Predictive Maintenance in IT?
Predictive maintenance refers to predictive maintenance. This is familiar from industry and production halls. Thanks to the Internet of Things (IoT), digitization and the progressive merging of corporate divisions, predictive maintenance has also found its way into IT.
For example, there are now predictive software or hardware updates here. Essentially, this involves condition-based maintenance. In order to be able to apply this in IT, a reliable database is needed that can be evaluated accordingly.
What does predictive maintenance mean?
Predictive maintenance refers to the implementation of data-driven and proactive maintenance methods that analyze the actual condition of equipment and predict the right time for maintenance work. It is a technique that uses data analysis tools to detect and predict anomalies and defects in IT assets and processes at an early stage so that they can be fixed before failure occurs.
The goal of predictive maintenance is to perform maintenance in a timely manner and as cost-effectively as possible so that the life of an equipment can be maximized. Predictive maintenance solutions collect and store data, transform it, monitor and evaluate the condition of an equipment or asset, make predictions and support decisions.
The benefits of predictive maintenance
Predictive maintenance can optimize the maintenance and reliability of an operation. Unplanned downtime in plants can be reduced, unnecessary maintenance costs can be avoided and the lifetime of a plant can be extended. As the solution collects data about a machine, it can also help improve performance.
Predictive maintenance is a cost-effective alternative in the long term, because complex IT failures can be avoided. This saves costs for maintenance tools and services. Admins and technicians are relieved and have more time, for example, for the further development of their areas.
The benefits at a glance:
- Minimization of unexpected failures
- Utilization of the maximum uptime of devices, hardware and software
- Reduction of IT infrastructure costs
- Increased productivity
- Increased security
- Rationalization of maintenance expenses
- Little to no unplanned downtime
- Increase in ROI (return on investment).
- The disadvantages of Predictive Maintenance
When Predictive Maintenance is newly introduced to a business, it can be costly in the beginning. However, over time, the benefits to the business come into play, significantly outweighing the high initial costs.
Other disadvantages include:
- Large amount of time and planning required to implement predictive maintenance.
- Misinterpretation of data can lead to incorrect maintenance requests
- High costs
- Ignoring of contextual information by predictive analysis
- Eliminating the need for physical maintenance of assets
- Time intensive implementation
- Preventive and predictive maintenance - a comparison
Preventive Maintenance is used only when needed, reducing labor and material costs. Predictive Maintenance is scheduled as needed, based on the real-time condition of an asset. Preventive Maintenance can result in over-maintenance and is labor intensive to perform. It is better than reactive maintenance and easier to implement.
The main difference between Preventive and Predictive Maintenance is based on data analysis. Preventive maintenance is based on historical data and averages, while predictive maintenance focuses on the current state.
The term predictive maintenance, which originated in the production halls, has also found its way into the IT sector as a result of the IoT and digitization. Here, it refers to the predictive maintenance of IT systems. It is a fusion of business processes and the areas of production, IT and the Internet. Data is collected and analyzed to determine whether and when systems are likely to require maintenance. This can then be carried out specifically when required.
Beitragsfoto: Shutterstock, WOTAN Monitoring, GH-Informatik GmbH