Preparing your Path…
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Path Catalog
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7801 Paths · page 306 / 781
This learning path equips graduate students with an advanced understanding of human-robot collaboration (HRC) in industry. It covers foundational robotics concepts, industrial safety standards, human factors, and user experience design, culminating in the ability to design and evaluate HRC systems.
This path equips graduate students in industrial engineering with the conceptual and technical foundations to understand and evaluate blockchain applications in supply chain management. It covers blockchain fundamentals, traceability, and smart contracts, emphasizing their roles in enhancing transparency, efficiency, and trust.
This learning path equips graduate students in industrial engineering with the knowledge and skills to apply AI techniques to operations management, focusing on demand forecasting and optimization. It covers essential data analytics foundations, machine learning methods, and practical implementation strategies for real-world operations challenges.
This advanced path for senior or graduate students in industrial engineering covers the foundational concepts and enabling technologies of smart manufacturing, including manufacturing systems, IoT, cyber-physical systems, data analytics, and digital twins. Learners will integrate these technologies to understand modern smart factories.
This learning path equips quality professionals with the knowledge and skills to implement Total Quality Management (TQM) in their organizations. It covers the foundational principles of TQM, the critical role of leadership, and the systematic processes for continuous improvement. The path progresses from core concepts to practical application, ensuring learners can drive a culture of quality and achieve organizational excellence.
This learning path equips supply chain professionals with the knowledge to design and control effective inventory systems. It covers foundational inventory concepts, demand forecasting, inventory classification, and key inventory control models, culminating in a holistic system design project.
This learning path equips productivity professionals with advanced skills in work measurement, method improvement, and incentive systems. It covers time study, work sampling, predetermined time systems, method study, and incentive plan design, with a focus on practical application in industrial settings.
This path equips plant engineers with the knowledge and skills to effectively manage maintenance operations in industrial facilities. It covers core principles of maintenance management, including preventive and predictive maintenance, reliability-centered maintenance (RCM), computerized maintenance management systems (CMMS), and downtime analysis. The path emphasizes the strategic importance of maintenance for operational efficiency and asset reliability.
This learning path equips management professionals with the knowledge and skills to design, implement, and use performance measurement systems in an industrial context. It covers foundational statistics, KPI development, balanced scorecard, benchmarking, and dashboard creation, enabling learners to drive data-informed decisions.
This path equips process improvement professionals with the knowledge and skills to apply structured process redesign methodologies. It covers process mapping, analysis, redesign approaches, and change management, culminating in a capstone project.