The Department of Industrial Engineering embraces a diverse range of research interests that reflect both traditional and emerging areas of the discipline. Faculty members focus on advancing industrial systems’ efficiency, sustainability, and technological innovation. Their research spans from optimization, artificial intelligence, and quality management to smart and sustainable manufacturing. The following clusters summarize the department’s main research themes after consolidating and integrating overlapping areas.
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Supply Chain & Logistics Optimization
Developing integrated models for resilient and sustainable supply chains
Enhancing two-phase supply chain network distribution mathematically
Applying Lean Six Sigma and architecture development methods for continuous supply chain optimization
Supply chain conceptual framework optimization
Decision-making frameworks in industrial, supply chain, and energy systems
Assessing resilience and mitigation strategies in supply chains
Reduce e-commerce delivery times via machine learning
Industrial & Manufacturing Systems Optimization
Optimizing industrial systems mechanisms
Enhancing industrial performance through simulation and multi-objective optimization
Modeling human resource flexibility in industrial scheduling and planning
Scheduling energy consumption models
Developing sustainable multi-objective optimization models
Multi-objective optimization of reconfigurable manufacturing transfer line supported by digital twin
AI-powered predictive maintenance in Industry 4.0
Robotics optimization under Industry 4.0
Organization structure and manpower utilization in project offices
Smart Manufacturing & Industry 4.0 Technologies
Digital twin integration for smart factories
Digital twin of Jidoka simulator to optimize predictive techniques
Digital twin calibration of industrial robots
Digital twin-based additive manufacturing process control
AI-driven defect detection in advanced manufacturing
FDM parameter optimization via deep learning
Additive manufacturing of soft robots
Industry 4.0 adoption: modeling drivers in emerging economies
Smart and digital transformation in quality engineering
Sustainability & Circular Economy
Integrating circular economy principles into production systems
Optimize circular economy using digital twin
Sustainable advanced manufacturing process through process optimization
Lean Six Sigma applications in sustainable manufacturing and project delivery
Modelling Total Quality Management (TQM) implementation factors for sustainable building projects
Integration of quality management systems with green construction and Vision 2030 objectives
Risk management frameworks for sustainable project performance
Quality, Lean & Performance Management
An integrated Lean-DMAIC framework to enhance manufacturing plant performance
Performance evaluation using data envelopment analysis
Data-driven process optimization in industrial and construction systems
Materials & Manufacturing Processes
Study of mechanical and corrosion properties of ATIG welded joints
Effect of oxide flux on weld shape, mechanical properties, and corrosion resistance of stainless-steel welds
Mechanical properties of friction stir processed B4C/Gr-reinforced hybrid composite fabricated through stir casting method
Material removal rate prediction for electro discharge machining
Mathematical Modeling & Optimization
Mathematical and multi-objective programming (LP, IP, NLP, GP)
Optimization tools: LINGO, GAMS, IBM ILOG- CPLEX, Excel Solver, MATLAB
Heuristic and metaheuristic optimization (GA, SA, PSO, WOA)
Simulation & Systems Modeling
Simulation: Arena, Simio, MATLAB
System dynamics: VENSIM, MATLAB
System modeling, inventory management, and project scheduling: MS Project, SAP ERP, Visual Basic
Work systems design
Statistical & Data Analysis
Statistical analysis: Minitab, SPSS, XLSTAT, Power BI
Predictive modeling: ARIMA, SARIMA, ANN, Holt–Winters
Regression analysis and statistical inference
Design of Experiments (DOE)
Fuzzy Logic & Multi-Criteria Decision Making (MCDM)
Fuzzy logic and MCDM methods: AHP, TOPSIS, QFD, DEMATEL
Programming & Computational Tools
MATLAB, Python, Java
Computational platforms for modeling, optimization, and data analytics
Machine learning and deep learning
Engineering & Manufacturing Tools
CAD/SmartDraw
Finite Element Analysis (ANSYS, ABAQUS)
TIG welding, Oxide flux, and corrosion testing (EC-Lab software)
Robotics
1. Smart & Sustainable Manufacturing Systems
Sustainable and smart manufacturing systems
Lean Six Sigma for sustainable manufacturing
Incorporating human-machine collaboration and sustainability objectives into multi-objective optimization frameworks
Human-centered and adaptive scheduling under Industry 5.0 paradigm
Deep reinforcement learning for factory layout planning for flexible transfer lines
2. Artificial Intelligence & Digital Twins in Industrial Systems
Integration of AI and digital twins in industrial systems planning and control
Hybridization of AI and digital twins to predict laborers' behavioral disturbances and prevent risky events (Poka-yoke system)
Real-time scheduling adaptation using digital twins and AI
Integration of AI with operations research techniques
AI and data analytics for quality and risk management
3. Green Supply Chain & Sustainable Production
Green supply chain optimization and carbon-neutral production strategies
Sustainable and data-driven decision frameworks for industrial systems
Advanced forecasting frameworks for energy, environmental, and economic sustainability
4. Digital Transformation & Industry 4.0/5.0 Applications
Digital transformation and Industry 4.0 applications
Robotics in Industry 4.0 and 5.0
Assigning laborers according to the Industry 5.0 & Respect for People paradigm
Industry 4.0 challenges: Modeling drivers in emerging economies
5. Quality, Risk & Performance Management
Integration of TQM and sustainability in smart construction projects
Performance measurement aligned with Vision 2030
