Verwandte Artikel zu Lean Six Sigma & Machine Learning for Optimization:...
Lean Six Sigma & Machine Learning for Optimization: Predicting Heavy Oil Viscosity with Machine Learning to Optimize Steam Injection and Reduce Energy Waste - Softcover
Inhaltsangabe
Heavy oil exploitation presents significant energy and operational challenges due to high viscosity, which directly impacts the efficiency of thermal recovery processes. In Madagascar's Tsimiroro field, accurate viscosity prediction is critical for optimizing steam injection and mitigating excessive energy waste. This study adopts the Lean Six Sigma methodology as a structured framework to eliminate operational Mudas (wastes) related to steam overconsumption. A machine learning-based predictive framework was developed, comparing six distinct architectures: Linear Regression, Second-Degree Polynomial Regression, Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest, and XGBoost. The results demonstrate that while the polynomial model achieves high statistical precision (R² = 0.995, RMSE = 154.62 cSt), the Artificial Neural Network architecture delivers superior robustness (R² = 1.000, RMSE = 154.62 cSt) in capturing complex non-linear thermal behaviors. XGBoost and Random Forest show competitive performance with R² values of 0.90 and 0.91 respectively, while SVM exhibits the highest prediction errors (RMSE ¿ 780 cSt).
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Über die Autorin bzw. den Autor
I leverage Lean principles, TRIZ, and advanced modeling to deliver innovative and sustainable solutions for industrial and energy systems. As a researcher and lecturer, I bridge the gap between scientific theory and practical efficiency to solve complex engineering challenges.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Suchergebnisse für Lean Six Sigma & Machine Learning for Optimization:...
Beispielbild für diese ISBN
Lean Six Sigma & Machine Learning for Optimization
Print-on-DemandAnbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Englisch. Bestandsnummer des Verkäufers 9786209925986
Neu kaufen
EUR 48,90
EUR 23,00 Versand
Versand von Deutschland nach USA
Versand von Deutschland nach USA
Anzahl: 2 verfügbar
Foto des Verkäufers
Lean Six Sigma & Machine Learning for Optimization : Predicting Heavy Oil Viscosity with Machine Learning to Optimize Steam Injection and Reduce Energy Waste
Print-on-DemandAnbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Heavy oil exploitation presents significant energy and operational challenges due to high viscosity, which directly impacts the efficiency of thermal recovery processes. In Madagascar's Tsimiroro field, accurate viscosity prediction is critical for optimizing steam injection and mitigating excessive energy waste. This study adopts the Lean Six Sigma methodology as a structured framework to eliminate operational Mudas (wastes) related to steam overconsumption. A machine learning-based predictive framework was developed, comparing six distinct architectures: Linear Regression, Second-Degree Polynomial Regression, Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest, and XGBoost. The results demonstrate that while the polynomial model achieves high statistical precision (R = 0.995, RMSE = 154.62 cSt), the Artificial Neural Network architecture delivers superior robustness (R = 1.000, RMSE = 154.62 cSt) in capturing complex non-linear thermal behaviors. XGBoost and Random Forest show competitive performance with R values of 0.90 and 0.91 respectively, while SVM exhibits the highest prediction errors (RMSE = 780 cSt). Bestandsnummer des Verkäufers 9786209925986
Neu kaufen
EUR 51,60
EUR 35,00 Versand
Versand von Deutschland nach USA
Versand von Deutschland nach USA
Anzahl: 1 verfügbar
Beispielbild für diese ISBN
Lean Six Sigma & Machine Learning for Optimization
Print-on-DemandAnbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware 52 pp. Englisch. Bestandsnummer des Verkäufers 9786209925986
Neu kaufen
EUR 48,90
EUR 60,00 Versand
Versand von Deutschland nach USA
Versand von Deutschland nach USA
Anzahl: 1 verfügbar
Foto des Verkäufers
Lean Six Sigma & Machine Learning for Optimization | Predicting Heavy Oil Viscosity with Machine Learning to Optimize Steam Injection and Reduce Energy Waste
Anbieter: preigu, Osnabrück, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Lean Six Sigma & Machine Learning for Optimization | Predicting Heavy Oil Viscosity with Machine Learning to Optimize Steam Injection and Reduce Energy Waste | Rakotozandry Ignace (u. a.) | Taschenbuch | Englisch | 2026 | GlobeEdit | EAN 9786209925986 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 135570029
Neu kaufen
EUR 43,30
EUR 70,00 Versand
Versand von Deutschland nach USA
Versand von Deutschland nach USA
Anzahl: 5 verfügbar