Along with all this cutting-edge technology, Hexagon demonstrates how paying attention to fundamentals is also vitally important to customer success.  We had numerous Hexagon Enterprise Asset Management (EAM) customers come by the Itus Digital booth to talk about the next natural steps in their asset management journey.  We learned how these organizations manage maintenance activities and react efficiently when things require attention. With Hexagon EAM in place, they have a solid foundation to drive the next steps of achieving an optimal balance between risk, cost, and performance of assets.  Now Hexagon EAM customers are asking themselves, what’s next?  How do we eliminate failures altogether and optimize maintenance activities based upon the current risk in the business?  Asset Performance Management (APM) is the additive business process to help achieve these objectives.

As a Hexagon partner, Itus Digital is ready to take these organizations to the next level in their asset management journey.  Itus brings the power of APM to mitigate risk to an acceptable level by operationalizing asset strategies.  With operationalized asset strategies, preventative maintenance and inspection activities are driven based upon current failure risk and early warning is provided when potential failure is detected.  Armed with asset strategies, industrial organizations can optimize the use of maintenance resources and minimize equipment downtime.

Itus Digital collectively has a generation worth of asset performance management experience and has strong ties to Hexagon from a technology perspective.  If you would like to learn more about how to drive APM processes from solutions such as EAM, SDx, and J5, connect with us here.  We look forward to the productive dialog we started at Hexagon Live and to next year’s conference where we will present the Asset Performance Management stories that began at #HxGNLiveGlobal 2023.

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The industrial market has exploded with new sensors and solutions which can quickly and affordably monitor vibration in rotating machinery and predict potential failure.  From wireless sensors to handheld devices to completely outsourced condition monitoring services, you now have many options when looking to mitigate one of the most common failure risks in rotating machinery, high vibration.

In addition, we are seeing industrial organizations increase their adoption of standards as they can provide reliability and maintenance teams with the opportunity to take advantage of expert perspectives and years of learning at a very low cost.  These technical standards, in particular, provide a solid starting point for organizations looking to implement basic condition monitoring.

As a technology provider to the industrial market, Itus Digital leverages standards as they allow our customers to quickly develop best practices built on what experts across industrial sectors, have developed over the years.  Our latest work here is the inclusion of ISO 10816 compliance elements into the Itus Asset Twin Library.

This article offers insights into the ISO 10816 Standard and provides a walk through on how Itus Asset Twin capabilities enable the requirements of this standard.  As a technical footnote to this article, we will limit our discussion to the use of overall vibration readings as defined in the ISO Standard.  We will not be addressing the use of detailed vibration data (such as waveform) which are also a key aspect of vibration data diagnostic activities.

What is the ISO 10816 Standard?

The ISO 10816 standard provides guidelines to evaluate the severity of overall vibration levels of machinery taken from sensors or handheld devices.  The standard has seven ‘parts’ which offer guidance for a variety of machine designs and applications.  For the audience reading this blog, ISO 10816-3 (Part 3) will be of particular interest as it specifically applies to industrial machines with nominal power above 15kW and speeds between 120 and 15,000 revolutions per minute (RPM).  Typical machines included in this standard include pumps, fans, motors, blowers, and rotary compressors which can often be significant drivers of repair cost and downtime.

One of the most valuable aspects of ISO 10816-3 are guidelines on how best to interpret the results from vibration readings taken on non-rotating parts of the machine (such as the housing).  The chart below provides a concise summary of how to interpret the severity of overall vibration readings based upon the machine group and foundation type.

Once readings are taken, the standard can be applied to evaluate if further action should be taken such as a more thorough diagnostic, operator check or specific maintenance activity to prevent equipment damage.  It can also be a trigger to check the execution of standard preventative maintenance activities.

Applying the ISO 10816 Standard

Here is a common situation we see with our customers.

• Vibration monitoring programs are recognized as a valuable method for early detection of failure risk across various equipment types to prevent catastrophic failure, unnecessary repair costs and production downtime.
• Investments in continuous vibration monitoring solutions have been made in highly critical equipment which represent a small percentage of all rotating equipment.
• Expansion of vibration monitoring programs is desired on medium and low criticality equipment leveraging low-cost sensors and handheld devices.

The key challenge they face is how to leverage these new equipment condition data streams to their fullest potential without putting more burden on already stretched resources?  Additionally, how to implement these new data streams without creating another siloed data source.

This is where enabling technology such as the Itus Asset Twin can be leveraged to develop best practices such as those that can be enabled with ISO 10816.  With Itus technology, not only can the prescribed decision criteria be automated, but the results of the evaluation can also be driven into broader reliability and maintenance processes in your organization, realizing more value from your assets:

• Centralized management of all vibration monitoring advisories from your various sensors, field data collectors, and solutions to drive collaboration among your equipment experts.
• Integration of additional equipment conditions from other systems such as thermography, oil analysis, and process monitoring to enable broader failure mode coverage and overall asset health scoring.
• Automatic generation of requests in your maintenance management to drive appropriate follow up or repairs as needed.

Let’s walk through a quick example of how ISO 10816-3 requirements are enabled with an Itus Asset Twin.  Below is the configuration of the standard’s requirement for Machine Group 1 on a flexible foundation.

In this configuration, the Itus Asset Twin is utilized as a screening tool for machinery vibration to identify situations which require more diagnostic tests or the initiation of an inspect/repair activity.  Here are the key aspects of the Protection implementation.

• Tag Aliases – The incoming vibration data stream from sensors, handheld devices or historians. This template is set up for readings with units of in/sec but mm/s is also supported.
• Thresholds – The definition for the analytical evaluation of the vibration readings. This example is very straightforward with two threshold evaluations, .28 in/sec and .44 in/sec.
• Actions – The prescribed action which will be recommended when the Threshold condition has been met. In this case, when the ISO defined Threshold of .28 in/sec is met we recommend performing a more detailed vibration diagnostic at a high priority within the next 3 days.  If the vibration readings exceed .44 in/sec, we recommend an operations/maintenance intervention as the standard indicates the machine may experience damage.

This example of an Asset Twin demonstrates how ISO 10816-3 requirements can be technically enabled ‘in kind’ but you can easily adjust this definition based upon your specific operating experience and context as needed for your business needs.

Itus Libraries quickly enable the requirements of this standard

Our use case for this article has focused on one specific aspect of ISO 10816, Part 3, more specifically, machine group 1 with a flexible Foundation.  Beyond this example, subscribers to the Itus solution have access to every scenario covered in Part 1 and 3 of ISO 10816 through the Itus Asset Twin Library.  For subscribers of the Itus solution, the requirements of the ISO standard can be enabled for a piece of equipment within minutes by accessing the library, selecting the appropriate machine group and foundation type, and then applying the model to the vibration data feeds from sensors, devices or monitoring solutions.

The Itus Asset Twin Library also provides Asset Twin templates for the most common failure modes across over 200 types of industrial equipment.  Leveraging this library allows maintenance and reliability teams to standardize their asset strategies and drive a consistent approach to preventive maintenance activities, condition monitoring and evaluation of equipment health.

Minimize failure risks by enabling standards requirements with Itus technology

Vibration monitoring is a very effective approach for early detection of potential failure in rotating machinery.  Historically, applications of vibration monitoring have been limited to highly critical equipment due to the cost and required resources.

Advancements in sensor technology and handheld data collection have dramatically reduced the cost of assessing machinery vibration which now opens the opportunity to expand usage for medium and low criticality equipment.

The downside is organizations are now drowning in sensor data and need simple methods to analyze and interpret that data from a myriad of equipment and condition data sources.  Fortunately, ISO 10816 provides a practical model to assess the severity of vibration readings and should be considered when implementing a vibration monitoring program.

Evaluation of vibration data and compliance to the ISO 10816 standard is just one simple use case of how the Itus APM solution can be used to drive optimal asset strategies to reduce maintenance cost and lower equipment failure rates.  If you would like to learn more about our approach and solution, please connect with us here.

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The primary mechanical failure risk being investigated in the accident is the overheating of a wheel bearing. Overheated bearings are not the only problem that can cause a train to derail, but they are essential to a train’s safe and efficient operation. Inside each bearing is a series of rollers that are a critical component in turning the rail car axle. When lubricated, the bearings limit friction while supporting the railcar’s weight. If a bearing gets too hot, usually from a loss of lubricant, it can melt, causing it to seize up or come off the axle. The resulting damage can throw a railcar out of alignment and cause it to jump the tracks.

“Roller bearings fail. But it’s absolutely critical for problems to be identified and addressed early so these aren’t run until failure”  NTSB Chair Jennifer Homendy

Norfolk Southern has implemented protections to mitigate bearing failures on its railcars using a Hot Bearing Detector (HBD). The HBD is placed trackside at fixed points and automatically measures the axle temperatures as the train passes by. Its function is to detect overheated bearings and provide real-time warnings to train crews so they can take appropriate action. A more detailed view of the protection scheme, evaluation thresholds, and prescribed actions is provided below.

The protection definition follows very similar constructs to an Asset Twin in the Itus Solution. Key components which are defined include a Failure Risk, which is the elevated bearing temperature due to lack of lubrication. Also defined is the specific Protection, which monitors the bearing temperature over time. The Advisories (prescriptive actions) are also defined, which detail what should be done when certain conditions identify emerging threats.

The report found that the temperature of the bearing in question had been increasing for 30 miles before reaching East Palestine. However, only the third reading reached Norfolk Southern’s threshold to stop and inspect the train via a real-time audible alarm. Unfortunately, the alarm was triggered too late as the train derailment was already in process.

The bearing temperatures were evaluated at three data points before the train derailment. The 23rd car’s axle had a recorded temperature of 38 degrees above ambient temperature at Milepost 79.9 on the Fort Wayne Line. At the next detector at 69.01, it increased to 103 degrees, and at Milepost 49.81 on the east side of East Palestine, the recorded temperature was 253 degrees above ambient.

The accident highlights key constructs to consider when designing failure risk protection models.

Data polling rates should consider condition escalation rates to allow for enough time to detect and respond to mitigate the identified failure risk. In the case of the NS derailment, the distance between the last two temperature measurements on the wheel bearing was 19.2 miles, and the temperature difference over that time was 150 degrees. Somewhere over that time, the bearing temperature passed through a non-critical threshold that would have advised the train engineer to stop and inspect the rail car but significantly pushed past the critical threshold of 200 degrees. To mitigate this potential data gap in the future, the Association of American Railroads announced that all seven Class 1 railroads in the country have committed to adding approximately 1,000 detectors to close the gaps between detectors and achieve an average spacing of 15 miles.

Design thresholds, analytics, and actions from actual experience. When designing a Failure Risk Protection, reliability engineers must make key decisions, including how many thresholds to implement, how much tolerance should be given for each threshold, and what to prescribe for risk mitigation at each level. Design thresholds, analytics, and actions from actual experience, using historical data to simulate a model and define analytics for a specific operating context. Sometimes this information is available through the collective knowledge of industry experts via standards such as ISO10816 (mechanical vibration).  In other situations, this information may be available from OEMs in their operation, maintenance, and troubleshooting manuals defined from their specific failure testing.  Many times, these models are developed from a ‘really bad experience’ or consequential failure.  As a result of this accident, Norfolk Southern is working with manufacturers to develop more sensors, reevaluate triggering thresholds, and analyze data for patterns that could provide earlier warnings. A more robust method to design Protections is from actual operating experience.  Solutions like Itus provide an ability to simulate a model from historical data which is an ideal method to define analytics for a specific operating context.  The capability allows engineers to understand how often the system will advise at various threshold levels, ensuring there is appropriate time to respond with the most appropriate prescriptive action to mitigate the risk.

Accounting for the worst-case consequence is essential in evaluating risk and advising on mitigations with critical context to drive appropriate action. Unfortunately, we often see analytical models which are not designed from a complete risk context.  By injecting risk into a Failure Protection scheme we can assess the situation more accurately (historical probability of failure) but more importantly we can advise on mitigations with critical context to drive appropriate action.  According to the Federal Railroad Administration, about 1,000 derailments occur each year but on average only 17 of those accidents involved rail cars with hazardous cargo that could present significant safety or environmental risks.  Ideally, risk should be evaluated within the analytical model to provide more advanced warning, increase time to respond, and offer more specific context on what is happening and what to do. As we are learning from the East Palestine accident, there is a very different consequence when a rail car carrying freight has a failing bearing vs. a rail car carrying highly toxic vinyl chloride.

The East Palestine accident impacted 2,000 residents with long-term environmental and health concerns. The rail industry has a keen understanding of the wheel bearing – lack of lubrication failure mode for rail cars and is making progress on the protections that can be put in place to mitigate the risks. The preliminary report has provided great insights for anyone building analytical or failure risk monitoring models that are great reminders for design moving forward.

If you are interested in learning more about Asset Twins and how the Itus solution can rapidly implement failure risk protections to predict and minimize unplanned events, feel free to reach out to us, we would love to chat!

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