the project represents a first experience of integrating artificial intelligence technology in Sonatrach. Faced with the growing importance of maintenance in the industrial sector, we have integrated this technology in maintenance domain.
One of the main benefits of AI for maintenance is its ability to analyze big data in real time, connected sensors and monitoring systems(SCADA) to have continuous data collection on equipment, and AI uses this data to identify anomalies and predict equipement failure.
the algorithms we have developed are based on machine learning and deep learning models. The resulting prediction result allows engineers to plan maintenance before critical failures occur.
We have also developed AI models for each equipment failure mode. These models are based on the expertise of engineers who have identified the parameters to be predicted to predict different equipment failure.
With these predictive models we can:
* Reduce costs associated with frequent maintenance activities.
* Prevent production losses due to failure equipment.
* Anticipate costly equipment failure.
*Adopt a new maintenance schedule based on the recommendations of the intelligent AI model instead of adhere to a predefined schedule.

fatimazohra.bennani@sonatrach.dz

• Africa

the artificial intelligence project for predictive maintenance is sustainable in several ways:
1- Waste reduction: by preventing unexpected breakdowns nd optimizing resource utilization, AI-based predictive maintenance helps reduce wast generated from premature equipement replacements. this contributes to a more sustainable use of resources and preserves the envoronement.
2- Energy saving: AI enables optimization of maintenanceschedules, resulting in energgy saving by avoiding unplanned downtime.
3-extended equipement lifespan: ai-based predictive maintenance detects and addresses potential issues before they compromise performance or equipement lifespan. by optimizing performance and preventingfailures, Ai helps extend the useful lifespan of equipement, reducing the need for frequent remplacements
4- improved safety: by detecting potential safety issues before they become critical, AI in predictive maintenance improves worker safety by reducing risks associated with equipement failures. this promotes a safe and sustainable working environnement.
5- ressource optimization: AI in predictive maintenace helps optimize the use of ressourcesuch as spare parts, materials, and technical skils. thise result in more efficient ressource utilisation, cost reduction, and minimal environnemental footprint.
in summary, ours pridictive model is sustainable as it contributes to waste reduction, energy saving, extended equipement lifespan, improved safety, and ressource optimization

Predictive maintenance based on AI promotes the values of SMSI in the following ways: 1. Confidentiality: AI-driven predictive maintenance requires access to sensitive data about equipment and network. A company that adheres to SMSI values ensures that this data is adequately protected by implementing appropriate security measures like encryption and access controls. 2. Integrity: Predictive maintenance based on AI relies on accurate and reliable data to provide precise predictions. A company that upholds the values of SMSI commits to ensuring the integrity of data by implementing controls to prevent data alterations or falsifications. 3. Availability: AI used in predictive maintenance relies on continuous availability of real-time data. A company valuing SMSI principles ensures that systems and infrastructures necessary for data collection and analysis are resilient and available at all times. 4. Risk Management: AI-driven predictive maintenance helps identify potential failures before they occur, reducing risks of major incidents or breakdowns. A company aligning with SMSI values commits to assessing and proactively managing risks by implementing appropriate measures to prevent failures or cyber attacks. By integrating these core principles of confidentiality, integrity, availability, and risk management into AI-based predictive maintenance, a company can promote the values of SMSI and ensure the security and reliability of its operations.