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{ "item_title" : "Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials", "item_author" : [" Kamalakanta Muduli", "Bikash Ranjan Moharana", "Steve Korakan Ales "], "item_description" : "The shift toward sustainable manufacturing is vital for addressing the pressing environmental challenges of the 21st century. By integrating sustainability principles, manufacturing processes can minimize resource consumption, reduce greenhouse gas emissions, and extend product lifecycles. This approach emphasizes designing for regeneration, using eco-friendly materials, and adopting advanced digital technologies like artificial intelligence (AI), Internet of Things (IoT), and blockchain to optimize production and promote environmental stewardship. Sustainable manufacturing not only mitigates ecological harm but also fosters innovation, enhances competitiveness, and supports long-term economic and societal resilience. Adopting such practices is essential for transitioning to a more responsible and sustainable global economy. Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials highlights how the application of computational intelligence techniques can promote resource and environmental sustainability in manufacturing systems and operational practices. It further examines how sustainable practices and advanced technologies in materials manufacturing can revolutionize production processes while minimizing environmental impact and promoting resource efficiency. Covering topics such as energy storage, nanoparticles, and biomaterials, this book is an excellent resource for computer scientists, business professionals, manufacturers, environmentalists, researchers, professionals, scholars, academicians, and more.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/836/937/9798369379745_b.jpg", "price_data" : { "retail_price" : "440.00", "online_price" : "440.00", "our_price" : "440.00", "club_price" : "440.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials|Kamalakanta Muduli

Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials

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Overview

The shift toward sustainable manufacturing is vital for addressing the pressing environmental challenges of the 21st century. By integrating sustainability principles, manufacturing processes can minimize resource consumption, reduce greenhouse gas emissions, and extend product lifecycles. This approach emphasizes designing for regeneration, using eco-friendly materials, and adopting advanced digital technologies like artificial intelligence (AI), Internet of Things (IoT), and blockchain to optimize production and promote environmental stewardship. Sustainable manufacturing not only mitigates ecological harm but also fosters innovation, enhances competitiveness, and supports long-term economic and societal resilience. Adopting such practices is essential for transitioning to a more responsible and sustainable global economy. Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials highlights how the application of computational intelligence techniques can promote resource and environmental sustainability in manufacturing systems and operational practices. It further examines how sustainable practices and advanced technologies in materials manufacturing can revolutionize production processes while minimizing environmental impact and promoting resource efficiency. Covering topics such as energy storage, nanoparticles, and biomaterials, this book is an excellent resource for computer scientists, business professionals, manufacturers, environmentalists, researchers, professionals, scholars, academicians, and more.

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Details

  • ISBN-13: 9798369379745
  • ISBN-10: 9798369379745
  • Publisher: IGI Global
  • Publish Date: April 2025
  • Dimensions: 11 x 8.5 x 1.44 inches
  • Shipping Weight: 4 pounds
  • Page Count: 700

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