Course Objectives
- To provide information about the applications and benefits of the real-time locating systems, in
supply chain management. - To give advanced level information about the demand forecasting by means of the Time series
Analysis. - To give advanced level information about the demand forecasting by means of the Artificial
Neural Networks. - To make students earn skills of analyzing and comparing alternative supply chain configurations
by simulation and Statistical Analysis techniques.
Topics
- Introduction of the Basic Concepts of the Supply Chain Analytics
- Descriptive Analytics Applications of Object Positioning by means of GPS, RFID, RTLS Technologies
- Real-Life Examples of Descriptive Analytics from Several Sectors
- Predictive Analytics: Seasonality and trend analysis in demand data; data cleaning
- Time Series Models- Demand Forecasting by Regression
- Demand Forecasting by Artificial Neural Networks with Multi-Factors
- Supply chain network optimization and modelling
- Simulation modeling of the alternative supply chain configurations
- Statistical Analysis and Comparison of the alternative supply chain configurations
- Case Study on Demand Forecasting Techniques
- Case Study on Performance Analysis of the alternative supply chain configurations