ICSMDM · Registering as Listener

International Conference on Smart Manufacturing and Data Mining

23rd Dec – 24th Dec 2026 Najaf, Iraq Standard / Physical Participation
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ConferenceICSMDM
ModeStandard / Physical
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Conference Session Tracks
SDG Wheel

SDG-Aligned Research Themes

International Conference on Smart Manufacturing and Data Mining conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 9 - Industry, Innovation and Infrastructure SDG 12 - Responsible Consumption and Production SDG 13 - Climate Action

This track focuses on the latest advancements in smart manufacturing technologies, emphasizing the integration of data mining techniques. Participants will explore how these innovations enhance operational efficiency and productivity.

This session highlights the role of data mining in the Industrial Internet of Things, showcasing case studies and applications. Attendees will discuss how data-driven insights can optimize industrial processes and improve decision-making.

This track delves into predictive maintenance methodologies powered by data mining and machine learning. The focus will be on how these strategies can reduce downtime and enhance equipment reliability in manufacturing settings.

Participants in this session will examine various data mining techniques for process optimization in manufacturing environments. The discussions will center on methodologies that lead to improved efficiency and reduced operational costs.

This track addresses the use of data analytics in monitoring and improving production performance. Attendees will explore key performance indicators and analytical methods that drive manufacturing excellence.

This session focuses on the application of digital twin technology in smart manufacturing. Participants will discuss how data mining can enhance the accuracy and utility of digital twins for real-time monitoring and simulation.

This track investigates the application of machine learning algorithms in quality control processes. The session will highlight how data mining can identify defects and improve product quality in manufacturing.

This session explores how data mining techniques can streamline workflows in manufacturing environments. Discussions will focus on optimizing resource allocation and minimizing bottlenecks.

Participants will examine the impact of big data analytics on smart manufacturing processes. This track will highlight the challenges and opportunities presented by large datasets in driving innovation.

This session focuses on the intersection of sustainability and data mining in manufacturing. Attendees will discuss strategies for reducing environmental impact while maintaining efficiency through data-driven approaches.

This track will explore emerging trends and future directions in smart manufacturing, with a focus on data mining innovations. Participants will engage in discussions about the potential impact of these trends on the industry.

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