Logo_image_transparent.png

Condition Monitoring - all the details you need to know!

Nowadays, machines have to be operated to the limit of their capacity so that the costs of acquisition and production are worthwhile. The maintenance and repair costs should be as low as possible. In order to be able to fully enjoy the service life of a machine, smart measuring systems are becoming increasingly important. In most cases, the condition monitoring technology is the entry into the networked world of Industry 4.0 and the connection to future viability and competitiveness.



What exactly is condition monitoring?

With condition monitoring (CM), the technical condition of a machine is recorded using sensors. Significant measured values can be oscillations, vibrations, temperature and humidity. The actual and target values of a machine can be compared with the collected data. In this way, material fatigue and machine errors can be identified at an early stage so that countermeasures can be taken. With CM you know what happens when and learn to understand your machines better.


What ware the goals for condition monitoring?

Condition monitoring essentially pursues 2 goals:

  • Machine efficiency at maximum utilization through the early detection of material fatigue and

  • Safety for people, since the early detection of errors means a fast-reacting alarm system, e.g. B. an emergency shutdown can be integrated.

What are typical strategies of maintenance and repair operations?

There are 3 types of maintenance. CM is part of condition-based maintenance and thus stands between reactive and preventive maintenance. While reactive maintenance is only carried out when a machine actually breaks down and needs to be serviced, preventive maintenance sometimes involves replacing parts that are still functional. CM compensates for the weaknesses of both variants. The analysis of the measured values ​​makes errors recognizable in good time, before production comes to a standstill. Through the possible analysis of the cause, the service life of the machine parts is fully savored.


What are typical applications where condition monitoring is being used?

Condition monitoring can be found in particular on rotating systems, electric and combustion engines, compressors, pumps and in process technology.


How does condition monitoring work?

Sub-Steps

Condition monitoring can be divided into 3 sub-steps, with points 1 and 2 mainly corresponding to maintenance according to DIN 31051:

  • Condition detection means measuring and documenting the physical values ​​using sensors.

  • The status comparison is the comparison of actual and target or limit values ​​of the machines.

  • The diagnosis analyzes and localizes possible errors from the comparison of the values ​​and thus enables maintenance measures to be taken at an early stage, which can be meaningfully integrated into the production plan.

Sensors

Machines in the production industry must be equipped with sensors at the point where relevant measured values ​​for status analysis can be obtained. There are machines with already existing sensors or the possibility to retrofit them.


The sensors can be divided into the following functions:

  • Vibration monitoring on drives can be used on rotating machines to monitor axes and bearings.

  • Particle monitoring in hydraulic fluids captures the lubricant composition using an electronic microscope.

  • Heat monitoring using infrared or thermal sensors provides information about the heat development of individual machine parts.

  • Acoustic monitoring uses digital ultrasonic devices to measure signals in the high-frequency spectrum, locating friction and faults in moving machine parts.

  • Oil level monitoring analyzes contamination in the oil composition.

How do you measure any condition?

Period

Machine monitoring can be intermittent, either at regular or variable intervals, or continuous in real time. The intermittent measurement is able to show a long-term status development of the service life, but is not suitable for short-term deviations. The continuous measurement can completely document long-term and short-term developments.


Network

The data can be passed to the monitoring system via a wired or wireless network. The wireless network is usually quicker to implement since there is no need to run cables, but it is also more susceptible to interference from external factors. With a wired network, the shielding of the cables may have to be taken into account and electrical plans updated.


ExoSense® - a typical Condition Monitoring System (CMS)

The CMS covers the entire communication structure, from measuring the data to visualizing it on any end device. The sensors forward the measured values ​​to a monitoring system, which is connected to a router or also called edge device. The router forwards the data to a server via the Internet, which then sends it to the monitoring center. Here the data can be analyzed.


Lean.IQ is offering different solutions for data collection and aggregation. We differentiate our solution into a thin-edge and our edge software framework. Depending on the individual use case we will make a recommendation which solutions may be the best fit.


In addition, the measurement data can be combined with other parameters from process management (manufacturing process), quality management (damage statistics) and building management (security measures, room temperatures) to create a holistic monitoring system.


Data storage online vs. offline

This raises the question of who needs access to the data and from where. Is it sufficient to store the data locally (on-premise) or does it make sense to use a cloud for mobile applications? If the data collected is to be made available to mobile devices via the internet, privacy and cybersecurity issues also need to be considered. The Lean.IQ approach is "Cloud First" - just because we offer solutions with a high degree of standardization, allowing the user to get started quickly. With a no-code / low-code configuration environment it is possible to create your own IoT project without any line of code.


Integration using Lean Maintenance

The use of CM does not always have to be holistic and therefore cost-intensive. It is one of the core competencies of Lean.IQ to determine the best fit in an existing maintenance and repair operation. There are also individual entry options that are based on internal resources and, for example, only monitor the highest risk factors without having to change the entire infrastructure. The flexible use of condition monitoring is particularly interesting for smaller industrial companies. The most important question here is which monitoring objective is to be achieved. The principle of lean maintenance can help to find targeted monitoring. It determines which maintenance strategy makes the most sense for individual machines.


In order to capture all relevant aspects for your use case we seperate our approach in three individual phases

  • Exchange: Lean.IQ Exchange combines the exchange on technical and operational topics, market and industry trends with innovative concepts for transformation projects in a holistic approach.

  • Analyze: Lean.IQ Analyze examines operational value chains for optimal production parameters for maximum operational performance with benchmarks from research and development.

  • Connect: Lean.IQ Connect is the holistic, digital solution for reading data from processes or machines. A common data bus is the digital layer for the Industrial Internet of Things (IoT).

Now, let's transfer the strategic approach to building a typical condition monitoring application: In the first step, machines are sorted according to their importance for the entire value stream from customer order to delivery. Some are rarely used, while others have a massive impact on production. If a machine caused so-called bottlenecks in the value stream, it would be suitable for condition monitoring.


Since every machine consists of several plant parts, the second step aims to determine the riskiest components. The Failure Modes and Effects Analysis (FMEA) can help with the assessment here. In this way, suitable positioning for measuring sensors can also be determined. It makes sense to only apply this step to the prioritized machines from step 1.


The machines can then be divided into damage classes from 1-8, which are defined according to the impact on plant operation (A), frequency of damage (S) and predictability (P). While damage classes 1-4 are considered non-critical, damage classes 5-8 are suitable for condition monitoring.


Insourcing and outsourcing of data analytics?

The evaluation of the measurement data by experts is generally recommended if the know-how is not available in your own company. Complete outsourcing of condition monitoring makes sense for large production plants, since reading out the data becomes more and more difficult depending on the complexity. CM providers work with you to develop a monitoring strategy based on your goals, help with the installation of the technology and also support you with maintenance and the delivery of spare parts.


What are typical advantages and challenges building a condition monitoring application?

The potential of condition monitoring is versatile and future-oriented. CM is the connection to the digital, networked world of Industry 4.0. Topics such as machine learning (M2M) and Industrial Internet of Things (IIot) are milestones in the Smart Factory. The implementation poses a number of challenges, which essentially deal with the question of what, when, where, how and with what should be monitored.


Benefits

  • Monitoring the condition of the machine enables a prognosis of the remaining service life.

  • System deviations are detected early.

  • The measured values ​​help to find the cause.

  • A possible machine standstill can be reacted to more quickly.

  • Downtime can be reduced to a minimum.

  • Energy costs, maintenance and repair costs are reduced.

  • The machine output or overall equipment effectiveness (OEE: Overall Equipment Efficiency) is increased.

  • The quality of processes and products is optimized.

  • Maintenance measures can be integrated into the production plan with foresight.

  • Occupational safety for employees is improved.

  • Security measures can be better integrated.

  • The scope of use can be adjusted according to individual needs.


Challenges

  • CM cannot detect spontaneous failures of the machine, such as B. a violent fracture of a drive shaft

  • Especially for the continuous use of CM, the measurement data must be managed in the style of big data.

  • Reading, understanding and interpreting the measurement data is essential for the effectiveness of the condition analysis. Experts are needed here.

  • The scope of use must be carefully considered according to the individual needs of the machine. Questions like:

  • Which measurement parameters are meaningful or necessary to achieve the desired goal?

  • Which requirements for the reliability of the machine are necessary and realistic?

  • Holistic monitoring is costly, but not always necessary.

  • Data protection and cyber security must be taken into account.

For a barrier free approach Lean.IQ offers onboarding solutions where we take the first steps together and get you started. Just let our expert team be your guide and ensure you can meet your digitization goals. Together with Exosite we have been helping companies for over 10 years to get their project up and running with a connected solution. We will onboard your team, help to find the right hardware for connectivity and sensors, ensure data is flowing, and get your ExoSense instance set up while training you on the functionality.


What is the difference between condition monitoring and predictive maintenance?

CM is a prerequisite for the concept of predictive maintenance. The aim of PM is to predict the optimal time for maintenance based on calculated probabilities of occurrence, so that maintenance only has to be carried out when it is actually necessary. The data measured in real time from the continuous condition monitoring are essential for this. In order to cope with the flood of data, the system must be expanded to include a digital, intelligent communication structure. CM thus provides data for the status quo, while PM evaluates the data to predict the development of a machine's condition.


Conclusion

The early error detection of condition monitoring allows machine efficiency, service life and the production process to be optimized and maintenance and energy costs to be reduced. You get to know your machine better, you can order spare parts in good time and plan maintenance sensibly in production.


On the other hand, there are the costs for the monitoring technology and the integration of a CM system. However, permanent, comprehensive monitoring is not always necessary. Its use depends on individual needs and monitoring goals. The fact is that digitization is also progressing steadily in Maintenance 4.0. Condition Monitoring offers a way to follow the trend and stay competitive.


For those who want to get started quickly, Lean.IQ offers a starter kit consiting of pre-configured hardware and access to an IoT condition monitoring solution. Due to the plug and stream option, you can right away connect the kit and access your application within minutes.



12 views0 comments