Industrial Internet of Things Applications

Condition Monitoring

Any unexpected downtime in the production process or the sudden failure of a machine can lead to enormous costs for industrial companies, which can be avoided with condition monitoring, i.e. the continuous monitoring of machines and systems. In addition, further potential for improving production processes can be identified.

Condition monitoring involves the real-time measurement and analysis of relevant machine and plant parameters and provides reliable and detailed insights into the current and historical condition of machines. By analyzing the data and issuing an alarm in the event of deviations, imminent failures or signs of declining performance can be detected and prevented, or optimization potential in production can be identified. Predefined parameters, which provide information on vibrations and oscillations, temperatures, fill levels or current voltages, for example, serve as indicators. In addition to minimizing the risk of machine and production downtime, condition monitoring in industrial environments offers the following advantages.

Increase machine efficiency and plant effectiveness
By measuring and monitoring the parameters, inefficiencies can be identified, which can be prevented by condition monitoring. While machines and plants work more efficiently through production optimization, downtimes are reduced at the same time and a better basis for decision-making is made for the optimal time to rectify defects during ongoing production operation. 

Reduction of repair costs
Some machine parts can be very expensive to replace. Condition monitoring helps to give these components a longer life through early corrective action, saving the need to purchase expensive replacement parts. With the help of condition monitoring, technicians are able to act faster while focusing on the right fault. No unnecessary time is wasted checking non-faulty parts of the machine, which ultimately allows personnel to work faster and more effectively.

Increase in production capacity
Reliable and efficient machinery and equipment can significantly increase production capacity by improving utilization and minimizing throughput losses. 

There are a variety of applications for condition monitoring in different industrial environments, for example:

• Analysis of oscillations and vibrations
  Plant and machinery respond to vibration in different ways. Untypical vibrations can be used to detect defects due to misalignment or wear.
• Analysis of optimal filling quantities
  In the foundry industry, for example, the optimal filling of furnaces is of great importance in order to produce resource-efficiently and to reduce CO2 emissions. With condition monitoring, furnace fill levels can be determined and refilled with the exact amount of metal required.

In conclusion, it can be said that condition monitoring significantly helps to determine the exact condition of machines and systems and, on this basis, to derive further recommendations for action that contribute to the improvement and stability of the production process. 

Predictive Maintenance

Predictive maintenance is an important tool for a comprehensive maintenance program. It is by no means a substitute for traditional maintenance, but it is a useful addition to optimize maintenance intervals. While traditional maintenance management relies on routine maintenance of all machines and equipment, a predictive maintenance program plans specific maintenance tasks based on need and machine data.

With the help of collected and analyzed data, developing errors and inefficiencies can be detected at an early stage and unplanned downtime or cost-intensive emergency repairs can be avoided. Monitoring here takes place continuously in real time, so that in the event of emergencies, timely responses can be made and possible precautions can be taken. Based on the analyzed data, predictive maintenance can provide detailed forecasts about the expected future condition. Simply put, three pieces of information in particular become usable through predictive maintenance:

1. Whether a plant will break
2. How it will break, and
3. How much is available to repair or replace the plant or machine before it breaks down.
   

With this information, maintenance can be planned at a time suitable for the production process. To enable permanent monitoring in real time and thus condition-based maintenance, relevant data from machines is collected, compared and evaluated. By recording the condition of the machine, diagnoses, i.e. comparisons of target and actual values, can provide early indications of technical or mechanical defects and impending machine failures.

Reduce the cost of unplanned downtime
Often the true cost of unplanned downtime due to failed equipment in industrial environments is greatly underestimated. The following costs can be minimized or even prevented:

• the real cost of an unplanned delay in production
• necessary maintenance personnel to repair the equipment and possibly overtime incurred for this purpose
• depending on the severity and nature of the machine failure, other machines may be damaged as a result of the equipment failure
• the cost of storing and procuring spare parts

Apart from avoiding downtime due to machine failures, predictive maintenance also leads to other considerable benefits.

Maximizing ROI and machine efficiency
Predictive maintenance makes it possible to maximize the ROI of machines and equipment, because by monitoring the actual and future condition of the machine, they only need to be serviced, repaired or even replaced when it is actually necessary. At the same time, machine efficiency can be significantly increased and also offers the chance to exploit the maximum service life of the machine.

Efficient use of maintenance personnel and increased employee safety
If a fault is detected on a machine or system, resources can be efficiently scheduled for preventive repair or corrective action at an optimal time. At the same time, production employees work in a safer environment because, depending on the type of machine, a failure may well pose a risk to the safety of employees who are in the immediate vicinity of the equipment.

Ultimately, it can thus be said that predictive maintenance is an important component of any industrial maintenance strategy and can be applied in a variety of ways. Maintenance can be optimized cost-efficiently and at the same time offers the possibility to maintain the stability of the production process through increased machine and plant availability. 

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Möglich sind zu, Beispiel drahtlose Sensoren oder Bluetooth 4.0 zur Überwachung von Temperaturen, Luftfeuchtigkeit, Türkontakte, Batteriestatus oder Füllständen.

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