Industrial Engineering, B.S.

Industrial engineering (IE )which includes operations research and systems analysis is a field of study for individuals who are interested in analyzing and formulating abstract models of complex systems with intention of improving system performance. Unlike other traditional engineering disciplines and sciences, the industrial engineering considers the role of the human decision-maker as a key component of the complexity of systems.

IE applies mathematics to business processes to improve efficiency and productivity. IE uses technology to properly manage resources, including workers, and designs and analyzes complex systems that integrate technical, economic, and social factors for all types of organizations.

IE’s methodologies involve probability, statistics, optimization, economic decision analysis, and computer science. Important application areas are supply chain systems, manufacturing, quality control, economic and financial systems, energy systems, healthcare systems and many others.

IE areas of study are Systems Engineering, Facilities Engineering and Planning, Operations Engineering, Work Design and Quality Engineering. To help explain these areas, a sample of the topics taught in these areas is listed below. This list is from the NCEES, 2020, Principles and Practices for IE. These are the topics IE’s must know to pass the professional engineering examination.

1. Systems Engineering A. System analysis and design tools (e.g., flowcharts, Pareto charts, affinity diagrams, nominal group technique, input/output analysis, value stream mapping) B. Requirements analysis (e.g., Quality Function Deployment, functional requirements, constraints) C. Performance measures and applications (e.g., cost, environmental sustainability, output) D. Modeling techniques (e.g., simulation, queuing, linear programming, graph theory and networks, Markov chains) E. Process types (e.g., discrete versus continuous, manufacturing, service) F. Model assessment (e.g., interpretation, verification, validation, sensitivity analysis) G. Bottleneck analysis (e.g., theory of constraints) H. Value analysis and engineering I. Project management and planning (e.g., PERT/CPM/CCPM: risk analysis, cost, scope, and time; Gantt charts).
2. Facilities Engineering and Planning A. Process flow B. Layout design techniques (e.g., systematic layout planning [SLP], affinity diagram, relationship diagrams, center of gravity rule) C. Space analysis (e.g., equipment needs, demand, location, footprint of the equipment/WIP sizing, warehousing) D. Capacity analysis (e.g., calculation of personnel requirements, calculation of machine requirements) E. Cost-benefit analysis F. Site selection factors and methods (e.g., prioritization, factor weighting, network optimization) G. Unit load analysis H. Facility life cycle cost analysis (e.g., acquisition, implementation, sustainment, retirement) I. Material handling techniques and equipment (e.g., conveyors, industrial trucks, manual, overhead crane)
3. Operations Engineering A. Forecasting methods (e.g., time series, causal models, qualitative techniques) B. Production planning methods (e.g., capacity planning, materials planning, JIT, lot sizing, workforce planning, aggregate planning) C. Engineering economics (e.g., break-even analysis, technical capability assessment, ROR) D. Costing systems (e.g., activity-based costing including cost drivers, guidelines for overhead, labor, materials) E. Production scheduling methods (e.g., shortest processing time first, due date order) F. Inventory management and control policies (e.g., deterministic, stochastic) G. Distribution models (e.g., transshipment, direct ship, cross docking, intermediate storage) H. Storage and warehousing methods I. Transportation modes (e.g., truckload [TL], less than truckload [LTL], air, rail, ship)
4. Work Design A. Methods for analysis and improvement (e.g., therbligs, motion study, man-machine charts) B. Line balancing C. Work measurement systems techniques (e.g., stopwatch, predetermined time systems, proprietary process determined time system) D. Learning curves E. Sample size calculations F. Work sampling analysis G. Safety codes, standards, and voluntary guidelines (e.g., ANSI, OSHA, MIL STD, NIOSH) 3 H. Methods for quantifying risk factors (e.g., NIOSH lifting equation, OSHA limits for noise, coefficient of friction, RULA) I. Limits of human capacity (e.g., strength, endurance, metabolic energy, range of motion, vision, hearing, skeletal-joint force analysis, exposure) J. Lifting aids (e.g., hoist, cranes, lifting tables) K. Link analysis and associated criteria (e.g., importance, frequency of use) L. Workplace design/human–computer interaction (e.g., use of anthropometric data) M. Days Away, Restricted and Transferred (DART) rate calculations (e.g., injury/illness incident rate and/or management of information required to calculate this rate) N. Manufacturing/service process planning (e.g., selection of operations, sequence, instructions, tooling and fixturing, mistake proofing)
5. Quality Engineering A. Statistical process control (e.g., control chart construction and interpretation) B. Process capability analysis (e.g., Cpk, Cp) C. Acceptance sampling (e.g., single sampling, double sampling, MIL STD 105E, Dodge Romig, OC-curves) D. Quality systems (e.g., Deming, TQM, ISO 9000, benchmarking) E. Techniques for process improvement (e.g., design of experiments [DOE], Taguchi, FMEA) F. Reliability analysis G. Maintenance procedures (e.g., reactive, preventive, predictive) H. Root cause analysis