Find the best condition monitoring solution

Traditionally, many companies use reactive or preventative maintenance approaches, which may incur high spare part costs, inefficient use of maintenance resources and, worst of all, significant unplanned downtime. Condition monitoring takes a more proactive approach to maintenance by monitoring equipment conditions for anomalies such as excessive vibration or temperature increases and sending alarms when thresholds are exceeded. Condition monitoring also forms the basis for predictive maintenance. The data gathered can be used in trend analysis and modeling for predictive solutions.

Whether you already have some knowledge and experience with condition monitoring or are just getting started, we would like to help you learn more. We’re here to provide you with information to find the best solution for your application, including expert knowledge and insights on what to look for.

Where to start Condition monitoring? 

• Look for the machines that cause you the most frustration or could have the most impact on your production if they fail. These can be different machines with different tasks where a breakdown will cause lost production or damaged products.

• Consider where, when, and how equipment can fail. Look to your own experience, ask partners with similar machines, or even your equipment supplier to help you determine the most common failure points and modes.

• Analyze which parts of the machine fail. Moving parts have the highest potential failure point. On many machines, these include motors, gearboxes, fans, pumps, bearings, conveyors, and shafts.

• Consider what to measure. Vibration is a commonly gathered measurement and is often assessed in combination with temperature and humidity. On some machines, pressure, flow, or amperage/voltage should be measured.

• Question the current maintenance program for each machine and consider the costs/benefits of different maintenance approaches. In some cases, it may be OK to let a non-critical, low-value asset run-to-failure, while in other cases it might be worth investing in condition monitoring or predictive maintenance to prevent a critical machine's costly failure.

• Start small by implementing condition monitoring on one or two machines, and then scale up once you've learned what does and doesn't work for your operation. Using a low-cost sensor, which can be easily integrated with existing controls architectures or added on externally, is also a great way to start.

Which data do I need? 

The condition monitoring data which should be gathered depends on the individual application because different machine components fail in different ways and exhibit different failure indicators. Increased vibration and temperature can be early failure indicators for moving equipment, whereas changes in pressure and flow may be better failure indicators for fluid power systems. Once the appropriate indicators are known, matching sensors can be selected. These sensors will then transmit the data and allow the controller, supervisory system or cloud to use real-time condition monitoring data with the same speed they use a sensor’s primary process data.  

In line with our application example, we have listed here four indicators that are frequently gathered in condition monitoring with the corresponding effects on machines: 

Machine condition indicators such as vibration, temperature, pressure or flow can be detected by various sensors. Selection of the optimal sensor depends on the equipment being monitored, other attributes being sensed, budget/cost-benefit tradeoff, and the maintenance approach. In some cases, a single-purpose, dedicated condition monitoring sensor may be the right choice. In other cases, a multi-function sensor which can handle both condition monitoring and standard sensing tasks may be an efficient and cost-effective solution.

Where do I need the data and how does it get there?

Sensor condition monitoring data can be gathered and transmitted several ways, depending on where it is needed:

1. Data to be available in the PLC or machine control system
In manufacturing and automation control, the programmable logic controller (PLC) is an essential tool. If the condition monitoring data is required in the PLC, a traditional IO-Link controls architecture is the best approach. The PLC is already integrated into the machine, and condition monitoring sensors can be connected to the system via IO-Link masters. Once the PLC code is modified, the controller can be used as an all-in-one device for machine processing and condition monitoring. In addition, the condition data can be transmitted to supervisory systems or the cloud for data storage and deeper analysis.

2. Data to be available in a specialized controller/gateway  
A Condition Monitoring Toolkit (CMTK) can collect and process sensor data as an independent, stand-alone system which performs visualization, alarming and simple analysis. The CMTK is easily retrofitted to installed machines, without impacting the existing machine control system and offers plug-and-play commissioning of the system and visualization of the data. The software is preinstalled on the base unit and is used to set and monitor threshold values, warnings are sent when these values are exceeded. And LAN network ports allow optional connection to other systems and the cloud, and remote monitoring from any location.

3. Data to be available in edge gateway/cloud
The biggest benefit of an IIoT edge gateway is the ability to process and store large amounts of data quickly, enabling real-time applications to use that data efficiently. An IIoT edge gateway typically sits at the end or edge of the network and gathers all the sensor data either directly from the sensors or from the PLC or specialized controller. Since there will be a large amount of data from all the sensors on the network, part of the edge gateway setup is to filter the relevant and important information and process this vast amount of data. The gateway also provides a translation to different communications networks, whether local or cloud-based so that the data can be used across many different software platforms.

Condition Monitoring Toolkit vs. IO-Link Master

The Condition Monitoring Toolkit (CMTK) and IO-Link masters are gateways which take sensor data and communicate it to machine controllers, supervisory systems, or the cloud. An IO-Link master is a good choice for new installations which include IO-Link or for when the data is needed in the PLC or machine controller. The CMTK is an excellent add-on solution to systems which are already installed or when changing the existing controls architecture is difficult. It is also a good solution when built-in visualization tools are desired or when data is needed in the cloud.

How do I set the right limit values? 

Alarm limits must be set based on the specific application and any relevant outside factors. However, there are several ways to approach them. In the example of vibration, you could use your experience from the past, discussion with experts, or even use the help of guidelines like the ISO standard for vibration. Vibration is one of the most critical metrics regarding the health of machines, providing early detection of potential faults - before they cause damage or equipment failure. Most customers are confused about where to start. They want a baseline to begin monitoring machines and then finetune them to their use case.

One approach is to hire a vibration expert to determine the baseline and the best location to mount the vibration measuring sensor. Proper setup by an expert can ensure reliable data is obtained and can speed up the process of developing a condition monitoring process. You could also choose to use standardized ISO baseline charts to determine your own baselines and the best mounting positions for their sensors. Generally tables show the different standards for severity for different machine classes. These standards detail the baseline vibration and show the best place to mount the sensor based on the machine type. You can proceed similarly for the other data types. Or contact us and we will find your solution together.

Another approach is to speak with colleagues, partner companies or equipment suppliers for their experience and recommendations setting limits for similar equipment and applications. This approach may be low-cost, but other machines and applications may not be good benchmarks for your equipment.

And then there are standardized baseline guidelines from ISO, which can be used to determine your own baselines and the best mounting positions for your sensors. For general-purpose industrial rotating machinery with a power of more than 15 kW and a speed range between 120 r/min and 30,000 r/min, the vibration specification ISO 20816-03 is commonly used. These guidelines are extremely convenient and make it easy to set up limits in practice. Check here for more information on using the ISO guidelines with the Balluff Condition Monitor (BCM).

How can I analyze data? 

Data can be processed and analyzed several different ways and the selection of a gateway can impact this.

The IO-Link master is part of a traditional controls architecture, and the sensors are set up using IO-Link configuration tools. The sensor data gathered and transmitted by the master must be stored and analyzed in the PLC, machine controller or supervisory system. With this approach users must create their own alarms, visualization, and analyses. A variety of third-party software tools are available to do this, with a wide range of capabilities ranging from creation of simple dashboards to sophisticated condition monitoring and predictive analysis tools.

The Condition Monitoring Toolkit has analysis functions available that allow the user to set limit values directly through the toolkit's interface. Warnings can be received within the dashboard or via email, while the alarms from sensors can be sent via MQTT. The collected data, which you own, is available for further processing, and individual solutions and analysis tools are on the system, including simple machine learning capabilities. The condition monitoring data can also be transmitted to other systems and analyzed in more detail using third-party software.

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