- What is Condition monitoring?
- Benefits of Condition monitoring
- Use of Artificial Intelligence In Condition Monitoring
What do you mean by Condition Monitoring?
Condition monitoring is a maneuver to help a company maintain the condition of its machinery, as a part of Asset Management. Colloquially known as CM, Condition Monitoring is the process of determining on a yardstick of the condition in machinery like vibration, temperature, etc., and hence observe the same in order to identify a considerable change that acts as an indicator of a developing glitch in the machine. It is a kind of predictive maintenance.
Thus, Condition monitoring is, a plan of action that allows observing the existing condition of an asset, extracting information to decipher the actual health of the machinery, and whether any changes have taken place in its existing functioning. There are a number of techniques used for Condition monitoring.
Condition Monitoring is a salient component of any industrial maintenance strategy, with a plethora of uses in various sectors, namely oil and gas, transport, food and beverage, healthcare, local communities, water and wastewater, pulp and paper, etc. the analysis of asset metrics constitutes an important part of condition monitoring. Condition monitoring surfaces the major issues with the machine which can shorten its useful life, to the earliest, so that it can be resolved before any major failure develops.
Benefits of Condition Monitoring
Importance of Condition monitoring can be understood from the statement that it is a surveillance exercise, designed to recognize changes with respect to a regular course of action and send out signals when the changes surpass safety standards.
The primary objective of condition monitoring is to observe the changes in parameters of the health of the machinery and send prior signals so that necessary preventive measures can be taken in this regard. It is a mechanism of receiving real-time information about the functioning of the machine. This helps to give comprehensive exposure to the machine so that managers don't have to wait for any faulty indications so as to raise concerns.
A special type of condition-based monitoring systems has been introduced as a part of Artificial intelligence and machine learning. IoT based condition monitoring can aid the businesses to achieve many of the benefits by transitioning from reactive to preventive maintenance, which can save the business from major technical failures and thereby prove to cost-effective for the managers to maintain the machinery.
Condition Monitoring helps businesses to walk past the traditional maintenance procedure and have a modern proactive maintenance exercise with real-time implications. With the introduction of the latest versions of the software, the new Condition monitoring systems are being integrated with Computerized Maintenance Management Systems (CMMS), so as to further make it easier for companies to transcend from traditional to software equipped machine conservation procedures.
Minimized Unplanned Downtime
Most industries processes intend to reduce their overall downtime, not only due to abnormal direct costs associated with these unforeseen events, but also the disturbances that can be caused up to the production chain, having exponential business repercussions. A new set of the condition-based monitoring system scan, detect alterations in the machines, way before the actual failure, most of the times, providing maintenance staff with a considerable time window within inspection can be scheduled, and a comprehensive suggestive action can be curated, if necessary so as to rectify the problem. This leads to a substantial cost reduction, by avoiding some unwanted, unplanned downtime.
The condition of the machinery directly affects the level of output and production quality and also sometimes, costs a huge sum of money due to faulty machinery. Not only does that affect the potential profit margin of the business, but it can potentially disrupt delivery schedules and agreements with the clients. With condition monitoring, production and output can be maximized so that deadlines can be met and quality control is also monitored.
Increasing Lifespan of Machinery
Condition monitoring can help to enhance the lifespan of components of machinery and also its overall useful life of the machine. This can be a cost-effective measure. Studies have shown that fixing those faulty parts of a rotating machine can save up to 40% of the maintenance cost as well as boosting performance levels overall. Thus, condition monitoring can increase the overall productivity and also, in turn, ensure that the machinery remains effective for longer periods.
Use of Artificial Intelligence In Condition Monitoring
A number of attempts have been made to utilize the techniques of Artificial Intelligence for the purpose of diagnosis of the health of machinery and transformers. The most popular approach in this regard is the supervised Artificial Neutral Network (ANN). It is primarily used for detecting thermal and arcing faults of machinery. It can also be used for detection of cellulose degradation. Another AI approach for Condition Monitoring is Hybrid AI, which is known as the Spiking Neutral Network. The modern application of AI helps in building a decision support system for monitoring the condition of the machinery depending on SNN technique. It is best useful for classifying the tool wear level of the tool inserts, with the help of apparent weak features. So that corrective measures can be taken.
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