Conference Session Tracks
Aligned with
UN Sustainable Development Goals
This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.
SDG 8
Decent Work and Economic Growth
SDG 9
Industry, Innovation and Infrastructure
SDG 12
Responsible Consumption and Production
Track 01
Statistical Methods in Industrial Engineering
This track focuses on the application of statistical methods to solve complex problems in industrial engineering. Topics may include quality control, reliability analysis, and process optimization.
Track 02
Data Analytics for Operations Management
This session explores the role of data analytics in enhancing operations management practices. Emphasis will be placed on predictive modeling, big data applications, and decision-making frameworks.
Track 03
Optimization Techniques in Engineering
This track examines various optimization techniques applicable to engineering problems. Participants are encouraged to present research on linear programming, integer programming, and heuristic methods.
Track 04
Statistical Quality Control
This session delves into statistical quality control methodologies used in manufacturing and service industries. Topics include control charts, process capability analysis, and Six Sigma methodologies.
Track 05
Industrial Engineering and Operations Research
This track highlights the intersection of industrial engineering and operations research. Contributions may include case studies, theoretical advancements, and innovative applications in various sectors.
Track 06
Simulation Modeling in Industrial Systems
This session focuses on the use of simulation modeling to analyze and improve industrial systems. Researchers are invited to present their findings on discrete-event simulation, Monte Carlo methods, and system dynamics.
Track 07
Statistical Inference and Decision Making
This track addresses the role of statistical inference in decision-making processes within industrial contexts. Topics may include hypothesis testing, confidence intervals, and Bayesian approaches.
Track 08
Supply Chain Analytics and Optimization
This session explores analytical methods for optimizing supply chain operations. Discussions will cover inventory management, logistics optimization, and demand forecasting techniques.
Track 09
Machine Learning Applications in Engineering
This track investigates the integration of machine learning techniques in engineering disciplines. Participants are encouraged to share insights on algorithm development, model validation, and real-world applications.
Track 10
Statistical Modeling for Industrial Processes
This session focuses on the development and application of statistical models to understand and improve industrial processes. Topics may include regression analysis, time series forecasting, and multivariate analysis.
Track 11
Risk Analysis and Management in Engineering
This track examines methodologies for risk analysis and management in engineering projects. Contributions may include risk assessment frameworks, uncertainty quantification, and mitigation strategies.
