IND 3510 - Fundamentals of Enterprise Operations for Engineers

• Define and explain common terminology related to IE tools and methods
• Demonstrate an ability to use quality and process improvement tools and techniques such as value stream mapping, cause-and-effect analysis, SIPOC diagrams, 5S system, and flowcharts among others
• Develop a project charter using project management terminology
• Interpret a basic time study
• Read and interpret a bill of materials, process routing, and production schedule
• Calculate a net present worth, a rate of return, and a payback period of a static cash-flow
• Recognize the basic types of factory layouts in contemporary use
• Summarize and explain software common to industry (e.g., ERP, statistical software, etc.)
• Develop a project plan including objective(s), scope, and boundaries of a project around the triple constraint (i.e., cost, schedule, and technical performance), as well as project metrics and deliverables
• Describe the differences between deterministic and stochastic modeling
• Apply linear programming to various organizational or industry problems to determine optimal solution
• Explain the importance of ergonomics in workplace health and safety
• Recognize and describe how different forms of process simulation can be applied to business situations
• Describe the various components of supply chain processes
• Explain the role of data analytics in business and how each type can be applied to specific problem categories

• Basic understanding of probability and statistics
• Linear equations
• Matrix equations

• Project management (with learning curves), change management, and facilitation
• Engineering economic analysis
• Facilities layout
• The Internet of Things (IoT) and ERP
• Automation
• Ergonomics/human factors and work systems
• Quality including Six Sigma and Lean concepts
• Logistics, distribution, and transportation
• Quantitative methods for decision-making
• Forecasting methods
• Inventory models
• Linear programming models: graphical and computer methods
• Linear programming applications
• Queuing models
• Mathematical programming and simulation modeling