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Artificial Intelligence in Production Engineering and Management

Om Artificial Intelligence in Production Engineering and Management

Artificial intelligence (AI) plays a crucial role in production engineering and management, revolutionizing operation optimization, data analysis, forecasting, and task automation. In production engineering, AI contributes to operational efficiency by identifying patterns, predicting failures, and optimizing supply chains. In management, it offers predictive and prescriptive insights, allowing quick adaptations to changes in market conditions. However, it is essential to address ethical challenges, such as data security and workforce impacts, to ensure responsible and sustainable implementation of AI in these contexts. Among the different topics covered in Artificial Intelligence in Production Engineering and Management, the reader can find, among others, living under AI; machine learning and large language models; AI and people management; nudging financial behavior in AI; the European Union narrative on AI; multidimensional transhuman influence; and AI, emotional intelligence, and ethics. This topical book will be of great value for those working and researching in the production engineering and management fields who are seeking to understand and capitalize on the revolutionary wave that artificial intelligence brings to modern engineering and management.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9780128194713
  • Bindende:
  • Paperback
  • Sider:
  • 252
  • Utgitt:
  • 1. juli 2024
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 8. desember 2024

Beskrivelse av Artificial Intelligence in Production Engineering and Management

Artificial intelligence (AI) plays a crucial role in production engineering and management, revolutionizing operation optimization, data analysis, forecasting, and task automation. In production engineering, AI contributes to operational efficiency by identifying patterns, predicting failures, and optimizing supply chains. In management, it offers predictive and prescriptive insights, allowing quick adaptations to changes in market conditions. However, it is essential to address ethical challenges, such as data security and workforce impacts, to ensure responsible and sustainable implementation of AI in these contexts. Among the different topics covered in Artificial Intelligence in Production Engineering and Management, the reader can find, among others, living under AI; machine learning and large language models; AI and people management; nudging financial behavior in AI; the European Union narrative on AI; multidimensional transhuman influence; and AI, emotional intelligence, and ethics. This topical book will be of great value for those working and researching in the production engineering and management fields who are seeking to understand and capitalize on the revolutionary wave that artificial intelligence brings to modern engineering and management.

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