The maintenance concept is defined by the standard EN 13306, as follows: the combination of all technical, administrative, and managerial actions performed during the life cycle of an element to maintain or restore the conditions under which it can perform the required function. In simpler terms, maintenance is a formal strategy used by manufacturers to keep their machines and equipment in good condition.
To perform maintenance operations, a maintenance management plan is needed. Maintenance management is defined as the sum of all the management activities that determine the maintenance objectives, strategies, and responsibilities and their implementation by means of maintenance planning, maintenance control, and improvement of maintenance activities.
There are three main types of maintenance:
- Reactive Maintenance or Run-to-failure (R2F) strategy: in this strategy, the assets are used until they break down and then repaired or replaced with new ones.
- Preventive maintenance (PvM) – This type of maintenance is performed proactively to prevent failures, and it includes tasks like regular inspections, cleaning, lubrication, and adjustments. This reduces the likelihood of unexpected equipment downtime.
- Predictive Maintenance (PdM) – This is an advanced type of maintenance that uses monitoring and diagnostic tools to predict equipment failure before it occurs. Predictive maintenance aims to detect potential problems early, allowing for proactive maintenance, minimizing unplanned downtime, and improving equipment reliability. Using artificial intelligence and machine learning for predictive maintenance seems the most cost-effective solution.
Predictive maintenance is a critical aspect of Industry 4.0, going beyond reactive and preventive Maintenance. It leverages real-time and historical data to detect anomalies and predict the future health of equipment, allowing for proactive maintenance plans to mitigate potential failure modes and minimize their impact. Predictive maintenance capitalizes on the abundance of data in the enterprise ecosystem to optimize equipment reliability and reduce downtime, making it a crucial strategy in Industry 4.0
Implementing Predictive Maintenance techniques and technologies provides manufacturing companies with a significant competitive advantage, resulting in several benefits. By leveraging predictive maintenance, they can extend the lifespan of the equipment, minimize maintenance costs, reduce downtimes, increase knowledge about their assets, enhance plant reliability, optimize maintenance resource utilization, achieve a zero-defects strategy, and efficiently plan their processes. These benefits enable manufacturing companies to remain competitive.
There are many advantages to using predictive maintenance, but some of the most notable benefits include:
- Higher productivity
- Asset availability
- Less unplanned downtime
- More effective maintenance
- Lower costs in case of breakdowns
- Lower costs for maintenance
- Safer working environment
- Longer equipment life
Predictive maintenance:
- Increases productivity by 25%
- Lowers the costs of equipment maintenance by 25%
- Increases machine uptime even by up to 20%
Additionally, the following objectives can be fulfilled:
- Total cost reduction (11%),
- risk reduction associated with safety, health, environment, and quality (SHEQ) (8%),
- extending the lifetime of assets (7%)
- improving customer satisfaction (12%).