07/12/2025 Call for Paper

International Conference on AI and Concurrent Engineering (AICE-2026) to be held at IIMT, Bhubaneswar, India, during August 21st-22nd, 2026 invites original papers from the academicians, researchers and industry practitioners from the fields of AI and Concurrent Engineering. The primary goal of AICE-2026 aims at attracting scholars and professionals to present and publish up-to-date ideas and innovation in all areas related to Concurrent Engineering in various industries and in driving the new-generation economy, society, and government at large.

The scope of the conference has been kept wide but is not limited to:

Theme 1: Advanced Concurrent Engineering Practices

1. • Integrated multi-disciplinary design methodologies
2. • Simultaneous design, testing, and production planning
3. • Workflow synchronization in distributed engineering teams
4. • Collaborative platforms for parallel product development
5. • Best practices and challenges in scaling concurrent engineering
6. • Real-time collaboration tools for engineering design
7. • Knowledge management in concurrent engineering environments
8. • Process re-engineering for enhanced product development
9. • Digital thread integration across design stages
10. • Case studies on successful concurrent engineering implementations
11. • Sustainable concurrent engineering strategies
12. • Human–machine collaboration in concurrent workflows
13. • Interoperability frameworks for cross-domain engineering tools

Theme 2: AI-Driven Design and Optimization in Engineering

1. • AI-enabled tuning of design parameters
2. • Machine learning for multi-objective design optimization
3. • Deep learning-based generative design for concept creation
4. • Reinforcement learning for iterative design improvements
5. • Data-driven simulation for performance forecasting
6. • Predictive analytics for design feasibility assessments
7. • Neural network applications in exploring design trade-offs
8. • AI algorithms for virtual prototyping
9. • Optimization of product configurations through AI
10. • Integration of AI with traditional design methods
11. • Computational intelligence for lightweight and smart materials design
12. • AI-assisted sustainable product development
13. • Autonomous design agents for engineering creativity and innovation

Theme 3: Real-Time Monitoring, Adaptive Control, and Predictive Analytics

1. • Real-time sensor data analysis for dynamic design feedback
2. • AI for predictive maintenance and quality assurance
3. • Adaptive control systems in production environments
4. • Feedback loops using digital twin integration
5. • AI-based process anomaly detection and troubleshooting
6. • Machine learning for real-time decision support
7. • Intelligent control systems in concurrent engineering
8. • Cyber-physical integration for responsive manufacturing
9. • Data fusion techniques for real-time process analytics
10. • Automated system monitoring for continuous improvement
11. • Edge AI for smart production environments
12. • Autonomous fault-tolerant industrial systems
13. • Zero-defect manufacturing with AI-enabled error correction

Theme 4: Data-Driven Collaboration and Digital Twin Technologies

1. • Integration of heterogeneous design data through AI
2. • Cloud-based simulation and collaborative design tools
3. • Digital twins for real-time design iteration and validation
4. • AI-enhanced synchronization across multi-disciplinary teams
5. • Unified analytics frameworks for product lifecycle management
6. • AI-driven knowledge management in engineering design
7. • Collaborative platforms with integrated decision support
8. • Big data analytics in concurrent engineering workflows
9. • Enhanced communication protocols for digital threads
10. • Virtual and augmented reality for collaborative design reviews
11. • Mixed-reality environments for immersive engineering
12. • Blockchain-enabled engineering data governance
13. • Secure data pipelines for global collaborative engineering

Theme 5: Emerging Trends and Industrial Applications in AI-Integrated Engineering

1. • Case studies on AI integration in concurrent engineering projects
2. • Disruptive innovations in automated design processes
3. • Sustainable and resilient design via AI-driven strategies
4. • Scaling AI solutions for industrial product development
5. • Future directions in integrated digital transformation
6. • Convergence of simulation, prototyping, and production analytics
7. • AI for adaptive manufacturing and smart factory solutions
8. • Robotics and autonomous systems in concurrent engineering
9. • Leveraging Industry 4.0 for enhanced product lifecycle management
10. • Cross-sector applications of AI in modern engineering design
11. • AI in circular manufacturing and remanufacturing processes
12. • Standards and ethics in AI-enabled engineering systems
13. • Workforce transformation in AI-driven engineering industries