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Deadline for Abstract Submission Extended to December 31, 2024

The intersection of Artificial Intelligence (AI) and Machine Learning (ML) with mechanical systems and engineering applications marks a transformative era in the field of engineering. This dynamic convergence holds the promise of revolutionizing traditional mechanical engineering practices, offering innovative solutions to complex challenges, and driving unparalleled advancements in various sectors.

Mechanical systems, encompassing a wide array of machinery, equipment, and devices, are undergoing a paradigm shift with the integration of AI and ML technologies. These systems, once reliant on deterministic algorithms and manual interventions, are now empowered with the capability to learn, adapt, and optimize their operations autonomously. AI and ML algorithms are being employed for predictive maintenance, quality control, process optimization, and robotic automation, among other applications, leading to enhanced efficiency, reliability, and flexibility in mechanical systems.

The application of AI and ML in engineering extends far beyond mechanical systems, permeating diverse domains such as aerospace, automotive, manufacturing, robotics, healthcare, and infrastructure. In these applications, AI and ML techniques are driving innovation by enabling predictive modeling, design optimization, materials discovery, energy management, and supply chain optimization, among other functionalities. From designing high-performance materials to orchestrating complex manufacturing processes, AI and ML are reshaping the landscape of engineering applications, offering unprecedented opportunities for efficiency gains, cost savings, and sustainable development.

We invite authors to submit original research papers and abstracts addressing the following topics 

• AI-Driven Design:

  • • Application of AI in optimizing mechanical design.

    • Integration of ML algorithms for enhancing materials and processes.

    • Generative design and design automation.

    • Design optimization for improved performance and efficiency.

    • Case studies on AI-empowered product lifecycle management.

•  Predictive Maintenance and Condition Monitoring:

  • • ML models for predicting failures and extending the lifespan of mechanical systems.

    • Implementation of AI in real-time monitoring for energy efficiency.

    • Advanced diagnostics and prognostics for efficient operations.

    • Fault detection and diagnosis.

    • Quality control and process optimization.

•  Energy Efficiency and Green Technologies:

  • • AI applications in renewable energy systems and smart grids.

    • Optimization of energy consumption in manufacturing processes through ML.

    • AI in the development of efficient transportation and automotive systems.

    • Energy management and sustainability strategies.

•  Manufacturing Innovations:

  • • Use of AI to minimize waste and emissions in manufacturing.

    • ML techniques for optimizing resource utilization and recycling.

    • AI-driven innovations in additive manufacturing (3D printing).

    • Production planning and scheduling.

    • Process optimization for manufacturing systems.

• Smart Materials and Structures:

  • • AI-enabled design and analysis of innovative materials.

    • ML approaches for adaptive and resilient structural systems.

    • Case studies on the use of AI in developing advanced composites.

    • Materials discovery, characterization, and analysis.

•  Environmental Impact Assessment:

  • • AI and ML for assessing and mitigating the impact of mechanical systems.

    • Development of AI tools for lifecycle assessment and impact metrics.

    • Innovative approaches to integrating AI in monitoring and control.

•  Supply Chain and Logistics:

  • •  AI and ML applications in optimizing supply chain efficiency.

    • Enhancing logistics and transportation through intelligent algorithms.

    • Case studies on practices in global supply chains driven by AI.

    • Supply chain optimization for improved efficiency.

•  Robotics and Automation:

  • •  AI-driven advancements in robotics systems and automation.

    •  Human-machine collaboration for enhanced productivity.

    •  Applications of AI in robotics for manufacturing and other industries.

• Aerospace and Automotive Systems:

  • •   AI and ML applications in aerospace and automotive engineering.

    •   Enhancing performance and safety in aerospace systems.

    •   Advanced AI techniques for automotive systems.

• VAC and Power Generation Systems:

  • •   AI applications in optimizing HVAC systems for better performance.

    •   ML-driven advancements in power generation systems for efficiency and reliability.

Submissions are accepted in the form of abstracts or full papers. Authors should carefully follow the guidelines below:

• Abstract Length: Maximum 500 words.

• Full Paper Length: Maximum 10 pages (including references, figures, and appendices).

• Submission Format: PDF or DOC format.

• Submission Platform: Abstracts and full papers must be submitted through the CMT platform ( https://cmt3.research.microsoft.com/iMECHCON2025 ).

• Important Dates: All deadlines are final. Late submissions will not be accepted.

Authors must ensure their submissions meet the following criteria:

• Formatting: Submissions should be formatted according to IEEE guidelines (or any specific format that applies).

• Originality: Papers must be original and unpublished. Plagiarism will result in rejection.

• Citation Style: Use APA/IEEE referencing style.

• Language: All papers must be written in English. 

• Authors should submit their papers using the official CMT conference platform. The submission link will be available on this page soon.

• Ensure that all files are properly formatted and meet the conference requirements before submission.

Please note the key dates for the AIML 2025 conference:

• Abstract Submission Deadline: December 31, 2024 (Extended)

• Notification of Acceptance: January 1, 2025 (Extended)

• Last Date for Payment of Registration Fee: January 2 2025 (Extended)

• Full Length Paper Submission Deadline: January 8, 2025

• AIML 2025 Conference dates: January 9-11, 2025

Mr. Venkatesh Duraisamy, Director, Data Engineering - Memory Technology, Western Digital, Bengaluru, India 

• Engineering Applications of Artificial Intelligence ( Supports Open Access)

• Applied Artificial Intelligence ( Fully Open access)

Note: 

Following the conference presentations, a selection of abstracts will be recommended for inclusion in a special issue of one of the following journals. Authors of these selected works will be invited to submit their full papers for a formal peer review process conducted by the journal. Please note that while every effort will be made to facilitate this opportunity, selection or recommendation does not guarantee publication, and all final publication decisions rest solely with the journal’s editorial board.

Any applicable article processing charges to be paid.

• Dr. Mohan R, Professor, School of Mechanical Engineering, VIT Chennai

• Dr. Raghukiran Nadimpalli, Associate Professor, School of Mechanical Engineering, VIT Chennai 

Email your queries to chennai.aiml@vit.ac.in

• Dr. Padmanabhan R, Professor, School of Mechanical Engineering, VIT Chennai

• Dr. Devaprakasam D, Professor, School of Mechanical Engineering, VIT Chennai

• Dr. Lakshmi Pathi Jakkamputi, Associate Professor, School of Mechanical Engineering, VIT Chennai

• Dr. Anshuman Das, Associate Professor, School of Mechanical Engineering, VIT Chennai

• Dr. Abhishek Rudra Pal, Assistant Professor, School of Mechanical Engineering, VIT Chennai

• Dr. Gajanand Gupta, Assistant Professor, School of Mechanical Engineering, VIT Chennai

• Dr. Awani Bhushan, Assistant Professor, School of Mechanical Engineering, VIT Chennai