtime costs thousands of dollars per minute in some industries. The time and resources required to deal with a failed machine far exceed the cost of the entire system designed to produce an early warning, provide indication, and document the event.

Quality and efficiency are the difference makers in manufacturing. That is, whoever makes the highest quality products most efficiently usually has the most profitable and sustainable business. Again, why is obvious, but how is the challenge. Hopefully, you can use the above data to make higher quality products more efficiently.

 

More to come! Here are the data-driven topics I will cover in my next blogs:

  • Part inspection and data collection for work in process
  • Using data to manage molds, dies, and machine tools

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.

 

What does that “Ready for IIoT” tag really mean?

These days almost every smart industrial device that comes to the market is advertised as “ready for IIoT.” But what does it actually mean? Before we get too technical, we should look at what the objectives are for IIoT and why it is important to the industrial age of our time.

In a previous post, “The promise of the Industrial Internet of Things (IIoT)“, we highlighted features such as Virtual IP address, to help address several things that plant maintenance and management would like to achieve. This blog touches those topics in a different perspective.

The concept of the Industrial Internet of Things (IIoT), or Industry 4.0, applies to the future of industrial automation, and these concepts heavily rely on the interoperability of a wide variety of devices and systems that communicate large amounts of data. This data is important because IIoT promises superior efficiency of machines and personalized manufacturing. Personalized manufacturing – also known as micro batch production or lot size one – means connecting with the customers at an individual level rather than connecting to masses. If efficiency and customization in production are the end goals or prime objectives for IIoT, these questions must be answered: What type of data would be necessary? Where and how is that data obtainable? In other words, what are the capabilities or characteristics of the device or system that really qualify as being “ready for IIoT”? Does simply providing an Ethernet connection to the device or adding a webserver qualify the device for IIoT? The answer is NO!

In my opinion, the following 5 key characteristics/capabilities, depending of course on the end user’s objectives, would qualify for being “ready for IIoT” tag.

If an end-user of automation wants to run the plant efficiently, the device or system should be able to provide information regarding; (1) Condition Monitoring, and (2) Automatic Parameterization

  1. Condition Monitoring enables predictive maintenance and eliminates unplanned downtime. Is the PLC or automation controller the right place for determining predictive maintenance? Maybe not. The PLC should focus on making sure the system is running effectively. Adding more non-application related stuff to the PLC may disrupt what is truly important. In most cases you would need a different PC or server to do this pattern analysis throughout the plant. A system or device with the “ready for IIoT” tag should be able to collect and provide that information to a higher level controls system/server. An example would be a power supply with IO-Link. Through the IO-Link master it tells the system about the stress or ambient temperature and predicts its lifetime.
  2. Automatic configuration or parameterization of sensors and systems. This feature enables plug-n-play benefit so that replacing devices is easy and the system automatically configures the replaced device to reduce downtime.

As IT and Controls Engineering work closer together, there are other characteristics of the devices that become important.

  1. Configurability of sensors and production line beyond controller of the system: Automation controllers in use today have physical limits of memory and logic. Today manufacturers are running multiple batches of different products on the same line which means more change over and more downtime. If the devices could allow for quick line change configurations such as set point changes for your sensors, different pressures on fluids, different color detections for the parts or even the ability to provide you with detection of the physical format change, that would significantly reduce your changeover times. In a PLC or controller, you can only build logic for factors known today (for ex. the number of configurations), but in the near future there will be additional product configurations. To be truly ready for the IIoT, you need devices that can be configured (with proper authorizations) in multiple ways. A webserver might be one of the ways – but that also has its limitations. Simple Network Management Protocol (SNMP) is widely used with several of the network management software tools in the IT world. OPC UA is another open communication protocol in industrial space. JSON is a protocol for cloud interface among many others. A device that can offer connectivity, via SNMP, OPC UA, JSON or other such open formats, to connect to other network software tools to gather information or configuration would solve several of these challenges without burdening the existing PLC or controller logic. In other words, these types of interfaces can connect your machine directly to an MRP or similar enterprise-level system which would make production floors much more efficient for quick changeovers.
  2. Capability for asset tracking, and quick troubleshooting: These features become important when there are hundreds of parameters changing and configurations evolving as your system becomes smarter and more efficient. To ensure right things are happening down the line, error-proofing your system becomes essential, and this involves additional information tracking. So the systems or solutions you choose should have these features.
  3. Scalability for the future: This characteristic can be interpreted in many different ways. But, in this blog it refers to adding features and functions as the need arises and building in capability to adapt to these changes is needed so that you are not starting from scratch again when the business needs to evolve again.

So, as we move into this new era of manufacturing, it is important to understand what the “ready for IIoT” tag on the device you are investing in means, and how it is helping you become more efficient or helping you connect to your customer one-on-one. Using IIoT to implement an ‘Enable and Scale’ plan would be the best way to meet the ever-evolving needs for the plant floor.

To learn more about IIoT and Industry 4.0 visit www.balluff.us.

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The 2010 Windpower Expo & Conference in Dallas, held recently at the end of May, was a hotbed of technical and commercial activity this year.  I had not attended the “Wind Show” since 2004, and I was amazed at the explosive growth of the event and overall industry in just six short years.  This was a very substantial gathering, with about 1,400 exhibitors and 20,000 attendees.

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