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ML

Automation of Production Planning and Control

Automation of Production Planning and Control

A deep dive into production control with intelligent agents
Jonas Schneider, Peter Nyhuis ORCID Icon, Matthias Schmidt
How can artificial intelligence (AI) automate production planning and control? This study examines its potential to enhance efficiency in modern production environments. The focus is on establishing a robust data infrastructure that integrates real-time, historical, and contextual data to create a solid basis for AI models. Reinforcement learning (RL) is applied to aid automation. A roadmap for implementation, focusing on practical application, is presented. This roadmap incorporates simulation-based training methods and outlines strategies for continuous improvement and adaptation of production processes.
Industry 4.0 Science | Volume 41 | 2025 | Edition 5 | Pages 86-93 | DOI 10.30844/I4SE.25.5.84
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  • I4S+
  • Industry 4.0
    • Automation
    • Digital Twin
    • Factory Planning
    • Industry 4.0
    • Internet of Things
    • Lean Production
    • Sustainability
    • Manufacturing Systems
    • Adaptability
  • Artificial Intelligence
  • Functions
    • Start-up Management
    • Maintenance
    • Logistics
    • Assembly
    • Product Development
    • Production Planning
    • Production Control
    • Process Management
    • Quality Management
    • Risk Management
    • Safety
  • Tools
    • Additive Manufacturing
    • Analytics
    • Augmented Reality
    • Blockchain
    • Modularization
    • Training
    • Robotics
    • Sensors
    • Simulation
    • Software
  • Management
    • Services
    • Dynamics
    • Energy Efficiency
    • Leadership
    • Business Models
    • Innovation
    • SME
    • Management
    • Product Piracy
    • Resource Efficiency
    • Strategy
    • Profitability
  • Journal
    • Current Issue
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    • All E-Journals
    • Annual Table of Contents
    • List of Reviewers
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