Condition Monitoring/Predictive Maintenance

Food processing plants typically run their equipment for 16 to 20 hours a day, yet a Forbes report claims that manufacturers face an average of 15 hours downtime per week. This translates into increased operation costs and disruptions in the supply chain, causing delays in deliveries. Here Tom Cash, director of Siemens parts supplier, Foxmere, explains how the role of condition-based maintenance (CBM) helps maintenance engineers recognise gross defects before catastrophe strikes.

CBM is a strategy that monitors the actual condition of an asset to decide what maintenance needs to be done. Using sensors, this strategy dictates that maintenance should only be performed when specific indicators show decreasing performance or upcoming failure.

Checking a machine for these indicators include non-invasive measurements, visual inspection, performance data and scheduled tests. Condition data can then be gathered at specific intervals or continuously, as is done when a machine has internal sensors.

Simply put, the primary goal of CBM is to optimise equipment maintenance practices by monitoring real-time data and responding to the actual condition of assets. It aims to prevent unplanned downtime, reduce maintenance costs and extend equipment lifespan by conducting maintenance activities only when necessary.

Better than predictive maintenance?

Although similar, CBM differs from predictive maintenance in its approach. Yes, both strategies involve real-time data and analytics, but CBM is a broader concept that covers various maintenance strategies driven by equipment condition.

Predictive maintenance, on the other hand, specifically relies on data analysis and machine learning to predict when equipment failures are likely to occur. As the name suggests, this method focuses on predicting when equipment failures might occur, with the aim to pre-emptively address issues.

That’s not to say that CBM can’t include predictive maintenance as one of its components. However, it encompasses other techniques, such as preventive and corrective maintenance, based on observed conditions.

Therefore, the question food maintenance engineers should ask is, what strategy best suits your requirements? For instance, CBM is suitable for equipment impacted by variations in operating conditions, like temperature, pressure or flow rates, as continuous monitoring ensures consistent product quality.

Whereas predictive maintenance is valuable for predicting failures in equipment critical to maintaining specific processing conditions, like heat exchangers or refrigeration systems.

CBM for food safety

Food safety problems can have many root causes. A significant number of incidents reported to the Rapid Alert System for Food and Feed (RASFF), which is established by the European Union to ensure a high level of food safety and protect public health, are caused by contaminations with extraneous material.

Such material includes metal pieces coming from broken equipment, grease or detergent remnants. In fact, heavy metals represented the fourth most often notified hazard category in the RASFF from 1980 to 2016.

Contamination is arguably the biggest risk to any food and beverage manufacturing firm. As a result, these companies should be looking at new technologies, like IoT sensors, to ensure food safety as well as improving overall equipment effectiveness.

Monitoring the condition of bearings and metal detection equipment that impact food safety eliminates the risk of metal parts ending up in the food. As mentioned above, an advanced and very welcome development is the use of sensors, which trigger timely cleaning to avoid contamination risks.

Calling upon the support of parts suppliers, like Foxmere, food manufacturers can source these sensors in their journey in making CBM, or predictive maintenance for that matter, a reality.

These tools allow you to identify where the choke points are in your food and beverage production lines proactively, rather than reactively. As, after all, these efforts are geared towards helping maintenance engineers recognise gross defects before a catastrophe, like contamination, strikes.

To ensure that your business is amongst those thriving, contact Foxmere today for a no-obligation quote on automation equipment ranging from replacement or obsolete parts to complete robotic systems.

Practically all production, manufacturing and assembly processes use compressed air or vacuum systems at some point in their process. Compressed air and vacuum systems are reasonably inexpensive to install, fairly easy to maintain, and usually very reliable.

While these systems are installed and used with very good reason, they can have inefficiencies that can impact their performance, costing businesses a significant amount of money.

Leaks develop over time and subsequently compressors and pumps run at higher rates to compensate; processes are rarely interrupted. If leaks become severe then its often easier to add additional compressors and pumps then it is to fault-find and repair leaks, especially in loud and noisy operational factories.

Enter the FLIR Si-series of acoustic cameras. These cameras see sound, overlaying leak information onto a digital camera screen, adding quantifiable metrics about the leak severity and likely cost to the business for each individual leak identified.

FLIR acoustic cameras work at distances well beyond 50 meters, filtering out irrelevant noise from operating production lines to isolate leak information and clearly pinpoint their location.

After surveying a facility, all images, along with their leak metrics can be viewed on-camera, or uploaded onto cloud-based reporting software, or transferred to FLIR Thermal Studio reporting software.

Leak images will clarify and improve repair work orders, every leak repaired will reduce the electricity consumption of the compressors and pumps used, which in-turn reduces their associated emissions.

Acoustic imaging works beyond air leaks, also locating leaks in CO2, Nitrogen, Hydrogen, Helium, Argon and other industrial gas systems too, associated savings are significantly higher for industrial gasses due to their increased production and purchase costs.

Contact FLIR or one of our partners and request a telephone consultation, or even an in-person demo to see how much money we can help your business save too.

Click the link below for more information.

https://bit.ly/3SVefGZ

Rules of Thumb for Maintenance and Relibility Engineers by Rick Smith and and Keith Mobley.  to read this great article click on the link below. 

Leading_and_Lagging_Key_Performance_Indicators_2.pdf

Interested in Maintenance and Reliability Best Practices Articles? If so go to: www.worldclassmaintenance.org

In the context of Condition Based Maintenance (CBM) it is generally accepted that measuring the vibration of a rotating machine (motor, pump, fan etc.) will tell us something about the condition of the machine. But what exactly are we measuring and what does it tell us about the machine?

Basically, it boils down to two numbers. One is the average (RMS) value of the low frequency vibration that tells us something about how well the machine is running. The other is the average value of the high frequency vibration that tells us something about the condition of its bearings.

The low frequency vibration is the typical “hum” you hear from a rotating machine. This vibration is due to the centrifugal force resulting from any out-of-balance in the machine. Since it is virtually impossible to exactly align a machine’s centre of gravity with its centre of rotation, even a well-balanced machine will still vibrate or “hum”. But what is an acceptable level? This is where the International Standards Organisation (ISO) comes to our aid. ISO have produced a set of guidelines that define suitable levels of machine vibration in the frequency range 2Hz to 1kHz (120 RPM to 60,000 RPM). That frequency range being chosen because it covers the vast majority of machine running speeds normally encountered.

The high frequency vibration is the typical “whine” you hear from a badly worn bearing. In practice, it is there all the time but is inaudible until the bearing becomes so bad it is probably about to fail. Fortunately, a vibration analyser can detect the inaudible bearing noise well before it gets to that point. This means bearing wear can then be displayed, for example, in Bearing Damage Units (BDU) that can very roughly be thought of as a “percentage” of bearing wear.

Vibration analysers employ sensors to capture a vibration waveform from a machine and then analyse it to automatically generate the ISO reading and the bearing condition. It is largely this ability that distinguishes them from simple vibration meters. The readings below, taken from a typical VibTrend report, show vibration levels measured on a motor. The ISO readings appear in green as they are below the recommended 4.5mm/s ISO warning level for a medium size motor. However, the drive end bearing noise is displayed in red as it is above the specified 100 BDU critical alarm level. The high BDU reading was in fact due to an outer race defect on the drive end bearing.

Test Products International manufactures a complete range of low-cost, high-performance vibration analysers from the £575, one-button-to-press TPI 9070, to devices that include advanced diagnostic and machine balancing capability. The TPI 9070 features colour coded alarm levels and zoomable on-screen vibration frequency plots together with on-meter analysis for the detection of machine faults such as unbalance, misalignment, looseness and bearing wear.

The TPI 9080 from £1,100 comes complete with VibTrend PC based trending and reporting software that includes automatic report generation and email notification of alarms, implementing a full CBM solution. The TPI 9080 can store lists (routes) of machines (up to 1000), each with up to 10 measurement points, all with full vibration waveform and frequency spectrum (FFT) capture.

Routes and readings can be transferred between the TPI 9080 and the included, license free, VibTrend in a variety of different ways.  Via the included USB docking cradle, wirelessly via Bluetooth or remotely via a Bluetooth link with a smart phone or tablet running the free TPI Bridge App. This allows service personnel to receive and return routes and readings, no matter where they are in the world.  

For more information please contact TPI Europe’s head office on +44 1293 530196 or take a look on the website at www.tpieurope.com or email This email address is being protected from spambots. You need JavaScript enabled to view it.

One City Global have just launched their Predictive Maintenance Solution which with its machine learning capabilities brings far more efficiency and accuracy to your maintenance systems.

This cutting-edge solution is set to revolutionize industrial maintenance practices, enabling businesses to optimize their operations, reduce costs, and enhance overall equipment reliability.

Traditional maintenance practices have often relied on reactive or scheduled maintenance, leading to potential downtime, unplanned expenses, and inefficiencies. One City Global's Predictive Maintenance technology takes a proactive approach, harnessing the power of artificial intelligence to forecast and prevent equipment failures before they occur.

Using a combination of machine learning algorithms and data analysis techniques, One City Global's Predictive Maintenance solution continuously monitors the performance of critical machinery and systems. By analysing historical and real-time data, the technology can identify patterns, anomalies, and indicators of potential issues that may lead to failures or breakdowns.

The system includes a number of configurable dashboards that allow users a quick overview of the data to help make informed decisions or act quickly if a situation requiring rapid intervention occurs.

Key Features and Benefits of One City Global's Predictive Maintenance Solution:

1. Early Fault Detection: identify subtle changes in equipment behaviour and detect potential faults or anomalies at an early stage, allowing for timely interventions to prevent failures.
2. Optimal Maintenance Planning: accurately predict equipment maintenance requirements, to plan and schedule maintenance activities more efficiently, minimizing disruptions to operations and reducing unnecessary maintenance costs.
3. Increased Equipment Reliability: proactive maintenance measures can maximize the lifespan and reliability of machinery, avoiding costly downtime and improving overall operational efficiency.
4. Cost Reduction: help eliminate unnecessary maintenance tasks, optimize resource allocation, and reduce overall maintenance costs.
5. Data-Driven Decision Making: leverage the power of data analytics and machine learning, to gain valuable insights into equipment performance, to enable informed decision-making for maintenance strategies and resource allocation.

One City Global's Predictive Maintenance technology is designed to be adaptable and customizable to various industries, including manufacturing, energy, transportation, and more. The solution integrates seamlessly with existing systems, making it accessible and practical for businesses of all sizes.

“Significant savings of around 10-30% reduction in inventory levels, and around 5-15 % reduction in downtime can be realised through minimising equipment maintenance time and lost production hours. In addition to this a reduction of around 3-5% in new equipment costs are achievable.” (source Deloitte Development LLC)

To learn more about One City Global's Predictive Maintenance technology and its transformative impact on industrial maintenance, please visit www.onecityglobal.com  or email us at This email address is being protected from spambots. You need JavaScript enabled to view it..

"What led to this condition?" is one of the most common questions asked in the course of inspecting faulty or damaged rolling bearings. For machines with rotating shafts, the focus is on monitoring the rolling bearings. As the interface between the shaft and the machine foundation, they have to absorb the resulting forces. This means that faults and damage in design and operation have a particularly strong effect on rolling bearings. This is precisely what makes them suitable measurement points. Although rolling bearings are among the most important components in most machines, there is often a lack of effective methods for monitoring them. Monitoring (trending) is performed to detect changes or deterioration in condition. For this purpose, simple characteristic values are recorded by means of recurring measurements and their change is observed over time. If an alarm value is exceeded, measures must be initiated. If it is a first warning level, a detailed analysis is carried out first and, if necessary, the time interval until the next measurement is shortened. In order to identify a fault or damage pattern and determine the causes, special evaluations of the measurement data must be carried out. Simple characteristic values are not sufficient for this purpose. At this point, the maintenance measure can be planned accordingly, depending on the severity of the damage level and the possible cause. If the actual alarm level is exceeded, the machine must be stopped either immediately or as soon as possible. The maintenance actions must then be carried out immediately.

BS40: Innovative and reliable solution

The new BS40 broadband structure-borne sound sensor was developed by SONOTEC to help companies worldwide better maintain their rolling bearings. This practical and robust sensor is ideal for condition monitoring on machines with rotating parts. The product design impresses with a laser-welded stainless steel housing. The ¼"-28 UNF threaded bolt allows for maximum flexibility in mounting as well as in use, as the BS40 can be used with magnets for flat or curved surfaces. In addition, the BS40 can also be screwed to adhesive pads with an internal thread, resulting in excellent reproducibility. The optimized sensor characteristic in the range from 10 to 65 kHz ensures a nearly linear frequency response. An extension of the ultrasonic frequency range to <1 kHz also offers even greater flexibility in machine diagnostics. The sensor incorporates a piezocomposite material developed by SONOTEC that helps overcome the drawbacks of many solutions available on the market. Thus, a more reliable evaluation of bearings is possible.

SONAPHONE & LevelMeter App: Intuitive Hardware and Software Solutions

With the intuitive LevelMeter App, the SONAPHONE® digital ultrasonic flaw detector enables broadband measurements and determination of characteristic values. Due to the high sampling rate of 256 kS/s, signals up to 128 kHz can be analyzed. Up to this limit, characteristic values can be calculated and audio signals can be generated based on the filter settings. The instrument provides two methods for converting the ultrasonic signals into the audible frequency range. The heterodyne method is used when a narrowband transformation (bandwidth 4 kHz) is needed, while the vocoder method is suitable for a wideband transformation. The live signal is displayed as time signal, level graph and spectrogram.

Condition Monitoring Excellence

The powerful combination of the SONAPHONE®, the intuitive LevelMeter app, the broadband BS40 sensor and the maintenance task management software - SONAPHONE DataSuite - help you achieve the highest possible efficiency in your ultrasonic condition monitoring program. This holistic ultrasonic solution helps the maintenance team ensure that your equipment production processes are running smoothly. Timely maintenance actions can prevent costly downtime and costly repairs. Decisions regarding bearing lubrication can also be made based on acoustic feedback rather than time interval. With ultrasonic testing equipment developed and manufactured in Germany, it is now possible to detect rolling bearing damage at an early stage and optimize lubrication.

You can find out more about SONOTEC ultrasonic testing equipment at www.sonotec.eu

Condition Based Maintenance (CBM), using tools such as vibration analysis, thermal imaging, ultrasonic detectors and oil analysis, is now clearly recognised as being the key to running an efficient maintenance program. By comparison, planned maintenance, or worse still breakdown maintenance, strategies are expensive and unreliable, and particularly in these harsh financial times could prove to be the death sentence for a production facility.

Whilst they are using CBM tools, service and maintenance personnel bring another valuable skill to the job – they use their eyes and ears!  For example, a vibration analyser indicates that a pump bearing is likely to fail prematurely sometime in the next two months - but why has this happened?  A simple inspection may show that the drive coupling is misaligned, which can then be remedied along with the bearing change.  This is Proactive Maintenance, identifying the root cause of the problem and correcting it.  What if the misaligned coupling hadn’t been fixed? – The bearing may simply have been replaced, only to prematurely wear out again!

It is generally accepted that the three main causes of premature bearing failure in rotating equipment are:

• Out of balance
• Misalignment
• Lack of lubrication

Fortunately, thanks to modern technology, all of these conditions can be detected very easily using extremely affordable, simple to use handheld vibration analysers. For example:

Out of balance shows up as a large amplitude vibration at the running speed (1X) of the machine.

Misalignment on the other hand generally shows up as an additional large vibration at twice the running speed (2X).

Lack of lubrication will result in high frequency vibration (bearing noise) that is not necessarily audible to the human ear but can easily be detected by a vibration analyser.

Finally, machine looseness will typically generate vibrations at higher harmonics of the machine running speed e.g. three times running speed (3X) and above.

These days, once diagnosed, all these faults can easily be remedied in-house using affordable easy to use tools such as laser alignment systems, in-situ rotor balancers or even a simple grease gun!

Technology to the rescue

Not so long ago CBM tools used to be expensive and difficult to use. But thanks to modern technology, these tools are now not only extremely affordable; they are also very easy to use.

The TPI 9070 (pictured) is a simple to use, incredibly low-cost vibration analyser that records, analyses and displays vibration signals at the push of a button. The unit displays colour coded alarm levels based on internationally agreed (ISO) vibration values and bearing condition. It also incorporates a fully zoomable vibration frequency spectrum (FFT) display with cursor, and diagnoses out of balance, misalignment, looseness and bearing faults.

Condition monitoring is a crucial aspect of equipment maintenance that involves tracking the health of machines in real-time to prevent potential breakdowns and unplanned downtime. Traditionally, condition monitoring has been carried out through manual inspections and routine maintenance checks. However, with the advancements in technology, artificial intelligence (AI) is being increasingly used in condition monitoring to automate the process and improve the accuracy of the results.

AI can be used in several ways to perform condition monitoring, including:

1. Predictive maintenance: Predictive maintenance involves analysing data from sensors installed on equipment to predict when maintenance will be required. AI can be used to analyse large amounts of data in real-time and detect patterns that may indicate a potential problem. This helps to identify potential equipment failures before they occur, minimizing downtime and maintenance costs.
2. Fault diagnosis: AI can be used to diagnose faults in equipment by analysing sensor data and comparing it to a database of known fault signatures. This helps to identify the root cause of a problem quickly and accurately, allowing for timely repairs and maintenance.
3. Anomaly detection: AI can be used to identify anomalies in equipment behaviour that may indicate a potential problem. This involves analysing sensor data and comparing it to historical data to detect any deviations from the norm. This helps to identify potential problems early on and prevent equipment failures.
4. Asset optimization: AI can be used to optimize the performance of equipment by analysing data from sensors and other sources to identify opportunities for improvement. This can include optimizing energy usage, reducing waste, and improving production efficiency.

Overall, AI can significantly improve the accuracy and efficiency of condition monitoring, leading to reduced maintenance costs, increased equipment uptime, and improved safety. However, it’s essential to ensure that the AI algorithms used in condition monitoring are properly trained and validated to ensure that they provide accurate results. Additionally, human experts must be involved in the process to provide oversight and interpret the results.

In conclusion, AI is an increasingly important tool in condition monitoring that can help to improve the reliability and performance of equipment. As technology continues to evolve, we can expect to see even more advanced AI applications in this field, providing greater insights and value to businesses

www.cmservicesglobal.com

this article can also be found in issue below.

• Schaeffler supplies Zentis with ProLink condition monitoring system to monitor stacker crane trolley bearings in cold and frozen storage areas. 
• Zentis required a solution that could reliably take measurements despite inconsistent measuring conditions and ultra-low temperatures. 
• ProLink provides early warning of any change in bearing condition, which has improved the planning of maintenance tasks and safety. 

Birmingham, UK | June 07, 2023 | Global automotive and industrial supplier Schaeffler has supplied a fruit processing company with its ProLink condition monitoring system to monitor the condition of trolley bearings on stacker cranes, which operate in cold and frozen storage areas. 

Zentis GmbH & Co. KG, with its headquarters in Aachen, Germany, is one of Europe’s leading fruit processing companies, producing jams and fruit preparations for the baking, confectionery and dairy industries.  

The Aachen site uses large stacker cranes for storage, transfer and retrieval. In order to monitor the large and difficult-to-access moving components in the cold and frozen storage areas and to avoid unplanned downtime, the logistics team at Zentis was looking for a predictive maintenance solution. 

Previous CM success 

Zentis had previously implemented Schaeffler’s SmartCheck condition monitoring devices on gearboxes and cable reels to monitor the health of a critical pallet lifter. The devices have helped to prevent unplanned downtime and optimise production. If the pallet lifter fails, the first production stoppages occur around two hours later. The SmartCheck devices measure the vibration, speed, temperature and imbalance of various rolling bearings in the gearbox, as well as the gear teeth/mesh. The CM solution has enabled an early warning period of several weeks which allows Zentis to carry out repairs and remedial action as part of planned maintenance work, thereby avoiding costly unplanned downtime.

A cold challenge 

In the cold and frozen storage areas at Aachen, a different kind of CM solution was required. The stacker cranes constantly move around the 30-metre tall racks in different directions. The trolley bearings, in particular the non-driven bearings, are highly stressed. The fact that constant measuring conditions do not exist during regular operation posed an even greater challenge. In addition, temperatures in the frozen storage area are as low as -20°C, which presented yet another challenge for the new measuring system, for example, how to attach the sensors to the measuring points.  

Michael de Ben, Head of Internal Logistics at the Aachen site, comments: “We were looking for a monitoring solution for our stacker cranes that could reliably take measurements despite inconsistent measuring conditions and ultra-low temperatures in order to protect us from unplanned downtimes.” 

A smart solution 

After approaching one of Schaeffler’s local authorised sales partners the Schaeffler ProLink condition monitoring system (CMS) was chosen. This intelligent measuring concept was adapted to suit Zentis’ unique requirements.  

To monitor the stacker cranes, a Schaeffler ProLink CMS and five sensors (bearing guards) were installed on each stacker crane unit. In order to perform meaningful vibration monitoring, the original measurement concept had to be changed in the multi-channel CMS. Schaeffler achieved this by breaking down the short, slow travel times into many short measurements. Any extreme impacts could then be determined from these measurements. 

To solve the temperature challenge in the cold storage area, the ProLink CMS was installed in the switch cabinet. In the frozen storage area, the ProLink system was placed in heated control cabinets that escort each stacker crane run. The sensors were attached to the measuring points using a special, cold-resistant adhesive compound. 

Permanent benefits 

The implementation of the ProLink CMS, has benefitted Zentis in several ways. With early warnings of any change in the condition of the stacker crane trolley bearings, the site has also seen an improvement in the planning of maintenance activities, as well as improved safety and transparency. The ProLink CMS is also fully integrated into the sites own control system. 

As Michael de Ben states: “The ProLink CMS monitors heavily strained moving components on the stacker cranes that, due to their size or mounting position, cannot be repaired promptly in the event of an unplanned malfunction. By using bearing guards, the vibration pattern of this equipment can be permanently observed and any deviation can be detected at an early stage. In this way, the ProLink CMS makes a crucial contribution to safeguarding the production supply at Zentis KG Aachen.” 

ProLink is part of the Schaeffler Lifetime Solutions portfolio, which offers a comprehensive range of products, services and solutions for industrial maintenance. It is designed to support maintenance engineers over the entire lifetime of a machine.

www.schaeffler.com

This article can also be found an issue below.