Electricity distribution infrastructure is the foundation upon which energy is delivered safely to businesses and residents all over the world. This critical infrastructure is operational around the clock and any interruption, be it just a few seconds, may cause huge losses. That is why it is extremely important to keep the distribution network in balance and good health.
For the industry, especially, uninterrupted operation is vital to the business. Uninterrupted by the distribution network, but also from the asset side inside the factory. This means the maintenance process should be meticulous. To avoid unplanned downtime, factory managers have used time-tested maintenance strategies. Today, with the help of an expert staff, related technologies enable innovative condition-based surveillance services that continuously monitor the health of assets and provide extended notification if an asset exhibits unusual behavior. Potential problems are then resolved long before there is a safety risk or costly impact on the plant’s operation.
Throughout the years, depending on technology and organizational developments, several types of maintenance processes have been widely accepted.
- Reactive (run-to-failure) maintenance – the worst-case scenario is when plants implement this type of maintenance. It can cause huge losses and should be completely avoided.
- Preventive maintenance – scheduled assets and infrastructure check-ups.
- Condition-based maintenance – a proactive approach, where a problem is detected early on in the failure process.
- Predictive maintenance – this is a sort of condition-based maintenance with added analytics functionalities.
It is common knowledge what scheduled asset check-ups is because this is really the most common type of maintenance process. However, the other types of maintenance have many more benefits like tackling the constantly rising labor and energy costs. Condition-based maintenance refers to any proactive service performed on a critical asset after detecting a sign of poor machine health or impending failure. Rather than servicing equipment regularly or after a breakdown, a condition-based maintenance strategy relies on evidence discovered through visible inspection, sensor alerts, or testing to proceed with service.
The main advantage of condition-based maintenance is that teams only perform condition-based maintenance services when necessary. While maintenance teams make every effort to estimate preventive maintenance service schedules as accurately as possible, they may still perform unnecessary maintenance activities because they fail to consider factors such as lack of usage, ideal operating environment, or well-constructed components.
Preventive maintenance schedules, on the other hand, may arrive too late after an asset has failed because they cannot account for early signs of deterioration. When compared to preventive maintenance, condition-based maintenance is superior because teams only perform service when evidence supports it, resulting in cost savings in spare parts and labor and reduced unplanned downtime.
Condition-based maintenance can only be triggered by signs of potential failure or evidence of decreased performance. Condition-based monitoring refers to the process of measuring, testing, and identifying the current state of an asset to find these triggers.
Various warning signs will appear as machine health deteriorates to functional failure. The goal of condition monitoring is to detect these signs as early as possible to reduce maintenance costs and increase the time it takes to resolve the problem.
For detecting early signs of failure, there are two types of condition monitoring techniques: interval and continuous. Each category has advantages, and they are frequently used in tandem within the same organization.
- Interval monitoring (spot testing)
This type of condition monitoring entails performing spot tests at regular intervals. A maintenance professional is needed to manually inspect the asset and schedule service if it meets certain criteria. These spot tests can be as simple as a visual inspection or as complex as using specialized testing equipment to uncover detailed data.
- Continuous monitoring (sensor alerts)
This type of condition monitoring employs sensors that continuously monitor specific variables and send alerts when they exceed a predetermined threshold. The benefit of continuous monitoring is that it constantly assesses the condition, alerting the maintenance team as soon as a symptom appears.
Predictive maintenance is another common proactive maintenance strategy. In many ways, it overlaps with condition-based monitoring and condition-based monitoring, so it’s worth investigating the similarities and differences. By combining the accuracy of conditional data with the predictability and consistency of preventive maintenance schedules, predictive maintenance combines the benefits of both condition-based maintenance and preventive maintenance. Predictive maintenance can predict how long an asset will last before failing and allow your team to schedule maintenance work at a time that is convenient for your operation.
The design of a safe and reliable electrical power system relies heavily on medium and low voltage switchgear. This equipment protects critical power systems from over currents and serves as an isolation point for electrical equipment maintenance. Switchgear is critical to the overall performance of the power system and must be kept in peak condition.
Slow switchgear operation can accelerate the aging of other critical assets like power transformers. Any important data failure will result in unplanned outages, revenue loss, and potential worker safety concerns. Power transformers are commonly regarded as ideal candidates for condition-based monitoring due to their high initial investment. Medium voltage switchgear and circuit breakers are by far the most common cause of substation events, and switchgear failure is frequently identified as the root cause of transformer and other equipment failure.
An electronic monitoring system, which constantly observes the temperature and humid levels of the devices in the electrical infrastructure, will be able to detect early signs of wear and aging. This allows maintenance teams to react before any unanticipated system failures occur.
According to the US Department of Energy, such proactive maintenance approach can save between 8% and 12% compared to conventional scheduled maintenance and roughly 40% compared to run-to-failure maintenance process.
ARISTA EIM (Electrical Infrastructure Monitoring) is a cutting-edge technology that allows you to remotely and in real-time monitor power supplies and control electrical switchboards. The system measures electrical parameters (voltage, current, power, and consumption), reads signals from various digital sensors (for smoke, humidity, temperature, door position buttons, and so on), monitors the presence of voltage at circuit control points, and considers the states of infrastructure elements. It is intended to assist small and medium-sized businesses in their digital transformation to become more efficient and up-to-date.
The ARISTA EIM system rapidly locates and identifies emergency conditions, detects parameter deviations, and attempts infrastructure manipulation. Aids in making informed decisions, thereby optimizing processes and maintenance costs.
Unlike other expensive solutions, ARISTA EIM does not require a large upfront investment. Nonetheless, it can take maintenance operations to the next level of digitalization and automation.
The system allows for the digitalization and visualization of the states and parameters of the infrastructure’s electrical circuit via a web interface, as well as integration with other systems.
The ultimate goal is to continuously monitor the electrical parameters and thus protect the distribution transformer or power transformer from burning due to constraints such as overload, over temperature, and input high voltage.
Only through the analysis of information collected in real time from the equipment can maintenance be established based on actual conditions rather than time intervals. This analysis allows you to extend the maintenance cycle and reduce costs.
For more information, please contact our team.