
Understand time-based forecasting horizons: short-term forecasting for less than one year, medium-term for one to two years, and long-term for more than two years.
Explore forecasting errors in industrial engineering, including mean absolute deviation, mean squared error and its standard deviation, bias, mean absolute percentage error, and the tracking signal.
Compute line efficiency as 0.8 (48 over 10×6), with a 20% balance delay and smoothing index 6; car wash needs five stalls for 60 cars per hour.
Explore two diagram types: floor diagrams showing parts, materials, and equipment on a factory scale model, and string diagrams mapping movements on a time-scale model to study movement density.
Lean manufacturing is an operational system that maximizes value by reducing diverse activities in a value stream, classifies activities into production, inventory, motion, over-processing, and transportation, and uses just-in-time production.
Explore seven quality control tools, including histogram, Pareto analysis, cause-and-effect (fishbone) diagrams, defect concentration diagrams, scatter diagrams, textures, and the control chart.
Explore quality circles as voluntary worker groups to improve processes, and examine total quality management as a systematic, top-management driven, customer-focused approach with continuous improvement and poka-yoke, including Six Sigma.
Industrial Engineering is an engineering discipline that deals with utilizing and coordinating humans, machines, and materials to attain the desired output rate with the optimum utilization of energy, knowledge, money, and time. It also employs certain techniques (such as floor layouts, personnel organization, time standards, wage rates, incentive payment plans) to control the quantity and quality of goods and services produced.
This course covers various topics like Forecasting, Queuing theory, Line Balancing, Production Planning and Control, Quality Control, Reliability and various Inventory Control Techniques.