Condition Monitoring and Its Role in Predictive Maintenance

Industrial equipment is supposed to have a long life span. Unexpected failures have negative effects on the production, costs and pose safety hazards. In order to prevent these issues, condition monitoring and predictive maintenance are some of the maintenance planning adopted by many organizations.

Condition monitoring is aimed at monitoring the real health of machines in operation. That information is used in predictive maintenance to determine the time at which maintenance is required. These approaches are used jointly to enable organizations to keep equipment under a controlled and efficient manner.

What Condition Monitoring Requires

Condition monitoring ( https://artesis.com/condition-monitoring/ ) refers to measurement and assessment of equipment operating condition with time. It makes use of the data which includes the vibration levels, temperature, electric signals and pressure readings to identify performance changes. These measurements depict whether a machine is performing as usual or it is getting worn.

Condition monitoring is not intended to determine the date of failure itself, just to give information on equipment health reliably. By identification of the changes at an early stage, the maintenance teams are given time to investigate and act before a failure may set in. In this manner, it lowers the use of standard inspection and emergency repair.

Predictive Maintenance Defined

Predictive maintenance applies condition monitoring information to approximate when equipment issues are likely to occur and impact performance or lead to failure. Maintenance activities are scheduled according to the actual state of assets, instead of having a pre-determined schedule of maintenance.

The approach will enable maintenance crew to intervene when it is evident that a component is wearing out or its performance is deteriorating. Predictive maintenance assists in preventing avoidable maintenance at the cost of decreasing the likelihood of being caught unawares.

The Support of Condition Monitoring to Predictive maintenance

Predictive maintenance needs quality and consistent condition monitoring data. It is not easy to evaluate trends or how the behavior of the equipment is evolving over time without the reliable measurements.

As an example, when condition monitoring indicates a gradual rise in motor temperature, the data can be applied to assess the possible reasons, i.e. electrical imbalance or mechanical friction. The predictive maintenance analysis can then spell out the necessity of corrective action in the first instance or it can be planned in the next instance.

Condition monitoring presents the facts, whereas predictive maintenance makes use of them to make decisions.

Real-life Advantages of Operations

There are obvious benefits of applying condition monitoring and predictive maintenance simultaneously. Equipment malfunctions are monitored sooner hence, the possibility of unexpected closure is minimized. The maintenance repairs can be arranged within the normal operating breaks, which will reduce the losses in production.

Costs can be controlled more easily also. Orders of spare parts can be made and maintenance labor arranged easily. In the long run, equipment will be durable since issues are met before they become very harmful.

Safety improves as well. Constant monitoring of machines can reduce chances of failure that expose workers to dangerous situations.

Industries of Use

Most industries such as manufacturing, power generation, water treatment and transportation use condition monitoring and predictive maintenance ( https://artesis.com/predictive-maintenance/ ). Vibration and electrical signals monitoring used in rotating equipment (e.g. pumps and motors) allow the detection of mechanical and electrical problems at the early stage. Predictive maintenance contributes to reliability in critical infrastructure to prevent uninterrupted service.

The approaches are also useful in the contexts where the malfunction of equipment may have significant operational or economic consequences.

Conclusion

Condition-based maintenance and predictive maintenance offers a viable and sound strategy in maintenance of equipment. Understanding the behavior of machines under normal conditions enables organizations to make sound decisions of the maintainability as per the actual condition and not by assumption.

Both condition monitoring and predictive maintenance assist in reducing the downtime, managing the costs, and enhancing the quality of equipment. They are not valuable in elaborate terms, but in routine measurement, due analysis and prompt action.

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