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Product Lifecycle Management. PLM in the Age of Model-Based Engineering in Industry: 22nd IFIP WG 5.1 International Conference, PLM 2025, Seville, Spa [Hardcover]

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  • Category: Books (Computers)
  • ISBN-10:  3032096995
  • ISBN-10:  3032096995
  • ISBN-13:  9783032096999
  • ISBN-13:  9783032096999
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  400
  • Pages:  400
  • Binding:  Hardcover
  • Binding:  Hardcover
  • SKU:  3032096995-11-SPRI
  • SKU:  3032096995-11-SPRI
  • Item ID: 106901031
  • List Price: $199.99
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This 2-volume set constitutes the post proceedings of the 22nd IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2025, which took place in Seville, Spain, July 2025.

The 79 full papers presented in this volume were carefully reviewed and selected from 143 submissions. 

The papers are organized in the following topical sections:

Part I: Digital Twin and Smart Systems; AI and Data-Driven Innovation; Sustainable and Circular Product Lifecycle.

Part II: Model-Based Engineering (MBE) and System Engineering; Organizational Transformation and Strategy; Interoperability and Integration Technologies; Human-Centric and Educational Innovation.

.- Digital Twin and Smart Systems.

.- Expanding the Data Usability for Digital Product Twins.

.- Scenario-Driven Engineering Data Integration for the Generation of Digital Product Twins.

.- Integration of Digital Twins with Product Lifecycle Management using Digital Threads.

.- A Framework Proposal for Fast-Improved Learning by Virtual Simulations in the Digital-Twin Context.

.- A Digital Twin Framework for Enhanced Robot Control through Data Exchange Protocols.

.- DIGITAL AERO. Integrated system for industrial product manufacturing.

.- A No-Code Digital Thread Graph Prototype: Runtime Configurable, Cloud-Native, and AI-Driven.

.- Scalability Matters: Benchmarking Graph Databases for High-Performance Digital Threads.

.- International Situational Diagnosis on the Implementation of Smart Energy in Agribusiness.

.- Towards Knowledge-Driven Decision Support in Smart Manufacturing: Challenges and Research Opportunities.

.- A Discussion of Data-Driven and Knowledge-Driven Approaches in ManuflS“

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