Concept
intelligent mechanical systems
Parents
Children
Applied SciencesCommunication EngineeringComputer-aided DesignComputer-aided EngineeringComputer-aided Manufacturing
815
Publications
37.3K
Citations
2.7K
Authors
1K
Institutions
AI-Driven Intelligent Mechanical Systems
2018 - 2024
The era centers on AI-powered predictive maintenance using Internet of Things sensors, edge-cloud compute, and machine learning to forecast faults and optimize maintenance across manufacturing and logistics. AI integration with Digital Twins enables real-time monitoring, scenario testing, and cognitive decision support for maintenance and lifecycle management in buildings and industrial plants. AI-driven design for Industry 5.0 emphasizes human–machine collaboration, resilient teamwork, and intelligent Manufacturing Execution Systems architectures to support cooperative factory operations, while AI contributes to sustainability by optimizing energy use in HVAC and automated logistics. Historical Significance: This period marks a unifying paradigm of AI-enabled cyber-physical systems, integrating human-centered design with system-wide optimization, interoperability, and governance. These developments laid the groundwork for scalable, trustworthy intelligent maintenance ecosystems across industry and built environments.
• Artificial Intelligence (AI) powered predictive maintenance uses IoT sensors, edge-cloud compute, and machine learning to forecast faults and optimize maintenance scheduling across manufacturing and logistics domains [1], [4], [5], [16], [9].
• Artificial Intelligence (AI) integrated with Digital Twins enables real-time monitoring, scenario testing, and cognitive decision support for maintenance and lifecycle management in buildings and industrial plants [20], [8].
• Artificial Intelligence (AI) driven design for Industry 5.0 emphasizes human–machine collaboration, resilient teamwork and intelligent MES architectures to support cooperative factory operations [19], [13], [7].
• Artificial Intelligence (AI) contributes to sustainability and energy efficiency by optimizing automated logistics, maintenance planning, and HVAC systems' energy use [2], [9], [15], [11].
• Artificial Intelligence (AI) in engineering prompts new theoretical patterns and standards, highlighting how AI-enabled systems differ from traditional software and require new design approaches and governance [3], [7], [6], [14].