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{ "item_title" : "Mixture of Human and Machine Intelligence in Digital Manufacturing", "item_author" : [" Yang Lu", "Ming Zhang", "Ziwei Wang "], "item_description" : "This Reprint examines the evolving role of human-machine interfaces (HMI) within the context of Industry 4.0 and digital manufacturing, where human and machine intelligence are increasingly integrated to enhance design, production, and decision-making. It highlights research on advanced interaction technologies that move beyond traditional tools toward dynamic, collaborative relationships between humans and autonomous systems. Topics include novel design patterns in perception, control, and arbitration; the application of human expertise in machine decision-making; and the use of sensory data for informed, adaptive manufacturing processes. By bringing together contributions from both academic and industrial perspectives, the Reprint provides a comprehensive view of the opportunities, challenges, and future directions for human-machine collaboration in digital manufacturing.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/72/585/063/3725850631_b.jpg", "price_data" : { "retail_price" : "94.77", "online_price" : "94.77", "our_price" : "94.77", "club_price" : "94.77", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Mixture of Human and Machine Intelligence in Digital Manufacturing|Yang Lu

Mixture of Human and Machine Intelligence in Digital Manufacturing

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Overview

This Reprint examines the evolving role of human-machine interfaces (HMI) within the context of Industry 4.0 and digital manufacturing, where human and machine intelligence are increasingly integrated to enhance design, production, and decision-making. It highlights research on advanced interaction technologies that move beyond traditional tools toward dynamic, collaborative relationships between humans and autonomous systems. Topics include novel design patterns in perception, control, and arbitration; the application of human expertise in machine decision-making; and the use of sensory data for informed, adaptive manufacturing processes. By bringing together contributions from both academic and industrial perspectives, the Reprint provides a comprehensive view of the opportunities, challenges, and future directions for human-machine collaboration in digital manufacturing.

Details

  • ISBN-13: 9783725850631
  • ISBN-10: 3725850631
  • Publisher: Mdpi AG
  • Publish Date: September 2025
  • Dimensions: 9.61 x 6.69 x 0.75 inches
  • Shipping Weight: 1.53 pounds
  • Page Count: 228

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