## 2 State of the Art
### Artificial Intelligence in Science and Industry
This improves the overall resilience of a supply chain. **Reputation and Customer Satisfaction. ** Sustainable practices including reliable delivery services due to effective predictive maintenance enhance a company's reputation and customer satisfaction. The combination of AI methods for predictive maintenance has applications that extend far beyond supply chain management. These principles that leverage data and AI algorithms to anticipate and prevent equipment failures are adaptable to a wide range of industries and sectors. For example, in manufacturing, AI-based predictive maintenance can enhance equipment reliability, reduce downtime, and optimize resource utilization. In healthcare, it can ensure the reliable operation of medical devices, minimizing equipment downtime and improving patient care. The energy sector can benefit from improved power plant performance and grid management, while aviation can achieve enhanced safety and aircraft availability. However, the adoption of AI-based predictive maintenance is not without its challenges. It often involves data integration, security and privacy concerns, and compliance with industry-specific regulations. Nevertheless, the potential benefits, including increased reliability, cost savings, and improved efficiency, make it a promising approach for various industries as technology continues to advance. The implementation of predictive maintenance with AI in a supply chain offers significant benefits but also comes with the following limitations and potential risks that need to be carefully addressed to ensure successful adoption and integration:Data Quality and Availability.Predictive maintenance relies on high-quality and timely data from sensors and equipment. If the data are inaccurate or unavailable, the effectiveness of the AI models can be compromised. Cost of Implementation.The upfront cost of implementing AI-driven predictive maintenance systems, including sensors, data infrastructure, and AI software, can be substantial. Smaller businesses may find it challenging to make this initial investment. Integration Complexity.Integrating AI systems with existing supply chain management and maintenance systems can be complex. Compatibility and data sharing between systems may require significant effort and resources. Skill and Training.Organizations need skilled personnel to develop, operate, and maintain AI-based predictive maintenance systems. A shortage of talent and the need for continuous training can be obstacles. Maintenance of AI Systems.AI models require continuous maintenance and updates to remain effective. Failure to maintain AI systems can lead to performance degradation. False Positives/Negatives.Overreliance on AI predictions may lead to false alarms or missed maintenance opportunities. Organizations must carefully validate AI-generated alerts. Security Concerns.AI systems can be vulnerable to cyberattacks. Protecting sensitive maintenance data and ensuring the security of AI systems is essential. Privacy Issues.Collecting and analyzing data related to equipment and maintenance may raise privacy concerns, especially when personal data are involved such as employee information. Regulatory Compliance.In some industries, predictive maintenance systems must comply with specific regulations and standards. Failure to do so can result in legal and regulatory penalties. Dependency on Technology.Overreliance on AI systems can make organizations vulnerable to disruptions if the technology fails or experiences downtime. AI-based predictive maintenance holds great promise for industries, offering benefits such as reduced downtime, increased productivity, and enhanced equipment reliability. Research efforts should focus on refining AI algorithms, data analytics, and sensor technologies to drive further advancements. This technology also aligns with sustainability goals by conserving energy and reducing environmental impact, making it a win-win situation for both industry and research.