ICADSSM · Registering as Listener

International Conference on AI-driven Data Science for Smart Manufacturing

20th Oct – 21st Oct 2026 New York, USA Standard / Physical Participation
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ConferenceICADSSM
ModeStandard / Physical
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Conference Session Tracks
SDG Wheel

SDG-Aligned Research Themes

International Conference on AI-driven Data Science for Smart Manufacturing conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 7 - Affordable and Clean Energy SDG 8 - Decent Work and Economic Growth SDG 9 - Industry, Innovation and Infrastructure SDG 12 - Responsible Consumption and Production

This track focuses on the integration of artificial intelligence in industrial automation processes. It aims to explore innovative AI methodologies that enhance operational efficiency and reduce human intervention.

This session will delve into advanced predictive maintenance strategies powered by data analytics and machine learning. Participants will discuss case studies and frameworks that optimize maintenance schedules and reduce downtime.

This track examines the role of digital twins in simulating and optimizing manufacturing processes. Researchers will present their findings on how digital twin technology can enhance decision-making and operational performance.

Focusing on real-time data collection and analysis, this session will highlight tools and techniques for monitoring production efficiency. Discussions will include the impact of real-time analytics on decision-making and production outcomes.

This track explores the application of artificial intelligence in quality control processes within manufacturing. Participants will share insights on AI-driven inspection techniques and their effectiveness in ensuring product quality.

This session will cover the latest advancements in robotics and their applications in smart manufacturing environments. Topics will include collaborative robots and their role in enhancing productivity and safety.

This track focuses on the use of machine learning algorithms for optimizing manufacturing processes. Presentations will address various methodologies and their impact on efficiency and cost reduction.

This session will investigate how artificial intelligence can facilitate seamless integration across supply chain networks. Discussions will include AI applications that enhance visibility, responsiveness, and collaboration.

This track will explore the role of sensors in driving innovation within manufacturing settings. Participants will discuss how sensor data can be leveraged for improved monitoring and control of production processes.

This session will focus on the transformative impact of the Industrial Internet of Things on manufacturing operations. Topics will include connectivity, data management, and the integration of IoT devices into production systems.

This track will examine strategies for achieving energy efficiency in manufacturing through data-driven approaches. Researchers will present innovative solutions that minimize energy consumption while maintaining productivity.

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