feat: phd topic revisited

_posts/-_ideas/2030-01-01-new_articles_topics.md

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 There are several interesting article topics you can explore under the umbrella of **Predictive Maintenance**, especially focusing on the role of **data science**, **big data**, and **machine learning**. Here’s a list of potential articles you could write:
 
-### 1. Introduction to Predictive Maintenance
-   - **Overview**: Explain what predictive maintenance (PdM) is and how it differs from preventive and reactive maintenance. 
-   - **Focus**: Basic techniques and traditional approaches to predictive maintenance, including time-based and condition-based maintenance strategies.
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@@ -36,9 +34,7 @@ There are several interesting article topics you can explore under the umbrella
    - **Overview**: Provide a practical guide to building a predictive maintenance model using Python libraries like Pandas, Scikit-learn, and TensorFlow.
    - **Focus**: Walkthrough on collecting data, feature engineering, training models, and deploying them in a real-world industrial context.
 
-### 9. The Impact of Predictive Maintenance on Operational Efficiency
-   - **Overview**: Discuss how implementing PdM reduces downtime, optimizes maintenance costs, and improves overall equipment effectiveness (OEE).
-   - **Focus**: Include case studies or industry statistics showing measurable improvements from companies using predictive maintenance.
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 ### 10. Challenges in Implementing Predictive Maintenance
    - **Overview**: Highlight the challenges companies face when adopting PdM, such as data quality issues, organizational resistance, and the high cost of implementing IoT infrastructure.
@@ -48,9 +44,7 @@ There are several interesting article topics you can explore under the umbrella
    - **Overview**: Explain the role of cloud computing for storing, processing, and analyzing large-scale sensor data in PdM systems.
    - **Focus**: Discuss how edge analytics processes data closer to the source (e.g., on-site machinery) for faster, real-time predictions.
 
-### 12. The Role of Natural Language Processing (NLP) in Predictive Maintenance
-   - **Overview**: Explore how NLP can be used to process unstructured data such as maintenance logs, repair manuals, and service records for predictive insights.
-   - **Focus**: Techniques to extract useful information from text-based data to complement sensor-based predictive maintenance.
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 ### 13. Case Studies: How Industry Leaders are Using Predictive Maintenance
    - **Overview**: Showcase case studies from various industries (manufacturing, transportation, energy) where PdM has led to significant operational gains.