Industrial Glossary

Visit Predictive Maintenance (PdM) is the most advanced maintenance strategy. Its aim is to determine the actual state of a piece of equipment in operation, in order to predict future failure and plan the repair or replacement intervention at the optimum time. This is in contrast to corrective maintenance (repairing after a breakdown) and preventive maintenance (repairing at fixed intervals, whether necessary or not).

In-depth definition : Predictive Maintenance is a technological approach based on the continuous collection and analysis of physical data (IoT), d’Artificial Intelligence (AI) and Machine Learning. Sophisticated sensors (vibration, temperature, ultrasound, oil analysis, power consumption) are installed on critical equipment to monitor their “weak signals”. Algorithms for Machine Learning analyze these Big Data The system alerts the maintenance team, not that the machine is going to fail, but that it has a high probability of failure within a given time window. The system alerts the maintenance team, not that the machine is going to fail, but that it has a high probability of failure within a given time window (e.g. within the next 14 days).

The benefits of PdM in Operational Excellence

The adoption of Predictive Maintenance is a key factor in the company's success.’Operational Excellence and a major cost-cutting lever for SMEs:

A. Maximizing SRR (Synthetic Efficiency Ratio)

• Eliminating Unplanned Stops : This is the most visible benefit. Unplanned breakdowns are the main cause of poor machine performance, especially for equipment identified as Bottlenecks. By transforming unplanned breakdowns into planned stoppages, PdM maximizes production time.
• Intervention optimization : Maintenance operations are carried out just before failure, minimizing overall line downtime.

B. Drastic reduction in maintenance costs

• Avoid over-maintenance: Traditional preventive maintenance requires the replacement of parts that are still in good condition, which is wasteful (Muda). PdM extends the useful life of components, allowing them to be replaced only when they reach the end of their life, reducing spare parts costs and unnecessary labor.
• Secondary damage cost reduction : A sudden breakdown can cause cascading damage to other parts of the machine. Early intervention is limited to targeted repair of the failed component, reducing the total cost of repair.

C. Improving quality and workflow

• Constant quality : A machine in a state of imminent failure (e.g. worn bearings causing vibrations) can produce parts out of specification. The PdM ensures that the machine maintains optimal operating conditions, guaranteeing the highest level of safety. Quality of the Series Production and compliance with Manufacturing file.
• Reliability of the Pulled Flow : The systems Pulled Flow are very sensitive to machine stoppages. The PdM is a necessary condition to guarantee the fluidity of the flow and the respect of the schedule. Takt Time required.

Predictive Maintenance at the Heart of Industrial Digitization

PdM is the application par excellence of the technologies of the’Industry 4.0 :

1. IoT : It provides the raw material, i.e. real-time physical data.
2. Machine Learning : It is the technology that learns to interpret weak signals to generate predictions.
3. The Digital Twin: The PdM can be integrated into the machine's Digital Twin to simulate the impact of the failure on the overall plant system and optimize shutdown planning.
4. MES: The maintenance system (CMMS) is directly interfaced with the MES (Manufacturing Execution System) to transform predictive alerts into prioritized work orders.

Challenges and support

Implementing PdM requires expertise in Industrial Engineering and data science. The main challenge is to move from simple data collection to creation of a predictive model for customer-specific equipment.

The engineering consultant assists his customers in :

• Defining criticality equipment (where to install the sensors).
• Selecting the right technology (vibrometry, thermography, etc.) for each use case.
• Integrating systems data collection (IoT) to management software (CMMS/MES).
• Training teams reading AI diagnostics and using predictions to plan maintenance operations.

Predictive Maintenance is an investment that transforms maintenance from a cost center into a performance center to reinforce the company's sustainable competitiveness.