Industrial Engineering (IND)

Section Information

Industrial Engineering focuses on designing, optimizing, and managing complex systems involving people, materials, equipment, energy, and information. It aims to improve efficiency, productivity, quality, and sustainability across manufacturing, logistics, services, and organizational operations.

Modern industrial engineering integrates analytical modeling, data science, automation, human factors, and advanced computational tools to enhance system performance. The field supports decision-making, process improvement, supply chain optimization, and smart manufacturing in diverse industries.

This section publishes research articles, case studies, and reviews covering operations research, production systems, quality engineering, human–machine interaction, logistics, decision sciences, and emerging technologies that shape industrial processes and enterprise systems.

Scope

Operations Research and Decision Sciences
- Optimization, linear and nonlinear modeling
- Stochastic processes, queuing, and simulation
- Decision analysis, predictive analytics, and risk modeling
- Scheduling, resource allocation, and mathematical planning
Manufacturing and Production Systems
- Factory layout, production planning, and workflow design
- Lean manufacturing, Six Sigma, and process improvement
- Automation, robotics, and smart manufacturing systems
- Maintenance engineering, reliability, and asset management
Supply Chain and Logistics Engineering
- Supply chain design, integration, and coordination
- Inventory control, warehousing, and distribution networks
- Transportation systems and logistics optimization
- Demand forecasting and supply chain analytics
Human Factors and Ergonomics
- Human–machine interaction and workplace design
- Cognitive engineering, safety, and usability studies
- Ergonomic assessment and worker performance enhancement
- Human-centered system design and organizational behavior
Quality Engineering and Management
- Quality control, inspection, and reliability testing
- Statistical process control and design of experiments
- Total Quality Management (TQM) and continuous improvement
- Product lifecycle quality and risk management
Systems Engineering and Enterprise Integration
- System modeling, architecture, and lifecycle management
- Integration of people, processes, and technologies
- Cyber-physical systems and digital transformation
- Process automation, information systems, and enterprise analytics
Emerging Topics in Industrial Engineering
- Industry 4.0, IoT, and cyber-physical production systems
- AI- and data-driven decision support tools
- Sustainable operations and circular economy
- Robotic collaboration, smart factories, and autonomous logistics